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How to Evaluate Your RAG Pipeline with Synthetic Data?
Evaluating LLM applications, particularly those using RAG (Retrieval-Augmented Generation), is crucial but often neglected.Without proper evaluation, it’s almost impossible to confirm if your system’s retriever is effective, if the LLM’s answers are grounded in the sources (or hallucinating), and if the context size is optimal.The post How to Evaluate Your RAG Pipeline with Synthetic Data? appeared first on MarkTechPost.
SwiReasoning: Entropy-Driven Alternation of Latent and Explicit Chain-of-Thought for Reasoning LLMs
SwiReasoning is a decoding-time framework that lets a reasoning LLM decide when to think in latent space and when to write explicit chain-of-thought, using block-wise confidence estimated from entropy trends in next-token distributions.The method is training-free, model-agnostic, and targets Pareto-superior accuracy/efficiency trade-offs on mathematics and STEM benchmarks.Reported results show +1.5%–2.8% average accuracy improvements […]
Google Introduces Speech-to-Retrieval (S2R) Approach that Maps a Spoken Query Directly to an Embedding and Retrieves Information without First Converting Speech to Text
Google AI Research team has brought a production shift in Voice Search by introducing Speech-to-Retrieval (S2R).S2R maps a spoken query directly to an embedding and retrieves information without first converting speech to text.The Google team positions S2R as an architectural and philosophical change that targets error propagation in the classic cascade modeling approach […]
A Coding Implementation of Secure AI Agent with Self-Auditing Guardrails, PII Redaction, and Safe Tool Access in Python
In this tutorial, we explore how to secure AI agents in practical, hands-on ways using Python.We focus on building an intelligent yet responsible agent that adheres to safety rules when interacting with data and tools.We implement multiple layers of protection, such as input sanitization, prompt-injection detection, PII redaction, URL allowlisting, and rate limiting, […]
5 Most Popular Agentic AI Design Patterns Every AI Engineer Should Know
As AI agents evolve beyond simple chatbots, new design patterns have emerged to make them more capable, adaptable, and intelligent.These agentic design patterns define how agents think, act, and collaborate to solve complex problems in real-world settings.The post 5 Most Popular Agentic AI Design Patterns Every AI Engineer Should Know appeared first on MarkTechPost.
Sentient AI Releases ROMA: An Open-Source and AGI Focused Meta-Agent Framework for Building AI Agents with Hierarchical Task Execution
Sentient AI has released ROMA (Recursive Open Meta-Agent), an open-source meta-agent framework for building high-performance multi-agent systems.ROMA structures agentic workflows as a hierarchical, recursive task tree: parent nodes break a complex goal into subtasks, pass them down to child nodes as context, and later aggregate their solutions as results flow back up—making the context […]The post Sentient AI Releases ROMA: An Open-Source and AGI Focused Meta-Agent Framework for Building AI Agents with Hierarchical Task Execution appeared first on MarkTechPost.
A Coding Guide to Master Self-Supervised Learning with Lightly AI for Efficient Data Curation and Active Learning
In this tutorial, we explore the power of self-supervised learning using the Lightly AI framework.We begin by building a SimCLR model to learn meaningful image representations without labels, then generate and visualize embeddings using UMAP and t-SNE.We then dive into coreset selection techniques to curate data intelligently, simulate an active learning workflow, and […]
Meet OpenTSLM: A Family of Time-Series Language Models (TSLMs) Revolutionizing Medical Time-Series Analysis
A significant development is set to transform AI in healthcare.Researchers at Stanford University, in collaboration with ETH Zurich and tech leaders including Google Research and Amazon, have introduced OpenTSLM, a novel family of Time-Series Language Models (TSLMs).This breakthrough addresses a critical limitation in current LLMs by enabling them to interpret and reason over […]
Liquid AI Releases LFM2-8B-A1B: An On-Device Mixture-of-Experts with 8.3B Params and a 1.5B Active Params per Token
Liquid AI has released LFM2-8B-A1B, a small-scale Mixture-of-Experts (MoE) model built for on-device execution under tight memory, latency, and energy budgets.Unlike most MoE work optimized for cloud batch serving, LFM2-8B-A1B targets phones, […]The post Liquid AI Releases LFM2-8B-A1B: An On-Device Mixture-of-Experts with 8.3B Params and a 1.5B Active Params per Token appeared first on MarkTechPost.
Meta Superintelligence Labs’ MetaEmbed Rethinks Multimodal Embeddings and Enables Test-Time Scaling with Flexible Late Interaction
What if you could tune multimodal retrieval at serve time—trading accuracy, latency, and index size—simply by choosing how many learnable Meta Tokens (e.g., 1→16 for queries, 1→64 for candidates) to use?Meta Superintelligence Labs introduces MetaEmbed, a late-interaction recipe for multimodal retrieval that exposes a single control surface at serving time: how many compact “Meta […]The post Meta Superintelligence Labs’ MetaEmbed Rethinks Multimodal Embeddings and Enables Test-Time Scaling with Flexible Late Interaction appeared first on MarkTechPost.
Agentic Context Engineering (ACE): Self-Improving LLMs via Evolving Contexts, Not Fine-Tuning
TL;DR: A team of researchers from Stanford University, SambaNova Systems and UC Berkeley introduce ACE framework that improves LLM performance by editing and growing the input context instead of updating model weights.Context is treated as a living “playbook” maintained by three roles—Generator, Reflector, Curator—with small delta items merged incrementally to avoid brevity bias and […]The post Agentic Context Engineering (ACE): Self-Improving LLMs via Evolving Contexts, Not Fine-Tuning appeared first on MarkTechPost.
Google Open-Sources an MCP Server for the Google Ads API, Bringing LLM-Native Access to Ads Data
Google has open-sourced a Model Context Protocol (MCP) server that exposes read-only access to the Google Ads API for agentic and LLM applications.The repository googleads/google-ads-mcp implements an MCP server in Python that surfaces two tools today: search (GAQL queries over Ads accounts) and list_accessible_customers (enumeration of customer resources).It includes setup via pipx, Google […]
What are ‘Computer-Use Agents’? From Web to OS—A Technical Explainer
TL;DR: Computer-use agents are VLM-driven UI agents that act like users on unmodified software.Gemini 2.5 Computer Use leads several web benchmarks (Online-Mind2Web 69.0%, WebVoyager 88.9%)Next steps center on OS-level robustness, sub-second action loops, and […]
Microsoft Research Releases Skala: a Deep-Learning Exchange–Correlation Functional Targeting Hybrid-Level Accuracy at Semi-Local Cost
TL;DR: Skala is a deep-learning exchange–correlation functional for Kohn–Sham Density Functional Theory (DFT) that targets hybrid-level accuracy at semi-local cost, reporting MAE ≈ 1.06 kcal/mol on W4-17 (0.85 on the single-reference subset) and WTMAD-2 ≈ 3.89 kcal/mol on GMTKN55; evaluations use a fixed D3(BJ) dispersion correction.It is positioned for main-group molecular chemistry today, with […]The post Microsoft Research Releases Skala: a Deep-Learning Exchange–Correlation Functional Targeting Hybrid-Level Accuracy at Semi-Local Cost appeared first on MarkTechPost.
Tiny Recursive Model (TRM): A Tiny 7M Model that Surpass DeepSeek-R1, Gemini 2.5 pro, and o3-mini at Reasoning on both ARG-AGI 1 and ARC-AGI 2
Can an iterative draft–revise solver that repeatedly updates a latent scratchpad outperform far larger autoregressive LLMs on ARC-AGI?Samsung SAIT (Montreal) has released Tiny Recursive Model (TRM)—a two-layer, ~7M-parameter recursive reasoner that reports 44.6–45% test accuracy on ARC-AGI-1 and 7.8–8% on ARC-AGI-2, surpassing results reported for substantially larger language models such as DeepSeek-R1, o3-mini-high, and […]The post Tiny Recursive Model (TRM): A Tiny 7M Model that Surpass DeepSeek-R1, Gemini 2.5 pro, and o3-mini at Reasoning on both ARG-AGI 1 and ARC-AGI 2 appeared first on MarkTechPost.
RA3: Mid-Training with Temporal Action Abstractions for Faster Reinforcement Learning (RL) Post-Training in Code LLMs
TL;DR: A new research from Apple, formalizes what “mid-training” should do before reinforcement learning RL post-training and introduces RA3 (Reasoning as Action Abstractions)—an EM-style procedure that learns temporally consistent latent actions from expert traces, then fine-tunes on those bootstrapped traces.It shows mid-training should (1) prune to a compact near-optimal action subspace and (2) shorten […]The post RA3: Mid-Training with Temporal Action Abstractions for Faster Reinforcement Learning (RL) Post-Training in Code LLMs appeared first on MarkTechPost.
Stanford Researchers Released AgentFlow: In-the-Flow Reinforcement Learning RL for Modular, Tool-Using AI Agents
TL;DR: AgentFlow is a trainable agent framework with four modules—Planner, Executor, Verifier, Generator—coordinated by an explicit memory and toolset.The planner is optimized in the loop with a new on-policy method, Flow-GRPO, which broadcasts a trajectory-level outcome reward to every turn and applies token-level PPO-style updates with KL regularization and group-normalized advantages.On ten benchmarks, […]
Anthropic AI Releases Petri: An Open-Source Framework for Automated Auditing by Using AI Agents to Test the Behaviors of Target Models on Diverse Scenarios
How do you audit frontier LLMs for misaligned behavior in realistic multi-turn, tool-use settings—at scale and beyond coarse aggregate scores?Anthropic released Petri (Parallel Exploration Tool for Risky Interactions), an open-source framework that automates alignment audits by orchestrating an auditor agent to probe a target model across multi-turn, tool-augmented interactions and a judge model to […]The post Anthropic AI Releases Petri: An Open-Source Framework for Automated Auditing by Using AI Agents to Test the Behaviors of Target Models on Diverse Scenarios appeared first on MarkTechPost.
Model Context Protocol (MCP) vs Function Calling vs OpenAPI Tools — When to Use Each?
Comparison Table Concern MCP Function Calling OpenAPI Tools Interface contract Protocol data model (tools/resources/prompts) Per-function JSON Schema OAS 3.1 document Discovery Dynamic via tools/list Static list provided to the model From OAS; catalogable Invocation tools/call over JSON-RPC session Model selects function; app executes HTTP request per OAS op Orchestration Host routes across many servers/tools App-local […]The post Model Context Protocol (MCP) vs Function Calling vs OpenAPI Tools — When to Use Each? appeared first on MarkTechPost.
Google AI Introduces Gemini 2.5 ‘Computer Use’ (Preview): A Browser-Control Model to Power AI Agents to Interact with User Interfaces
Google AI introduces Gemini 2.5 Computer Use, a specialized variant of Gemini 2.5 that plans and executes real UI actions in a live browser via a constrained action API.It’s available in public preview through Google […]The post Google AI Introduces Gemini 2.5 ‘Computer Use’ (Preview): A Browser-Control Model to Power AI Agents to Interact with User Interfaces appeared first on MarkTechPost.
Meta AI Open-Sources OpenZL: A Format-Aware Compression Framework with a Universal Decoder
How much compression ratio and throughput would you recover by training a format-aware graph compressor and shipping only a self-describing graph to a universal decoder?Meta AI released OpenZL, an open-source framework that builds specialized, format-aware compressors from high-level data descriptions and emits a self-describing wire format that a universal decoder can read—decoupling compressor evolution […]The post Meta AI Open-Sources OpenZL: A Format-Aware Compression Framework with a Universal Decoder appeared first on MarkTechPost.
An Intelligent Conversational Machine Learning Pipeline Integrating LangChain Agents and XGBoost for Automated Data Science Workflows
In this tutorial, we combine the analytical power of XGBoost with the conversational intelligence of LangChain.We build an end-to-end pipeline that can generate synthetic datasets, train an XGBoost model, evaluate its performance, and visualize key insights, all orchestrated through modular LangChain tools.By doing this, we demonstrate how conversational AI can interact seamlessly with […]
Google DeepMind Introduces CodeMender: A New AI Agent that Uses Gemini Deep Think to Automatically Patch Critical Software Vulnerabilities
What if an AI agent could localize a root cause, prove a candidate fix via automated analysis and testing, and proactively rewrite related code to eliminate the entire vulnerability class—then open an upstream patch for review?Google DeepMind introduces CodeMender, an AI agent that generates, validates, and upstreams fixes for real-world vulnerabilities using Gemini “Deep […]The post Google DeepMind Introduces CodeMender: A New AI Agent that Uses Gemini Deep Think to Automatically Patch Critical Software Vulnerabilities appeared first on MarkTechPost.
Building a Human Handoff Interface for AI-Powered Insurance Agent Using Parlant and Streamlit
In this tutorial, we’ll implement a human handoff system for an AI-powered insurance agent using Parlant.You’ll learn how to create a Streamlit-based interface that allows a human operator (Tier 2) […]The post Building a Human Handoff Interface for AI-Powered Insurance Agent Using Parlant and Streamlit appeared first on MarkTechPost.
OpenAI Debuts Agent Builder and AgentKit: A Visual-First Stack for Building, Deploying, and Evaluating AI Agents
OpenAI has released AgentKit, a cohesive platform that packages a visual Agent Builder, an embeddable ChatKit UI, and expanded Evals into a single workflow for shipping production agents.The launch includes Agent Builder in beta and the rest generally available.A visual canvas for composing multi-step, multi-agent workflows with drag-and-drop […]
A New Agency-Focused Supervision Approach Scales Software AI Agents With Only 78 Examples
Do curated, tool-grounded demonstrations build stronger software agents than broad piles of generic instruction data? A team of researchers from Shanghai Jiao Tong University and SII Generative AI Research Lab (GAIR) proposes LIMI (“Less Is More for Agency”), a supervised fine-tuning method that turns a base model into a capable software/research agent using 78 samples. […] The post
StreamTensor: A PyTorch-to-Accelerator Compiler that Streams LLM Intermediates Across FPGA Dataflows
Why treat LLM inference as batched kernels to DRAM when a dataflow compiler can pipe tiles through on-chip FIFOs and stream converters?StreamTensor is a compiler that lowers PyTorch LLM graphs (GPT-2, Llama, Qwen, Gemma) into stream-scheduled dataflow accelerators on AMD’s Alveo U55C FPGA. The system introduces an iterative tensor (“itensor”) type to encode tile/order of […] The post
Salesforce AI Research Releases CoDA-1.7B: a Discrete-Diffusion Code Model with Bidirectional, Parallel Token Generation
Salesforce AI Research released CoDA-1.7B, a diffusion-based language model for code that generates by denoising whole sequences with bidirectional context, updating multiple tokens in parallel rather than left-to-right next-token prediction. The research team published both Base and Instruct checkpoints and an end-to-end training/evaluation/serving stack. Understanding the architecture and training CoDA adapts a 1.7B-parameter backbone to […] The post
Agentic Design Methodology: How to Build Reliable and Human-Like AI Agents using Parlant
Building robust AI agents differs fundamentally from traditional software development, as it centers on probabilistic model behavior rather than deterministic code execution. This guide provides a neutral overview of methodologies for designing AI agents that are both reliable and adaptable, with an emphasis on creating clear boundaries, effective behaviors, and safe interactions. What Is Agentic […] The post
How to Evaluate Voice Agents in 2025: Beyond Automatic Speech Recognition (ASR) and Word Error Rate (WER) to Task Success, Barge-In, and Hallucination-Under-Noise
Optimizing only for Automatic Speech Recognition (ASR) and Word Error Rate (WER) is insufficient for modern, interactive voice agents. Robust evaluation must measure end-to-end task success, barge-in behavior and latency, and hallucination-under-noise—alongside ASR, safety, and instruction following. VoiceBench offers a multi-facet speech-interaction benchmark across general knowledge, instruction following, safety, and robustness to speaker/environment/content variations, but […] <...
This AI Paper Proposes a Novel Dual-Branch Encoder-Decoder Architecture for Unsupervised Speech Enhancement (SE)
Can a speech enhancer trained only on real noisy recordings cleanly separate speech and noise—without ever seeing paired data? A team of researchers from Brno University of Technology and Johns Hopkins University proposes Unsupervised Speech Enhancement using Data-defined Priors (USE-DDP), a dual-stream encoder–decoder that separates any noisy input into two waveforms—estimated clean speech and residual […] The post
A Coding Implementation to Build a Transformer-Based Regression Language Model to Predict Continuous Values from Text
We will build a Regression Language Model (RLM), a model that predicts continuous numerical values directly from text sequences in this coding implementation. Instead of classifying or generating text, we focus on training a transformer-based architecture that learns quantitative relationships hidden within natural language descriptions. We start by generating synthetic text-to-number data, tokenizing it efficiently, […] The post
Google Proposes TUMIX: Multi-Agent Test-Time Scaling With Tool-Use Mixture
What if, instead of re-sampling one agent, you could push Gemini-2.5 Pro to 34.1% on HLE by mixing 12–15 tool-using agents that share notes and stop early? Google Cloud AI Research, with collaborators from MIT, Harvard, and Google DeepMind, introduced TUMIX (Tool-Use Mixture)—a test-time framework that ensembles heterogeneous agent styles (text-only, code, search, guided variants) […] The post
Can a Small Language Model Predict Kernel Latency, Memory, and Model Accuracy from Code? A New Regression Language Model (RLM) Says Yes
Researchers from Cornell and Google introduce a unified Regression Language Model (RLM) that predicts numeric outcomes directly from code strings—covering GPU kernel latency, program memory usage, and even neural network accuracy and latency—without hand-engineered features. A 300M-parameter encoder–decoder initialized from T5-Gemma achieves strong rank correlations across heterogeneous tasks and languages, using a single text-to-number decoder […] The post
A Coding Guide to Build an Autonomous Agentic AI for Time Series Forecasting with Darts and Hugging Face
In this tutorial, we build an advanced agentic AI system that autonomously handles time series forecasting using the Darts library combined with a lightweight HuggingFace model for reasoning. We design the agent to operate in a perception–reasoning–action cycle, where it first analyzes patterns in the data, then selects an appropriate forecasting model, generates predictions, and […] The post
AWS Open-Sources an MCP Server for Bedrock AgentCore to Streamline AI Agent Development
AWS released an open-source Model Context Protocol (MCP) server for Amazon Bedrock AgentCore, providing a direct path from natural-language prompts in agentic IDEs to deployable agents on AgentCore Runtime. The package ships with automated transformations, environment provisioning, and Gateway/tooling hooks designed to compress typical multi-step integration work into conversational commands. So, what exactly is it? […] The post
Microsoft Releases ‘Microsoft Agent Framework’: An Open-Source SDK and Runtime that Simplifies the Orchestration of Multi-Agent Systems
Microsoft released the Microsoft Agent Framework (public preview), an open-source SDK and runtime that unifies core ideas from AutoGen (agent runtime and multi-agent patterns) with Semantic Kernel (enterprise controls, state, plugins) to help teams build, deploy, and observe production-grade AI agents and multi-agent workflows. The framework is available for Python and .NET and integrates directly […] The post
Neuphonic Open-Sources NeuTTS Air: A 748M-Parameter On-Device Speech Language Model with Instant Voice Cloning
Neuphonic has released NeuTTS Air, an open-source text-to-speech (TTS) speech language model designed to run locally in real time on CPUs.The Hugging Face model card lists 748M parameters (Qwen2 architecture) and ships in GGUF quantizations (Q4/Q8), enabling inference through llama.cpp/llama-cpp-python without cloud dependencies.It is licensed under Apache-2.0 and includes a runnable demo and […]
Thinking Machines Launches Tinker: A Low-Level Training API that Abstracts Distributed LLM Fine-Tuning without Hiding the Knobs
Thinking Machines has released Tinker, a Python API that lets researchers and engineers write training loops locally while the platform executes them on managed distributed GPU clusters.The pitch is narrow and technical: keep full control of data, objectives, and optimization steps;hand off scheduling, fault tolerance, and multi-node orchestration.
How to Build an Advanced Voice AI Pipeline with WhisperX for Transcription, Alignment, Analysis, and Export?
In this tutorial, we walk through an advanced implementation of WhisperX, where we explore transcription, alignment, and word-level timestamps in detail. We set up the environment, load and preprocess the audio, and then run the full pipeline, from transcription to alignment and analysis, while ensuring memory efficiency and supporting batch processing. Along the way, we […] The post
IBM Released new Granite 4.0 Models with a Novel Hybrid Mamba-2/Transformer Architecture: Drastically Reducing Memory Use without Sacrificing Performance
IBM just released Granite 4.0, an open-source LLM family that swaps monolithic Transformers for a hybrid Mamba-2/Transformer stack to cut serving memory while keeping quality. Sizes span a 3B dense “Micro,” a 3B hybrid “H-Micro,” a 7B hybrid MoE “H-Tiny” (~1B active), and a 32B hybrid MoE “H-Small” (~9B active). The models are Apache-2.0, cryptographically […] The post
ServiceNow AI Releases Apriel-1.5-15B-Thinker: An Open-Weights Multimodal Reasoning Model that Hits Frontier-Level Performance on a Single-GPU Budget
ServiceNow AI Research Lab has released Apriel-1.5-15B-Thinker, a 15-billion-parameter open-weights multimodal reasoning model trained with a data-centric mid-training recipe—continual pretraining followed by supervised fine-tuning—without reinforcement learning or preference optimization. The model attains an Artificial Analysis Intelligence Index score of 52 with 8x cost savings compared to SOTA. The checkpoint ships under an MIT license on […] The post
Liquid AI Released LFM2-Audio-1.5B: An End-to-End Audio Foundation Model with Sub-100 ms Response Latency
Liquid AI has released LFM2-Audio-1.5B, a compact audio–language foundation model that both understands and generates speech and text through a single end-to-end stack. It positions itself for low-latency, real-time assistants on resource-constrained devices, extending the LFM2 family into audio while retaining a small footprint. But what’s actually new? a unified backbone with disentangled audio I/O […] The post
MLPerf Inference v5.1 (2025): Results Explained for GPUs, CPUs, and AI Accelerators
What MLPerf Inference Actually Measures? MLPerf Inference quantifies how fast a complete system (hardware + runtime + serving stack) executes fixed, pre-trained models under strict latency and accuracy constraints. Results are reported for the Datacenter and Edge suites with standardized request patterns (“scenarios”) generated by LoadGen, ensuring architectural neutrality and reproducibility. The Closed division fixes […] The post
The Role of Model Context Protocol (MCP) in Generative AI Security and Red Teaming
Overview Model Context Protocol (MCP) is an open, JSON-RPC–based standard that formalizes how AI clients (assistants, IDEs, web apps) connect to servers exposing three primitives—tools, resources, and prompts—over defined transports (primarily stdio for local and Streamable HTTP for remote). MCP’s value for security work is that it renders agent/tool interactions explicit and auditable, with normative […] The post
Google AI Proposes ReasoningBank: A Strategy-Level I Agent Memory Framework that Makes LLM Agents Self-Evolve at Test Time
How do you make an LLM agent actually learn from its own runs—successes and failures—without retraining? Google Research proposes ReasoningBank, an AI agent memory framework that converts an agent’s own interaction traces—both successes and failures—into reusable, high-level reasoning strategies. These strategies are retrieved to guide future decisions, and the loop repeats so the agent self-evolves. […] The post
How to Build an Advanced Agentic Retrieval-Augmented Generation (RAG) System with Dynamic Strategy and Smart Retrieval?
In this tutorial, we walk through the implementation of an Agentic Retrieval-Augmented Generation (RAG) system. We design it so that the agent does more than just retrieve documents; it actively decides when retrieval is needed, selects the best retrieval strategy, and synthesizes responses with contextual awareness. By combining embeddings, FAISS indexing, and a mock LLM, […] The post
Zhipu AI Releases GLM-4.6: Achieving Enhancements in Real-World Coding, Long-Context Processing, Reasoning, Searching and Agentic AI
Zhipu AI has released GLM-4.6, a major update to its GLM series focused on agentic workflows, long-context reasoning, and practical coding tasks. The model raises the input window to 200K tokens with a 128K max output, targets lower token consumption in applied tasks, and ships with open weights for local deployment. So, what’s exactly is […] The post
OpenAI Launches Sora 2 and a Consent-Gated Sora iOS App
OpenAI released Sora 2, a text-to-video-and-audio model focused on physical plausibility, multi-shot controllability, and synchronized dialogue/SFX. The OpenAI team has also launched a new invite-only Sora iOS app (U.S. and Canada first) that enables social creation, remixing, and consent-controlled “cameos” for inserting a verified likeness into generated scenes. Model capabilities Sora 2 claims materially better […] The post
Delinea Released an MCP Server to Put Guardrails Around AI Agents Credential Access
Delinea released an Model Context Protocol (MCP) server that let AI-agent access to credentials stored in Delinea Secret Server and the Delinea Platform. The server applies identity checks and policy rules on every call, aiming to keep long-lived secrets out of agent memory while retaining full auditability What’s new for me? The GitHub project DelineaXPM/delinea-mcp […] The post
DeepSeek V3.2-Exp Cuts Long-Context Costs with DeepSeek Sparse Attention (DSA) While Maintaining Benchmark Parity
DeepSeek released DeepSeek-V3.2-Exp, an “intermediate” update to V3.1 that adds DeepSeek Sparse Attention (DSA)—a trainable sparsification path aimed at long-context efficiency. DeepSeek also reduced API prices by 50%+, consistent with the stated efficiency gains. DeepSeek-V3.2-Exp keeps the V3/V3.1 stack (MoE + MLA) and inserts a two-stage attention path: (i) a lightweight “indexer” that scores context […] The post
A Coding Guide to Build a Hierarchical Supervisor Agent Framework with CrewAI and Google Gemini for Coordinated Multi-Agent Workflows
In this tutorial, we walk you through the design and implementation of an advanced Supervisor Agent Framework using CrewAI with Google Gemini model. We set up specialized agents, including researchers, analysts, writers, and reviewers, and bring them under a supervisor agent who coordinates and monitors their work. By combining structured task configurations, hierarchical workflows, and […] The post
Anthropic Launches Claude Sonnet 4.5 with New Coding and Agentic State-of-the-Art Results
Anthropic released Claude Sonnet 4.5 and sets a new benchmark for end-to-end software engineering and real-world computer use. The update also ships concrete product surface changes (Claude Code checkpoints, a native VS Code extension, API memory/context tools) and an Agent SDK that exposes the same scaffolding Anthropic uses internally. Pricing remains unchanged from Sonnet 4 […] The post
Meet oLLM: A Lightweight Python Library that brings 100K-Context LLM Inference to 8 GB Consumer GPUs via SSD Offload—No Quantization Required
oLLM is a lightweight Python library built on top of Huggingface Transformers and PyTorch and runs large-context Transformers on NVIDIA GPUs by aggressively offloading weights and KV-cache to fast local SSDs. The project targets offline, single-GPU workloads and explicitly avoids quantization, using FP16/BF16 weights with FlashAttention-2 and disk-backed KV caching to keep VRAM within 8–10 […] The post
How to Design an Interactive Dash and Plotly Dashboard with Callback Mechanisms for Local and Online Deployment?
In this tutorial, we set out to build an advanced interactive dashboard using Dash, Plotly, and Bootstrap. We highlight not only how these tools enable us to design layouts and visualizations, but also how Dash’s callback mechanism links controls to outputs, allowing for real-time responsiveness. By combining local execution with the ability to run in […] The post
Ensuring AI Safety in Production: A Developer’s Guide to OpenAI’s Moderation and Safety Checks
When deploying AI into the real world, safety isn’t optional—it’s essential. OpenAI places strong emphasis on ensuring that applications built on its models are secure, responsible, and aligned with policy. This article explains how OpenAI evaluates safety and what you can do to meet those standards. Beyond technical performance, responsible AI deployment requires anticipating potential […] The post
This AI Research Proposes an AI Agent Immune System for Adaptive Cybersecurity: 3.4× Faster Containment with <10% Overhead
Can your AI security stack profile, reason, and neutralize a live security threat in ~220 ms—without a central round-trip? A team of researchers from Google and University of Arkansas at Little Rock outline an agentic cybersecurity “immune system” built from lightweight, autonomous sidecar AI agents colocated with workloads (Kubernetes pods, API gateways, edge services). Instead […] The post
Gemini Robotics 1.5: DeepMind’s ER↔VLA Stack Brings Agentic Robots to the Real World
Can a single AI stack plan like a researcher, reason over scenes, and transfer motions across different robots—without retraining from scratch? Google DeepMind’s Gemini Robotics 1.5 says yes, by splitting embodied intelligence into two models: Gemini Robotics-ER 1.5 for high-level embodied reasoning (spatial understanding, planning, progress/success estimation, tool-use) and Gemini Robotics 1.5 for low-level visuomotor […] The post
Top 10 Local LLMs (2025): Context Windows, VRAM Targets, and Licenses Compared
Local LLMs matured fast in 2025: open-weight families like Llama 3.1 (128K context length (ctx)), Qwen3 (Apache-2.0, dense + MoE), Gemma 2 (9B/27B, 8K ctx), Mixtral 8×7B (Apache-2.0 SMoE), and Phi-4-mini (3.8B, 128K ctx) now ship reliable specs and first-class local runners (GGUF/llama.cpp, LM Studio, Ollama), making on-prem and even laptop inference practical if you […] The post
The Latest Gemini 2.5 Flash-Lite Preview is Now the Fastest Proprietary Model (External Tests) and 50% Fewer Output Tokens
Google released an updated version of Gemini 2.5 Flash and Gemini 2.5 Flash-Lite preview models across AI Studio and Vertex AI, plus rolling aliases—gemini-flash-latest and gemini-flash-lite-latest—that always point to the newest preview in each family. For production stability, Google advises pinning fixed strings (gemini-2.5-flash, gemini-2.5-flash-lite). Google will give a two-week email notice before retargeting a […] The post
What is Asyncio? Getting Started with Asynchronous Python and Using Asyncio in an AI Application with an LLM
In many AI applications today, performance is a big deal. You may have noticed that while working with Large Language Models (LLMs), a lot of time is spent waiting—waiting for an API response, waiting for multiple calls to finish, or waiting for I/O operations. That’s where asyncio comes in. Surprisingly, many developers use LLMs without […] The post
How to Build an Intelligent AI Desktop Automation Agent with Natural Language Commands and Interactive Simulation?
In this tutorial, we walk through the process of building an advanced AI desktop automation agent that runs seamlessly in Google Colab. We design it to interpret natural language commands, simulate desktop tasks such as file operations, browser actions, and workflows, and provide interactive feedback through a virtual environment. By combining NLP, task execution, and […] The post
Meet Qwen3Guard: The Qwen3-based Multilingual Safety Guardrail Models Built for Global, Real-Time AI Safety
Can safety keep up with real-time LLMs? Alibaba’s Qwen team thinks so, and it just shipped Qwen3Guard—a multilingual guardrail model family built to moderate prompts and streaming responses in-real-time. Qwen3Guard comes in two variants: Qwen3Guard-Gen (a generative classifier that reads full prompt/response context) and Qwen3Guard-Stream (a token-level classifier that moderates as text is generated). Both […] The post
Hugging Face Releases Smol2Operator: A Fully Open-Source Pipeline to Train a 2.2B VLM into an Agentic GUI Coder
Hugging Face (HF) has released Smol2Operator, a reproducible, end-to-end recipe that turns a small vision-language model (VLM) with no prior UI grounding into a GUI-operating, tool-using agent. The release covers data transformation utilities, training scripts, transformed datasets, and the resulting 2.2B-parameter model checkpoint—positioned as a complete blueprint for building GUI agents from scratch rather than […] The post
Sakana AI Released ShinkaEvolve: An Open-Source Framework that Evolves Programs for Scientific Discovery with Unprecedented Sample-Efficiency
Sakana AI has released ShinkaEvolve, an open-sourced framework that uses large language models (LLMs) as mutation operators in an evolutionary loop to evolve programs for scientific and engineering problems—while drastically cutting the number of evaluations needed to reach strong solutions. On the canonical circle-packing benchmark (n=26 in a unit square), ShinkaEvolve reports a new SOTA […] The post
Google AI Ships a Model Context Protocol (MCP) Server for Data Commons, Giving AI Agents First-Class Access to Public Stats
Google released a Model Context Protocol (MCP) server for Data Commons, exposing the project’s interconnected public datasets—census, health, climate, economics—through a standards-based interface that agentic systems can query in natural language. The Data Commons MCP Server is available now with quickstarts for Gemini CLI and Google’s Agent Development Kit (ADK). What was released Why MCP […] The post
OpenAI Releases ChatGPT ‘Pulse’: Proactive, Personalized Daily Briefings for Pro Users
OpenAI introduced ChatGPT Pulse, a proactive experience that compiles personalized, research-backed updates each morning. In preview on mobile and limited to $200/month Pro subscribers, Pulse surfaces topical cards built from a user’s chats, explicit feedback, and opt-in connected apps (e.g., calendar/email), shifting ChatGPT from a request-driven tool to a context-aware assistant. What Pulse Actually Does […] The post
OpenAI Introduces GDPval: A New Evaluation Suite that Measures AI on Real-World Economically Valuable Tasks
OpenAI introduced GDPval, a new evaluation suite designed to measure how AI models perform on real-world, economically valuable tasks across 44 occupations in nine GDP-dominant U.S. sectors. Unlike academic benchmarks, GDPval centers on authentic deliverables—presentations, spreadsheets, briefs, CAD artifacts, audio/video—graded by occupational experts through blinded pairwise comparisons. OpenAI also released a 220-task “gold” subset and […] The post
Meta FAIR Released Code World Model (CWM): A 32-Billion-Parameter Open-Weights LLM, to Advance Research on Code Generation with World Models
Meta FAIR released Code World Model (CWM), a 32-billion-parameter dense decoder-only LLM that injects world modeling into code generation by training on execution traces and long-horizon agent–environment interactions—not just static source text. What’s new: learning code by predicting execution? CWM mid-trains on two large families of observation–action trajectories: (1) Python interpreter traces that record local […] The post
How to Build an End-to-End Data Science Workflow with Machine Learning, Interpretability, and Gemini AI Assistance?
In this tutorial, we walk through an advanced end-to-end data science workflow where we combine traditional machine learning with the power of Gemini. We begin by preparing and modeling the diabetes dataset, then we dive into evaluation, feature importance, and partial dependence. Along the way, we bring in Gemini as our AI data scientist to […] The post
Vision-RAG vs Text-RAG: A Technical Comparison for Enterprise Search
Most RAG failures originate at retrieval, not generation. Text-first pipelines lose layout semantics, table structure, and figure grounding during PDF→text conversion, degrading recall and precision before an LLM ever runs. Vision-RAG—retrieving rendered pages with vision-language embeddings—directly targets this bottleneck and shows material end-to-end gains on visually rich corpora. Pipelines (and where they fail) Text-RAG. PDF […] The post
How to Master Advanced TorchVision v2 Transforms, MixUp, CutMix, and Modern CNN Training for State-of-the-Art Computer Vision?
In this tutorial, we explore advanced computer vision techniques using TorchVision’s v2 transforms, modern augmentation strategies, and powerful training enhancements. We walk through the process of building an augmentation pipeline, applying MixUp and CutMix, designing a modern CNN with attention, and implementing a robust training loop. By running everything seamlessly in Google Colab, we position […] The post
Alibaba’s Qwen3-Max: Production-Ready Thinking Mode, 1T+ Parameters, and Day-One Coding/Agentic Bench Signals
Alibaba has released Qwen3-Max, a trillion-parameter Mixture-of-Experts (MoE) model positioned as its most capable foundation model to date, with an immediate public on-ramp via Qwen Chat and Alibaba Cloud’s Model Studio API. The launch moves Qwen’s 2025 cadence from preview to production and centers on two variants: Qwen3-Max-Instruct for standard reasoning/coding tasks and Qwen3-Max-Thinking for […] The post
CloudFlare AI Team Just Open-Sourced ‘VibeSDK’ that Lets Anyone Build and Deploy a Full AI Vibe Coding Platform with a Single Click
CloudFlare AI team just open-sourced VibeSDK, a full-stack “vibe coding” platform that you can deploy end-to-end with a single click on Cloudflare’s network or GitHub Repo Fork. It packages code generation, safe execution, live preview, and multi-tenant deployment so teams can run their own internal or customer-facing AI app builder without stitching together infrastructure. What’s […] The post
Google AI Research Introduce a Novel Machine Learning Approach that Transforms TimesFM into a Few-Shot Learner
Google Research introduces in-context fine-tuning (ICF) for time-series forecasting named as ‘TimesFM-ICF): a continued-pretraining recipe that teaches TimesFM to exploit multiple related series provided directly in the prompt at inference time. The result is a few-shot forecaster that matches supervised fine-tuning while delivering +6.8% accuracy over the base TimesFM across an OOD benchmark—no per-dataset training […] The post
Coding Implementation to End-to-End Transformer Model Optimization with Hugging Face Optimum, ONNX Runtime, and Quantization
In this tutorial, we walk through how we use Hugging Face Optimum to optimize Transformer models and make them faster while maintaining accuracy. We begin by setting up DistilBERT on the SST-2 dataset, and then we compare different execution engines, including plain PyTorch and torch.compile, ONNX Runtime, and quantized ONNX. By doing this step by […] The post
Google AI Introduces the Public Preview of Chrome DevTools MCP: Making Your Coding Agent Control and Inspect a Live Chrome Browser
Google has released a public preview of “Chrome DevTools MCP,” a Model Context Protocol (MCP) server that lets AI coding agents control and inspect a real Chrome instance—recording performance traces, inspecting the DOM and CSS, executing JavaScript, reading console output, and automating user flows. The launch directly targets a well-known limitation in code-generating agents: they […] The post
Meet VoXtream: An Open-Sourced Full-Stream Zero-Shot TTS Model for Real-Time Use that Begins Speaking from the First Word
Real-time agents, live dubbing, and simultaneous translation die by a thousand milliseconds. Most “streaming” TTS (Text to Speech) stacks still wait for a chunk of text before they emit sound, so the human hears a beat of silence before the voice starts. VoXtream—released by KTH’s Speech, Music and Hearing group—attacks this head-on: it begins speaking […] The post
How to Create Reliable Conversational AI Agents Using Parlant?
Parlant is a framework designed to help developers build production-ready AI agents that behave consistently and reliably. A common challenge when deploying large language model (LLM) agents is that they often perform well in testing but fail when interacting with real users. They may ignore carefully designed system prompts, generate inaccurate or irrelevant responses at […] The post
Microsoft Brings MCP to Azure Logic Apps (Standard) in Public Preview, Turning Connectors into Agent Tools
Microsoft has released a public preview that enables Azure Logic Apps (Standard) to run as Model Context Protocol (MCP) servers, exposing Logic Apps workflows as agent tools discoverable and callable by MCP-capable clients (e.g., VS Code + Copilot). What’s actually shipping Key requirements and transport details API Center path: preview limitations that matter When creating […] The post
Perplexity Launches an AI Email Assistant Agent for Gmail and Outlook, Aimed at Scheduling, Drafting, and Inbox Triage
Perplexity introduced “Email Assistant,” an AI agent that plugs into Gmail and Outlook to draft replies in your voice, auto-label and prioritize messages, and coordinate meetings end-to-end (availability checks, time suggestions, and calendar invites). The feature is restricted to Perplexity’s Max plan and is live today. What it does? Email Assistant adds an agent to […] The post
Alibaba Qwen Team Just Released FP8 Builds of Qwen3-Next-80B-A3B (Instruct & Thinking), Bringing 80B/3B-Active Hybrid-MoE to Commodity GPUs
Alibaba’s Qwen team has just released FP8-quantized checkpoints for its new Qwen3-Next-80B-A3B models in two post-training variants—Instruct and Thinking—aimed at high-throughput inference with ultra-long context and MoE efficiency. The FP8 repos mirror the BF16 releases but package “fine-grained FP8” weights (block size 128) and deployment notes for sglang and vLLM nightly builds. Benchmarks in the […] The post
Top 15 Model Context Protocol (MCP) Servers for Frontend Developers (2025)
Model Context Protocol (MCP) has become the “USB-C” for agent/tool integrations, giving frontend teams a standard way to wire design specs, repos/PRs, deploy targets, observability, and work management into their editors and CI without bespoke adapters. This list focuses on production-ready, remote MCP servers (OAuth/permissioned) that map cleanly onto Frontend (FE) workflows—e.g., Figma→GitHub→Vercel/Cloudflare→Chromatic/Sentry—reflecting rapid ecosystem […] The post
MIT Researchers Enhanced Artificial Intelligence (AI) 64x Better at Planning, Achieving 94% Accuracy
Can a 8B-parameter language model produce provably valid multi-step plans instead of plausible guesses? MIT CSAIL researchers introduce PDDL-INSTRUCT, an instruction-tuning framework that couples logical chain-of-thought with external plan validation (VAL) to lift symbolic planning performance of LLMs. On PlanBench, a tuned Llama-3-8B reaches 94% valid plans on Blocksworld, with large jumps on Mystery Blocksworld […] The post
Understanding the Universal Tool Calling Protocol (UTCP)
The Universal Tool Calling Protocol (UTCP) is a lightweight, secure, and scalable way for AI agents and applications to find and call tools directly, without the need for additional wrapper servers. Key Features The Problem with Current Approaches Traditional solutions for integrating tools often require: These steps add friction for developers and slow down execution. […] The post
Meta AI Proposes ‘Metacognitive Reuse’: Turning LLM Chains-of-Thought into a Procedural Handbook that Cuts Tokens by 46%
Meta researchers introduced a method that compresses repeated reasoning patterns into short, named procedures—“behaviors”—and then conditions models to use them at inference or distills them via fine-tuning. The result: up to 46% fewer reasoning tokens on MATH while matching or improving accuracy, and up to 10% accuracy gains in a self-improvement setting on AIME, without […] The post
IBM and ETH Zürich Researchers Unveil Analog Foundation Models to Tackle Noise in In-Memory AI Hardware
IBM researchers, together with ETH Zürich, have unveiled a new class of Analog Foundation Models (AFMs) designed to bridge the gap between large language models (LLMs) and Analog In-Memory Computing (AIMC) hardware. AIMC has long promised a radical leap in efficiency—running models with a billion parameters in a footprint small enough for embedded or edge […] The post
Building a Hybrid Rule-Based and Machine Learning Framework to Detect and Defend Against Jailbreak Prompts in LLM Systems
In this tutorial, we introduce a Jailbreak Defense that we built step-by-step to detect and safely handle policy-evasion prompts. We generate realistic attack and benign examples, craft rule-based signals, and combine those with TF-IDF features into a compact, interpretable classifier so we can catch evasive prompts without blocking legitimate requests. We demonstrate evaluation metrics, explain […] The post
LLM-as-a-Judge: Where Do Its Signals Break, When Do They Hold, and What Should “Evaluation” Mean?
What exactly is being measured when a judge LLM assigns a 1–5 (or pairwise) score? Most “correctness/faithfulness/completeness” rubrics are project-specific. Without task-grounded definitions, a scalar score can drift from business outcomes (e.g., “useful marketing post” vs. “high completeness”). Surveys of LLM-as-a-judge (LAJ) note that rubric ambiguity and prompt template choices materially shift scores and human […] The post
An Internet of AI Agents? Coral Protocol Introduces Coral v1: An MCP-Native Runtime and Registry for Cross-Framework AI Agents
Coral Protocol has released Coral v1 of its agent stack, aiming to standardize how developers discover, compose, and operate AI agents across heterogeneous frameworks. The release centers on an MCP-based runtime (Coral Server) that enables threaded, mention-addressed agent-to-agent messaging, a developer workflow (CLI + Studio) for orchestration and observability, and a public registry for agent […] The post
A Coding Guide to End-to-End Robotics Learning with LeRobot: Training, Evaluating, and Visualizing Behavior Cloning Policies on PushT
In this tutorial, we walk step by step through using Hugging Face’s LeRobot library to train and evaluate a behavior-cloning policy on the PushT dataset. We begin by setting up the environment in Google Colab, installing the required dependencies, and loading the dataset through LeRobot’s unified API. We then design a compact visuomotor policy that […] The post
xAI launches Grok-4-Fast: Unified Reasoning and Non-Reasoning Model with 2M-Token Context and Trained End-to-End with Tool-Use Reinforcement Learning (RL)
xAI introduced Grok-4-Fast, a cost-optimized successor to Grok-4 that merges “reasoning” and “non-reasoning” behaviors into a single set of weights controllable via system prompts. The model targets high-throughput search, coding, and Q&A with a 2M-token context window and native tool-use RL that decides when to browse the web, execute code, or call tools. Architecture note […] The post
Xiaomi Released MiMo-Audio, a 7B Speech Language Model Trained on 100M+ Hours with High-Fidelity Discrete Tokens
Xiaomi’s MiMo team released MiMo-Audio, a 7-billion-parameter audio-language model that runs a single next-token objective over interleaved text and discretized speech, scaling pretraining beyond 100 million hours of audio. What’s actually new? Instead of relying on task-specific heads or lossy acoustic tokens, MiMo-Audio uses a bespoke RVQ (residual vector quantization) tokenizer that targets both semantic […] The post
Run MATLAB-Style Code Inside Python by Connecting Octave with the oct2py Library
In this tutorial, we explore how we can seamlessly run MATLAB-style code inside Python by connecting Octave with the oct2py library. We set up the environment on Google Colab, exchange data between NumPy and Octave, write and call .m files, visualize plots generated in Octave within Python, and even work with toolboxes, structs, and .mat […] The post
Google’s Sensible Agent Reframes Augmented Reality (AR) Assistance as a Coupled “what+how” Decision—So What does that Change?
Sensible Agent is an AI research framework and prototype from Google that chooses both the action an augmented reality (AR) agent should take and the interaction modality to deliver/confirm it, conditioned on real-time multimodal context (e.g., whether hands are busy, ambient noise, social setting). Rather than treating “what to suggest” and “how to ask” as […] The post
Top Computer Vision CV Blogs & News Websites (2025)
Computer vision moved fast in 2025: new multimodal backbones, larger open datasets, and tighter model–systems integration. Practitioners need sources that publish rigorously, link code and benchmarks, and track deployment patterns—not marketing posts. This list prioritizes primary research hubs, lab blogs, and production-oriented engineering outlets with consistent update cadence. Use it to monitor SOTA shifts, grab […] The post
Qwen3-ASR-Toolkit: An Advanced Open Source Python Command-Line Toolkit for Using the Qwen-ASR API Beyond the 3 Minutes/10 MB Limit
Qwen has released Qwen3-ASR-Toolkit, an MIT-licensed Python CLI that programmatically bypasses the Qwen3-ASR-Flash API’s 3-minute/10 MB per-request limit by performing VAD-aware chunking, parallel API calls, and automatic resampling/format normalization via FFmpeg. The result is stable, hour-scale transcription pipelines with configurable concurrency, context injection, and clean text post-processing. Python ≥3.8 prerequisite, Install with: What the toolkit […] The post
Physical AI: Bridging Robotics, Material Science, and Artificial Intelligence for Next-Gen Embodied Systems
What Do We Mean by “Physical AI”? Artificial intelligence in robotics is not just a matter of clever algorithms. Robots operate in the physical world, and their intelligence emerges from the co-design of body and brain. Physical AI describes this integration, where materials, actuation, sensing, and computation shape how learning policies function. The term was […] The post
Building AI agents is 5% AI and 100% software engineering
Production-grade agents live or die on data plumbing, controls, and observability—not on model choice. The doc-to-chat pipeline below maps the concrete layers and why they matter. What is a “doc-to-chat” pipeline? A doc-to-chat pipeline ingests enterprise documents, standardizes them, enforces governance, indexes embeddings alongside relational features, and serves retrieval + generation behind authenticated APIs with […] The post
MIT’s LEGO: A Compiler for AI Chips that Auto-Generates Fast, Efficient Spatial Accelerators
MIT researchers (Han Lab) introduced LEGO, a compiler-like framework that takes tensor workloads (e.g., GEMM, Conv2D, attention, MTTKRP) and automatically generates synthesizable RTL for spatial accelerators—no handwritten templates. LEGO’s front end expresses workloads and dataflows in a relation-centric affine representation, builds FU (functional unit) interconnects and on-chip memory layouts for reuse, and supports fusing multiple […] The post
Bringing AI Agents Into Any UI: The AG-UI Protocol for Real-Time, Structured Agent–Frontend Streams
AI agents are no longer just chatbots that spit out answers.They’re evolving into complex systems that can reason step by step, call APIs, update dashboards, and collaborate with humans in real time.But this raises a key question: how should agents talk to user interfaces?
H Company Releases Holo1.5: An Open-Weight Computer-Use VLMs Focused on GUI Localization and UI-VQA
H Company (A french AI startup) releases Holo1.5, a family of open foundation vision models purpose-built for computer-use (CU) agents that act on real user interfaces via screenshots and pointer/keyboard actions.The release includes 3B, 7B, and 72B checkpoints with a documented ~10% accuracy gain over Holo1 across sizes.The 7B model is Apache-2.0;
Alibaba Releases Tongyi DeepResearch: A 30B-Parameter Open-Source Agentic LLM Optimized for Long-Horizon Research
Alibaba’s Tongyi Lab has open-sourced Tongyi-DeepResearch-30B-A3B, an agent-specialized large language model built for long-horizon, deep information-seeking with web tools.The model uses a mixture-of-experts (MoE) design with ~30.5B total parameters and ~3–3.3B active per token, enabling high throughput while preserving strong reasoning performance.It targets multi-turn research workflows—searching, browsing, extracting, cross-checking, and synthesizing evidence—under ReAct-style […]
IBM AI Releases Granite-Docling-258M: An Open-Source, Enterprise-Ready Document AI Model
IBM has released Granite-Docling-258M, an open-source (Apache-2.0) vision-language model designed specifically for end-to-end document conversion.The model targets layout-faithful extraction—tables, code, equations, lists, captions, and reading order—emitting a structured, machine-readable representation rather than lossy Markdown.It is available on Hugging Face with a live demo and MLX build for Apple Silicon.
Meta AI Researchers Release MapAnything: An End-to-End Transformer Architecture that Directly Regresses Factored, Metric 3D Scene Geometry
A team of researchers from Meta Reality Labs and Carnegie Mellon University has introduced MapAnything, an end-to-end transformer architecture that directly regresses factored metric 3D scene geometry from images and optional sensor inputs.Released under Apache 2.0 with full training and benchmarking code, MapAnything advances beyond specialist pipelines by supporting over 12 distinct 3D vision […]The post Meta AI Researchers Release MapAnything: An End-to-End Transformer Architecture that Directly Regresses Factored, Metric 3D Scene Geometry appeared first on MarkTechPost.
How to Build an Advanced End-to-End Voice AI Agent Using Hugging Face Pipelines?
In this tutorial, we build an advanced voice AI agent using Hugging Face’s freely available models, and we keep the entire pipeline simple enough to run smoothly on Google Colab.We combine Whisper for speech recognition, FLAN-T5 for natural language reasoning, and Bark for speech synthesis, all connected through transformers pipelines.The post How to Build an Advanced End-to-End Voice AI Agent Using Hugging Face Pipelines? appeared first on MarkTechPost.
Ai2 Researchers are Changing the Benchmarking Game by Introducing Fluid Benchmarking that Enhances Evaluation along Several Dimensions
A team of researchers from Allen Institute for Artificial Intelligence (Ai2), University of Washington and CMU introduce Fluid Benchmarking, an adaptive LLM evaluation method that replaces static accuracy with 2-parameter IRT ability estimation and Fisher-information–driven item selection.By asking only the most informative questions for a model’s current ability, it yields smoother training curves, delays benchmark […]The post Ai2 Researchers are Changing the Benchmarking Game by Introducing Fluid Benchmarking that Enhances Evaluation along Several Dimensions appeared first on MarkTechPost.
Google AI Introduces Agent Payments Protocol (AP2): An Open Protocol for Interoperable AI Agent Checkout Across Merchants and Wallets
This trust gap is a primary blocker for agent-led checkout on today’s payment rails.Google’s Agent Payments Protocol (AP2) addresses it with an open, interoperable specification for agent-initiated payments, defining […]The post Google AI Introduces Agent Payments Protocol (AP2): An Open Protocol for Interoperable AI Agent Checkout Across Merchants and Wallets appeared first on MarkTechPost.
A Coding Guide to Implement Zarr for Large-Scale Data: Chunking, Compression, Indexing, and Visualization Techniques
In this tutorial, we take a deep dive into the capabilities of Zarr, a library designed for efficient storage & manipulation of large, multidimensional arrays.We begin by exploring the basics, creating arrays, setting chunking strategies, and modifying values directly on disk.The post A Coding Guide to Implement Zarr for Large-Scale Data: Chunking, Compression, Indexing, and Visualization Techniques appeared first on MarkTechPost.
Google AI Ships TimesFM-2.5: Smaller, Longer-Context Foundation Model That Now Leads GIFT-Eval (Zero-Shot Forecasting)
Google Research has released TimesFM-2.5, a 200M-parameter, decoder-only time-series foundation model with a 16K context length and native probabilistic forecasting support.The new checkpoint is live on Hugging Face.On GIFT-Eval, TimesFM-2.5 now tops the leaderboard across accuracy metrics (MASE, CRPS) among zero-shot foundation models.
Stanford Researchers Introduced MedAgentBench: A Real-World Benchmark for Healthcare AI Agents
A team of Stanford University researchers have released MedAgentBench, a new benchmark suite designed to evaluate large language model (LLM) agents in healthcare contexts.Unlike prior question-answering datasets, MedAgentBench provides a virtual electronic health record (EHR) environment where AI systems must interact, plan, and execute multi-step clinical tasks.This marks a significant shift from testing […]
MoonshotAI Released Checkpoint-Engine: A Simple Middleware to Update Model Weights in LLM Inference Engines, Effective for Reinforcement Learning
MoonshotAI has open-sourced checkpoint-engine, a lightweight middleware aimed at solving one of the key bottlenecks in large language model (LLM) deployment: rapidly updating model weights across thousands of GPUs without disrupting inference.The library is particularly designed for reinforcement learning (RL) and reinforcement learning with human feedback (RLHF), where models are updated frequently and downtime […]The post MoonshotAI Released Checkpoint-Engine: A Simple Middleware to Update Model Weights in LLM Inference Engines, Effective for Reinforcement Learning appeared first on MarkTechPost.
Building an Advanced Convolutional Neural Network with Attention for DNA Sequence Classification and Interpretability
In this tutorial, we take a hands-on approach to building an advanced convolutional neural network for DNA sequence classification.We focus on simulating real biological tasks, such as promoter prediction, splice site detection, and regulatory element identification.By combining one-hot encoding, multi-scale convolutional layers, and an attention mechanism, we design a model that not only […]
OpenAI Introduces GPT-5-Codex: An Advanced Version of GPT-5 Further Optimized for Agentic Coding in Codex
OpenAI has just released GPT-5-Codex, a version of GPT-5 further optimized for “agentic coding” tasks within the Codex ecosystem.The goal: improve reliability, speed, and autonomous behavior so that Codex acts more like a teammate, not just a prompt-executor.Codex is now available across the full developer workflow: CLI, IDE extensions, web, mobile, GitHub code […]
NVIDIA AI Open-Sources ViPE (Video Pose Engine): A Powerful and Versatile 3D Video Annotation Tool for Spatial AI
A team of researchers from NVIDIA released “ViPE: Video Pose Engine for 3D Geometric Perception” bringing a key improvement for Spatial AI.It addresses the central, agonizing bottleneck that has constrained the field of 3D computer vision for years.The post NVIDIA AI Open-Sources ViPE (Video Pose Engine): A Powerful and Versatile 3D Video Annotation Tool for Spatial AI appeared first on MarkTechPost.
Meta AI Released MobileLLM-R1: A Edge Reasoning Model with less than 1B Parameters and Achieves 2x–5x Performance Boost Over Other Fully Open-Source AI Models
Meta has released MobileLLM-R1, a family of lightweight edge reasoning models now available on Hugging Face.The release includes models ranging from 140M to 950M parameters, with a focus on efficient mathematical, coding, and scientific reasoning at sub-billion scale.Unlike general-purpose chat models, MobileLLM-R1 is designed for edge deployment, aiming to deliver state-of-the-art reasoning accuracy […]
Beyond the Black Box: Architecting Explainable AI for the Structured Logic of Law
The Epistemic Gap: Why Standard XAI Fails in Legal Reasoning The core problem is that AI explanations and legal justifications operate on different epistemic planes.AI provides technical traces of decision-making, while law demands structured, precedent-driven justification.Standard XAI techniques attention maps and counterfactuals fail to bridge this gap.
A Comprehensive Coding Guide to Building Interactive Experiment Dashboards with Hugging Face Trackio
In this tutorial, we walk through Hugging Face Trackio step by step, exploring how we can track experiments locally, cleanly, and intuitively.We start by installing Trackio in Google Colab, preparing a dataset, and setting up multiple training runs with different hyperparameters.The post A Comprehensive Coding Guide to Building Interactive Experiment Dashboards with Hugging Face Trackio appeared first on MarkTechPost.
Top 5 No-Code Tools for AI Engineers/Developers
In today’s AI-driven world, no-code tools are transforming how people create and deploy intelligent applications.They empower anyone—regardless of coding expertise—to build solutions quickly and efficiently.From developing enterprise-grade RAG systems to designing multi-agent workflows or fine-tuning hundreds of LLMs, these platforms dramatically reduce development time and effort.
Software Frameworks Optimized for GPUs in AI: CUDA, ROCm, Triton, TensorRT—Compiler Paths and Performance Implications
Deep-learning throughput hinges on how effectively a compiler stack maps tensor programs to GPU execution: thread/block schedules, memory movement, and instruction selection (e.g., Tensor Core MMA pipelines).In this article we will focus on four dominant stacks—CUDA, ROCm, Triton, and TensorRT—from the compiler’s perspective and explains which optimizations move the needle in practice.The post Software Frameworks Optimized for GPUs in AI: CUDA, ROCm, Triton, TensorRT—Compiler Paths and Performance Implications appeared first on MarkTechPost.
UT Austin and ServiceNow Research Team Releases AU-Harness: An Open-Source Toolkit for Holistic Evaluation of Audio LLMs
Voice AI is becoming one of the most important frontiers in multimodal AI.From intelligent assistants to interactive agents, the ability to understand and reason over audio is reshaping how machines engage with humans.The post UT Austin and ServiceNow Research Team Releases AU-Harness: An Open-Source Toolkit for Holistic Evaluation of Audio LLMs appeared first on MarkTechPost.
Top 12 Robotics AI Blogs/NewsWebsites 2025
Robotics and artificial intelligence are converging at an unprecedented pace, driving breakthroughs in automation, perception, and human-machine collaboration.Staying current with these advancements requires following specialized sources that deliver technical depth, research updates, and industry insights.The following list highlights 12 of the most authoritative robotics and AI-focused blogs and websites to track in 2025.
How to Build a Robust Advanced Neural AI Agent with Stable Training, Adaptive Learning, and Intelligent Decision-Making?
In this tutorial, we explore the design and implementation of an Advanced Neural Agent that combines classical neural network techniques with modern stability improvements.We build the network using Xavier initialization for balanced gradient flow and add stable activations like leaky ReLU, sigmoid, and tanh with clipping to avoid overflow.To stabilize training, we apply […]
Google AI Releases VaultGemma: The Largest and Most Capable Open Model (1B-parameters) Trained from Scratch with Differential Privacy
Google AI Research and DeepMind have released VaultGemma 1B, the largest open-weight large language model trained entirely with differential privacy (DP).This development is a major step toward building AI models that are both powerful and privacy-preserving.Large language models trained on vast web-scale datasets are prone […]
IBM AI Research Releases Two English Granite Embedding Models, Both Based on the ModernBERT Architecture
IBM has quietly built a strong presence in the open-source AI ecosystem, and its latest release shows why it shouldn’t be overlooked.The company has introduced two new embedding models—granite-embedding-english-r2 and granite-embedding-small-english-r2—designed specifically for high-performance retrieval and RAG (retrieval-augmented generation) systems.These models are not only compact and efficient but also licensed under Apache 2.0, […]
How to Build a Multilingual OCR AI Agent in Python with EasyOCR and OpenCV
In this tutorial, we build an Advanced OCR AI Agent in Google Colab using EasyOCR, OpenCV, and Pillow, running fully offline with GPU acceleration.The agent includes a preprocessing pipeline with contrast enhancement (CLAHE), denoising, sharpening, and adaptive thresholding to improve recognition accuracy.Beyond basic OCR, we filter results by confidence, generate text statistics, and […]
BentoML Released llm-optimizer: An Open-Source AI Tool for Benchmarking and Optimizing LLM Inference
BentoML has recently released llm-optimizer, an open-source framework designed to streamline the benchmarking and performance tuning of self-hosted large language models (LLMs).The tool addresses a common challenge in LLM deployment: finding optimal configurations for latency, throughput, and cost without relying on manual trial-and-error.Tuning LLM inference is […]
Deepdub Introduces Lightning 2.5: A Real-Time AI Voice Model With 2.8x Throughput Gains for Scalable AI Agents and Enterprise AI
Deepdub, an Israeli Voice AI startup, has introduced Lightning 2.5, a real-time foundational voice model designed to power scalable, production-grade voice applications.The new release delivers substantial improvements in performance and efficiency, positioning it for use in live interactive systems such as contact centers, AI agents, and real-time dubbing.Performance and Efficiency Lightning 2.5 achieves […]
TwinMind Introduces Ear-3 Model: A New Voice AI Model that Sets New Industry Records in Accuracy, Speaker Labeling, Languages and Price
TwinMind, a California-based Voice AI startup, unveiled Ear-3 speech-recognition model, claiming state-of-the-art performance on several key metrics and expanded multilingual support.The release positions Ear-3 as a competitive offering against existing ASR (Automatic Speech Recognition) solutions from providers like Deepgram, AssemblyAI, Eleven Labs, Otter, Speechmatics, and OpenAI.The post TwinMind Introduces Ear-3 Model: A New Voice AI Model that Sets New Industry Records in Accuracy, Speaker Labeling, Languages and Price appeared first on MarkTechPost.
What are Optical Character Recognition (OCR) Models? Top Open-Source OCR Models
Optical Character Recognition (OCR) is the process of turning images that contain text—such as scanned pages, receipts, or photographs—into machine-readable text.What began as brittle rule-based systems has evolved into a rich ecosystem of neural architectures and vision-language models capable of reading complex, multi-lingual, and handwritten documents.The post What are Optical Character Recognition (OCR) Models?
OpenAI Adds Full MCP Tool Support in ChatGPT Developer Mode: Enabling Write Actions, Workflow Automation, and Enterprise Integrations
OpenAI has just introduced a major upgrade to ChatGPT’s developer mode by adding full support for Model Context Protocol (MCP) tools.Until now, MCP integrations inside ChatGPT were limited to search and fetch operations—essentially read-only.With this update, MCP connectors can perform write actions, which means developers can now directly update systems, trigger workflows, and […]
Meet mmBERT: An Encoder-only Language Model Pretrained on 3T Tokens of Multilingual Text in over 1800 Languages and 2–4× Faster than Previous Models
Why was a new multilingual encoder needed?XLM-RoBERTa (XLM-R) has dominated multilingual NLP for more than 5 years, an unusually long reign in AI research.While encoder-only models like BERT and RoBERTa were central to early progress, most research energy shifted toward decoder-based generative models.
Building Advanced MCP (Model Context Protocol) Agents with Multi-Agent Coordination, Context Awareness, and Gemini Integration
In this tutorial, we are walking through the process of building an advanced MCP (Model Context Protocol) Agent that runs smoothly inside Jupyter or Google Colab.We are designing the system with real-world practicality in mind, focusing on multi-agent coordination, context awareness, memory management, and dynamic tool usage.The post Building Advanced MCP (Model Context Protocol) Agents with Multi-Agent Coordination, Context Awareness, and Gemini Integration appeared first on MarkTechPost.
NVIDIA AI Releases Universal Deep Research (UDR): A Prototype Framework for Scalable and Auditable Deep Research Agents
Deep Research Tools (DRTs) like Gemini Deep Research, Perplexity, OpenAI’s Deep Research, and Grok DeepSearch rely on rigid workflows bound to a fixed LLM.While effective, they impose strict limitations: users cannot define custom strategies, swap models, or enforce domain-specific protocols.NVIDIA’s analysis identifies three core problems: […]
Baidu Releases ERNIE-4.5-21B-A3B-Thinking: A Compact MoE Model for Deep Reasoning
Baidu AI Research team has just released ERNIE-4.5-21B-A3B-Thinking, a new reasoning-focused large language model designed around efficiency, long-context reasoning, and tool integration.Being part of the ERNIE-4.5 family, this model is a Mixture-of-Experts (MoE) architecture with 21B total parameters but only 3B active parameters per token, making it computationally efficient while maintaining competitive reasoning capability.The post Baidu Releases ERNIE-4.5-21B-A3B-Thinking: A Compact MoE Model for Deep Reasoning appeared first on MarkTechPost.
MCP Team Launches the Preview Version of the ‘MCP Registry’: A Federated Discovery Layer for Enterprise AI
The Model Context Protocol (MCP) team has released the preview version of the MCP Registry, a system that could be the final puzzle piece for making enterprise AI truly production-ready.More than just a catalog, the MCP Registry introduces a federated architecture for discovering MCP servers—public or private—that mirrors how the internet itself solved addressability […]The post MCP Team Launches the Preview Version of the ‘MCP Registry’: A Federated Discovery Layer for Enterprise AI appeared first on MarkTechPost.
Building a Speech Enhancement and Automatic Speech Recognition (ASR) Pipeline in Python Using SpeechBrain
In this tutorial, we walk through an advanced yet practical workflow using SpeechBrain.We start by generating our own clean speech samples with gTTS, deliberately adding noise to simulate real-world scenarios, and then applying SpeechBrain’s MetricGAN+ model to enhance the audio.Once the audio is denoised, we run automatic speech recognition with a language model–rescored […]
MBZUAI Researchers Release K2 Think: A 32B Open-Source System for Advanced AI Reasoning and Outperforms 20x Larger Reasoning Models
A team of researchers from MBZUAI’s Institute of Foundation Models and G42 released K2 Think, is a 32B-parameter open reasoning system for advanced AI reasoning.It pairs long chain-of-thought supervised fine-tuning with reinforcement learning from verifiable rewards, agentic planning, test-time scaling, and inference optimizations (speculative decoding + wafer-scale hardware).The result is frontier-level math performance […]
Alibaba Qwen Team Releases Qwen3-ASR: A New Speech Recognition Model Built Upon Qwen3-Omni Achieving Robust Speech Recogition Performance
Alibaba Cloud’s Qwen team unveiled Qwen3-ASR Flash, an all-in-one automatic speech recognition (ASR) model (available as API service) built upon the strong intelligence of Qwen3-Omni that simplifies multilingual, noisy, and domain-specific transcription without juggling multiple systems.Key Capabilities Use cases span edtech platforms (lecture capture, multilingual tutoring), media (subtitling, voice-over), and customer service (multilingual IVR […]The post Alibaba Qwen Team Releases Qwen3-ASR: A New Speech Recognition Model Built Upon Qwen3-Omni Achieving Robust Speech Recogition Performance appeared first on MarkTechPost.
Top 7 Model Context Protocol (MCP) Servers for Vibe Coding
Modern software development is shifting from static workflows to dynamic, agent-driven coding experiences.At the center of this transition is the Model Context Protocol (MCP), a standard for connecting AI agents to external tools, data, and services.MCP provides a structured way for large language models (LLMs) to request, consume, and persist context.
ParaThinker: Scaling LLM Test-Time Compute with Native Parallel Thinking to Overcome Tunnel Vision in Sequential Reasoning
Test-time compute scaling in LLMs has traditionally relied on extending single reasoning paths.While this approach improves reasoning for a limited range, performance plateaus quickly.The post ParaThinker: Scaling LLM Test-Time Compute with Native Parallel Thinking to Overcome Tunnel Vision in Sequential Reasoning appeared first on MarkTechPost.
How to Build a Complete Multi-Domain AI Web Agent Using Notte and Gemini
In this tutorial, we demonstrate a complete, advanced implementation of the Notte AI Agent, integrating the Gemini API to power reasoning and automation.By combining Notte’s browser automation capabilities with structured outputs through Pydantic models, it showcases how an AI web agent can research products, monitor social media, analyze markets, scan job opportunities, and more.The post How to Build a Complete Multi-Domain AI Web Agent Using Notte and Gemini appeared first on MarkTechPost.
GibsonAI Releases Memori: An Open-Source SQL-Native Memory Engine for AI Agents
Similarly, AI Agents become smarter with memory.For example, an agent can remember your past purchases, your budget, […]The post GibsonAI Releases Memori: An Open-Source SQL-Native Memory Engine for AI Agents appeared first on MarkTechPost.
A New MIT Study Shows Reinforcement Learning Minimizes Catastrophic Forgetting Compared to Supervised Fine-Tuning
What is catastrophic forgetting in foundation models?Fine-tuning on new tasks often introduces catastrophic forgetting—the loss of previously learned capabilities.Why does online reinforcement learning forget less than supervised fine-tuning?
How to Create a Bioinformatics AI Agent Using Biopython for DNA and Protein Analysis
In this tutorial, we demonstrate how to build an advanced yet accessible Bioinformatics AI Agent using Biopython and popular Python libraries, designed to run seamlessly in Google Colab.By combining sequence retrieval, molecular analysis, visualization, multiple sequence alignment, phylogenetic tree construction, and motif searches into a single streamlined class, the tutorial provides a hands-on approach […]The post How to Create a Bioinformatics AI Agent Using Biopython for DNA and Protein Analysis appeared first on MarkTechPost.
Meta Superintelligence Labs Introduces REFRAG: Scaling RAG with 16× Longer Contexts and 31× Faster Decoding
Meta Superintelligence Labs has unveiled REFRAG (REpresentation For RAG), a decoding framework that rethinks retrieval-augmented generation (RAG) efficiency.REFRAG extends LLM context windows by 16× and achieves up to a 30.85× acceleration in time-to-first-token (TTFT) without compromising accuracy.The attention mechanism in large language models scales […]
Tilde AI Releases TildeOpen LLM: An Open-Source Large Language Model with Over 30 Billion Parameters and Support Most European Languages
Latvian language-tech firm Tilde has released TildeOpen LLM, an open-source foundational large language model (LLM) purpose-built for European languages, with a sharp focus on under-represented and smaller national and regional languages.It’s a strategic leap toward linguistic equity and digital sovereignty within the EU.The post Tilde AI Releases TildeOpen LLM: An Open-Source Large Language Model with Over 30 Billion Parameters and Support Most European Languages appeared first on MarkTechPost.
From Pretraining to Post-Training: Why Language Models Hallucinate and How Evaluation Methods Reinforce the Problem
Large language models (LLMs) very often generate “hallucinations”—confident yet incorrect outputs that appear plausible.Despite improvements in training methods and architectures, hallucinations persist.A new research from OpenAI provides a rigorous explanation: hallucinations stem from statistical properties of supervised versus self-supervised learning, and their persistence is reinforced by misaligned evaluation benchmarks.
Implementing DeepSpeed for Scalable Transformers: Advanced Training with Gradient Checkpointing and Parallelism
In this advanced DeepSpeed tutorial, we provide a hands-on walkthrough of cutting-edge optimization techniques for training large language models efficiently.By combining ZeRO optimization, mixed-precision training, gradient accumulation, and advanced DeepSpeed configurations, the tutorial demonstrates how to maximize GPU memory utilization, reduce training overhead, and enable scaling of transformer models in resource-constrained environments, such as […]The post Implementing DeepSpeed for Scalable Transformers: Advanced Training with Gradient Checkpointing and Parallelism appeared first on MarkTechPost.
Meet ARGUS: A Scalable AI Framework for Training Large Recommender Transformers to One Billion Parameters
Yandex has introduced ARGUS (AutoRegressive Generative User Sequential modeling), a large-scale transformer-based framework for recommender systems that scales up to one billion parameters.This breakthrough places Yandex among a small group of global technology leaders — alongside Google, Netflix, and Meta — that have successfully overcome the long-standing technical barriers in scaling recommender transformers.The post Meet ARGUS: A Scalable AI Framework for Training Large Recommender Transformers to One Billion Parameters appeared first on MarkTechPost.
Hugging Face Open-Sourced FineVision: A New Multimodal Dataset with 24 Million Samples for Training Vision-Language Models (VLMs)
Hugging Face has just released FineVision, an open multimodal dataset designed to set a new standard for Vision-Language Models (VLMs).With 17.3 million images, 24.3 million samples, 88.9 million question-answer turns, and nearly 10 billion answer tokens, FineVision position itself as one of the largest and structured publicly available VLM training datasets.FineVision aggregates 200+ […]
Alibaba AI Unveils Qwen3-Max Preview: A Trillion-Parameter Qwen Model with Super Fast Speed and Quality
Alibaba’s Qwen Team unveiled Qwen3-Max-Preview (Instruct), a new flagship large language model with over one trillion parameters—their largest to date.It is accessible through Qwen Chat, Alibaba Cloud API, OpenRouter, and as default in Hugging Face’s AnyCoder tool.This milestone comes at a time when the industry […]
Google AI Introduces Personal Health Agent (PHA): A Multi-Agent Framework that Enables Personalized Interactions to Address Individual Health Needs
What is a Personal Health Agent?Large language models (LLMs) have demonstrated strong performance across various domains like clinical reasoning, decision support, and consumer health applications.The post Google AI Introduces Personal Health Agent (PHA): A Multi-Agent Framework that Enables Personalized Interactions to Address Individual Health Needs appeared first on MarkTechPost.
How to Build a Complete End-to-End NLP Pipeline with Gensim: Topic Modeling, Word Embeddings, Semantic Search, and Advanced Text Analysis
In this tutorial, we present a complete end-to-end Natural Language Processing (NLP) pipeline built with Gensim and supporting libraries, designed to run seamlessly in Google Colab.It integrates multiple core techniques in modern NLP, including preprocessing, topic modeling with Latent Dirichlet Allocation (LDA), word embeddings with Word2Vec, TF-IDF-based similarity analysis, and semantic search.The post How to Build a Complete End-to-End NLP Pipeline with Gensim: Topic Modeling, Word Embeddings, Semantic Search, and Advanced Text Analysis appeared first on MarkTechPost.
Meet Chatterbox Multilingual: An Open-Source Zero-Shot Text To Speech (TTS) Multilingual Model with Emotion Control and Watermarking
Resemble AI has recently released Chatterbox Multilingual, a production grade open-source Text To Speech (TTS) model designed for zero-shot voice cloning in 23 languages.It is distributed under the MIT license, making it freely available for integration and modification.The system builds on the original Chatterbox framework and adds multilingual capability, expressive controls, and built-in […]
Biomni-R0: New Agentic LLMs Trained End-to-End with Multi-Turn Reinforcement Learning for Expert-Level Intelligence in Biomedical Research
The Growing Role of AI in Biomedical Research The field of biomedical artificial intelligence is evolving rapidly, with increasing demand for agents capable of performing tasks that span genomics, clinical diagnostics, and molecular biology.they are expected to reason through complex biological problems, interpret patient data, and […]The post Biomni-R0: New Agentic LLMs Trained End-to-End with Multi-Turn Reinforcement Learning for Expert-Level Intelligence in Biomedical Research appeared first on MarkTechPost.
Google AI Releases EmbeddingGemma: A 308M Parameter On-Device Embedding Model with State-of-the-Art MTEB Results
EmbeddingGemma is Google’s new open text embedding model optimized for on-device AI, designed to balance efficiency with state-of-the-art retrieval performance.At just 308 million parameters, EmbeddingGemma is lightweight enough to run on mobile devices and offline environments.Despite its size, it performs competitively with much larger embedding […]
Google DeepMind Finds a Fundamental Bug in RAG: Embedding Limits Break Retrieval at Scale
Retrieval-Augmented Generation (RAG) systems generally rely on dense embedding models that map queries and documents into fixed-dimensional vector spaces.While this approach has become the default for many AI applications, a recent research from Google DeepMind team explains a fundamental architectural limitation that cannot be solved by larger models or better training alone.The post Google DeepMind Finds a Fundamental Bug in RAG: Embedding Limits Break Retrieval at Scale appeared first on MarkTechPost.
Australia’s Large Language Model Landscape: Technical Assessment
Key Points Local Model Development: Kangaroo LLM Kangaroo LLM is Australia’s flagship effort to build a sovereign, open-source large language model tailored to Australian English and culture.However, as of August 2025, Kangaroo […]The post Australia’s Large Language Model Landscape: Technical Assessment appeared first on MarkTechPost.
Nous Research Team Releases Hermes 4: A Family of Open-Weight AI Models with Hybrid Reasoning
Nous Research has released Hermes 4, a family of open-weight models (14B, 70B, and 405B parameter sizes based on Llama 3.1 checkpoints) that achieves frontier-level performance through pure post-training techniques.Hermes 4 introduces hybrid reasoning – models can toggle between standard responses and explicit reasoning using <think>...</think> tags when complex problems require deeper deliberation.
A Coding Implementation of Quantum State Evolution, Decoherence, and Entanglement Dynamics using QuTiP
In this advanced QuTiP tutorial, we explore the rich dynamics of quantum systems using Python and the QuTiP framework.We’ll begin by preparing fundamental single- and two-qubit states, including Bell pairs, and then move on to implement key quantum operations such as Pauli matrices, Hadamard gates, and CNOT.From there, we’ll simulate Rabi oscillations in […]
What is Agentic RAG? Use Cases and Top Agentic RAG Tools (2025)
Agentic RAG combines the strengths of traditional RAG—where large language models (LLMs) retrieve and ground outputs in external context—with agentic decision-making and tool use.Unlike static approaches, agentic RAG features AI agents that orchestrate retrieval, generation, query planning, and iterative reasoning.Use Cases and Top Agentic RAG Tools (2025) appeared first on MarkTechPost.
Meta AI Introduces DeepConf: First AI Method to Achieve 99.9% on AIME 2025 with Open-Source Models Using GPT-OSS-120B
Large language models (LLMs) have reshaped AI reasoning, with parallel thinking and self-consistency methods often cited as pivotal advances.However, these techniques face a fundamental trade-off: sampling multiple reasoning paths boosts accuracy but at a steep computational cost.A team of researchers from Meta AI and UCSD introduce Deep Think with Confidence (DeepConf), a new […]
The Evolution of AI Protocols: Why Model Context Protocol (MCP) Could Become the New HTTP for AI
Welcome to a new era of AI interoperability, where the Model Context Protocol (MCP) stands ready to do for agents and AI assistants what HTTP did for the web.If you’re building, scaling, or analyzing AI systems, MCP is the open standard you can’t ignore—it provides a universal contract for discovering tools, fetching resources, and […]The post The Evolution of AI Protocols: Why Model Context Protocol (MCP) Could Become the New HTTP for AI appeared first on MarkTechPost.
Google AI’s New Regression Language Model (RLM) Framework Enables LLMs to Predict Industrial System Performance Directly from Raw Text Data
Google’s new Regression Language Model (RLM) approach enables Large Language Models (LLMs) to predict industrial system performance directly from raw text data, without relying on complex feature engineering or rigid tabular formats.The Challenge of Industrial System Prediction Predicting performance for large-scale industrial systems—like Google’s Borg compute clusters—has traditionally required extensive domain-specific feature engineering and […]The post Google AI’s New Regression Language Model (RLM) Framework Enables LLMs to Predict Industrial System Performance Directly from Raw Text Data appeared first on MarkTechPost.
A Coding Implementation of an Advanced Tool-Using AI Agent with Semantic Kernel and Gemini
In this tutorial, we build an advanced AI agent using Semantic Kernel combined with Google’s Gemini free model, and we run it seamlessly on Google Colab.We start by wiring Semantic Kernel plugins as tools, like web search, math evaluation, file I/O, and note-taking, and then let Gemini orchestrate them through structured JSON outputs.The post A Coding Implementation of an Advanced Tool-Using AI Agent with Semantic Kernel and Gemini appeared first on MarkTechPost.
NVIDIA AI Released Jet-Nemotron: 53x Faster Hybrid-Architecture Language Model Series that Translates to a 98% Cost Reduction for Inference at Scale
NVIDIA researchers have shattered the longstanding efficiency hurdle in large language model (LLM) inference, releasing Jet-Nemotron—a family of models (2B and 4B) that delivers up to 53.6× higher generation throughput than leading full-attention LLMs while matching, or even surpassing, their accuracy.Most importantly, this breakthrough isn’t the result of a new pre-training run from scratch, […]The post NVIDIA AI Released Jet-Nemotron: 53x Faster Hybrid-Architecture Language Model Series that Translates to a 98% Cost Reduction for Inference at Scale appeared first on MarkTechPost.
Google AI Introduces Gemini 2.5 Flash Image: A New Model that Allows You to Generate and Edit Images by Simply Describing Them
Google AI has just unveiled Gemini 2.5 Flash Image, a new generation image model designed to let users generate and edit images simply by describing them—and its true innovation is how it delivers precise, consistent, and high-fidelity edits at impressive speed and scale.What Makes Gemini 2.5 Flash Image Impressive?Gemini 2.5 Flash Image is […]
What is MLSecOps(Secure CI/CD for Machine Learning)?: Top MLSecOps Tools (2025)
Machine learning (ML) is transforming industries, powering innovation in domains as varied as financial services, healthcare, autonomous systems, and e-commerce.However, as organizations operationalize ML models at scale, traditional approaches to software delivery—chiefly, Continuous Integration and Continuous Deployment (CI/CD)—have revealed critical gaps when applied to machine learning workflows.The post What is MLSecOps(Secure CI/CD for Machine Learning)?: Top MLSecOps Tools (2025) appeared first on MarkTechPost.
Your LLM is 5x Slower Than It Should Be. The Reason? Pessimism—and Stanford Researchers Just Showed How to Fix It
In the fast-paced world of AI, large language models (LLMs) like GPT-4 and Llama are powering everything from chatbots to code assistants.But here’s a dirty secret: your LLM inference—the process of generating responses—might be running up to five times slower than necessary.A overly cautious approach to handling uncertainty in output lengths.
Building a Reliable End-to-End Machine Learning Pipeline Using MLE-Agent and Ollama Locally
We begin this tutorial by showing how we can combine MLE-Agent with Ollama to create a fully local, API-free machine learning workflow.We set up a reproducible environment in Google Colab, generate a small synthetic dataset, and then guide the agent to draft a training script.The post Building a Reliable End-to-End Machine Learning Pipeline Using MLE-Agent and Ollama Locally appeared first on MarkTechPost.
Microsoft Released VibeVoice-1.5B: An Open-Source Text-to-Speech Model that can Synthesize up to 90 Minutes of Speech with Four Distinct Speakers
Microsoft’s latest open source release, VibeVoice-1.5B, redefines the boundaries of text-to-speech (TTS) technology—delivering expressive, long-form, multi-speaker generated audio that is MIT licensed, scalable, and highly flexible for research use.it’s a framework designed to generate up to 90 minutes of uninterrupted, natural-sounding audio, support simultaneous generation of up […]The post Microsoft Released VibeVoice-1.5B: An Open-Source Text-to-Speech Model that can Synthesize up to 90 Minutes of Speech with Four Distinct Speakers appeared first on MarkTechPost.
SEA-LION v4: Multimodal Language Modeling for Southeast Asia
AI Singapore (AISG) has released SEA-LION v4, an open-source multimodal language model developed in collaboration with Google and based on the Gemma 3 (27B) architecture.The model is designed to support Southeast Asian languages, including those with limited digital resources, and provides both text and image understanding capabilities.SEA-LION v4 uses a commercially permissive license […]
How Do GPUs and TPUs Differ in Training Large Transformer Models? Top GPUs and TPUs with Benchmark
Both GPUs and TPUs play crucial roles in accelerating the training of large transformer models, but their core architectures, performance profiles, and ecosystem compatibility lead to significant differences in use case, speed, and flexibility.Architecture and Hardware Fundamentals TPUs are custom ASICs (Application-Specific Integrated Circuits) engineered by Google, purpose-built for highly efficient matrix operations required […]The post How Do GPUs and TPUs Differ in Training Large Transformer Models?
Google AI Introduced Guardrailed-AMIE (g-AMIE): A Multi-Agent Approach to Accountability in Conversational Medical AI
Recent advances in large language model (LLM)-powered diagnostic AI agents have yielded systems capable of high-quality clinical dialogue, differential diagnosis, and management planning in simulated settings.Yet, delivering individual diagnoses and treatment recommendations remains strictly regulated: only licensed clinicians can be responsible for critical patient-facing decisions.The post Google AI Introduced Guardrailed-AMIE (g-AMIE): A Multi-Agent Approach to Accountability in Conversational Medical AI appeared first on MarkTechPost.
How to Implement the LLM Arena-as-a-Judge Approach to Evaluate Large Language Model Outputs
In this tutorial, we will explore how to implement the LLM Arena-as-a-Judge approach to evaluate large language model outputs.Instead of assigning isolated numerical scores to each response, this method performs head-to-head comparisons between outputs to determine which one is better — based on criteria you define, such as helpfulness, clarity, or tone.The post How to Implement the LLM Arena-as-a-Judge Approach to Evaluate Large Language Model Outputs appeared first on MarkTechPost.
Top 10 AI Blogs and News Websites for AI Developers and Engineers in 2025
Staying current with the latest breakthroughs, tools, and industry shifts is critical for AI developers and engineers.To help you cut through the noise, here’s a curated list of the top 10 AI-focused blogs and news platforms that deliver high-quality, technical, and actionable content for AI developers and engineers at every level.The post Top 10 AI Blogs and News Websites for AI Developers and Engineers in 2025 appeared first on MarkTechPost.
Zhipu AI Unveils ComputerRL: An AI Framework Scaling End-to-End Reinforcement Learning for Computer Use Agents
In the rapidly evolving landscape of AI-driven automation, Zhipu AI has introduced ComputerRL, a groundbreaking framework designed to empower agents with the ability to navigate and manipulate complex digital workspaces.This innovation addresses a core challenge in AI agent development: the disconnect between computer agents and human-designed graphical user interfaces (GUIs).The post Zhipu AI Unveils ComputerRL: An AI Framework Scaling End-to-End Reinforcement Learning for Computer Use Agents appeared first on MarkTechPost.
Google Releases Mangle: A Programming Language for Deductive Database Programming
Google has introduced Mangle, a new open-source programming language that extends the classic logic-based language Datalog for modern deductive database programming.Implemented as a Go library, Mangle is designed to simplify the complex task of querying and reasoning about data spread across multiple, disparate sources.The release addresses a growing challenge for developers and security […]
What Is Speaker Diarization? A 2025 Technical Guide: Top 9 Speaker Diarization Libraries and APIs in 2025
Speaker diarization is the process of answering “who spoke when” by separating an audio stream into segments and consistently labeling each segment by speaker identity (e.g., Speaker A, Speaker B), thereby making transcripts clearer, searchable, and useful for analytics across domains like call centers, legal, healthcare, media, and conversational AI.The post What Is Speaker Diarization?A 2025 Technical Guide: Top 9 Speaker Diarization Libraries and APIs in 2025 appeared first on MarkTechPost.
NVIDIA AI Just Released Streaming Sortformer: A Real-Time Speaker Diarization that Figures Out Who’s Talking in Meetings and Calls Instantly
NVIDIA has released its Streaming Sortformer, a breakthrough in real-time speaker diarization that instantly identifies and labels participants in meetings, calls, and voice-enabled applications—even in noisy, multi-speaker environments.Designed for low-latency, GPU-powered inference, the model is optimized for English and Mandarin, and can track up to four simultaneous speakers with millisecond-level precision.The post NVIDIA AI Just Released Streaming Sortformer: A Real-Time Speaker Diarization that Figures Out Who’s Talking in Meetings and Calls Instantly appeared first on MarkTechPost.
What is DeepSeek-V3.1 and Why is Everyone Talking About It?
The Chinese AI startup DeepSeek releases DeepSeek-V3.1, it’s latest flagship language model.Notably, DeepSeek models have rapidly gained a reputation for delivering OpenAI and Anthropic-level performance at a fraction of the cost.Model Architecture and Capabilities Performance Benchmarks […]
DeepCode: An Open Agentic Coding Platform that Transforms Research Papers and Technical Documents into Production-Ready Code
The emergence of advanced AI development tools is revolutionizing the way researchers and engineers translate groundbreaking academic ideas into robust, real-world applications.A team of researchers from the University of Hong Kong release DeepCode.DeepCode proposes an “Open Agentic Coding” paradigm, leveraging multi-agent AI systems to automate coding processes from research paper interpretation through to […]
Meet South Korea’s LLM Powerhouses: HyperClova, AX, Solar Pro, and More
South Korea is rapidly establishing itself as a key innovator in large language models (LLMs), driven by strategic government investments, corporate research, and open-source collaborations to create models tailored for Korean language processing and domestic applications.This focus helps mitigate dependencies on foreign AI technologies, enhances data privacy, and supports sectors like healthcare, education, and […]The post Meet South Korea’s LLM Powerhouses: HyperClova, AX, Solar Pro, and More appeared first on MarkTechPost.
Liquid AI Releases LFM2-VL: Super-Fast, Open-Weight Vision-Language Models Designed for Low-Latency and Device-Aware Deployment
Liquid AI has officially released LFM2-VL, a new family of vision-language foundation models optimized for low-latency, on-device deployment.With two highly efficient variants—LFM2-VL-450M and LFM2-VL-1.6B—this launch marks a significant leap in bringing multimodal AI to smartphones, laptops, wearables, and embedded systems without compromising speed or accuracy.Unprecedented Speed and Efficiency LFM2-VL models are engineered to […]
ZenFlow: A New DeepSpeed Extension Designed as a Stall-Free Offloading Engine for Large Language Model (LLM) Training
The DeepSpeed team unveiled ZenFlow, a new offloading engine designed to overcome a major bottleneck in large language model (LLM) training: CPU-induced GPU stalls.While offloading optimizers and gradients to CPU memory reduces GPU memory pressure, traditional frameworks like ZeRO-Offload and ZeRO-Infinity often leave expensive GPUs idle for most of each training step—waiting on slow […]The post ZenFlow: A New DeepSpeed Extension Designed as a Stall-Free Offloading Engine for Large Language Model (LLM) Training appeared first on MarkTechPost.
Deep Learning Framework Showdown: PyTorch vs TensorFlow in 2025
The choice between PyTorch and TensorFlow remains one of the most debated decisions in AI development.Both frameworks have evolved dramatically since their inception, converging in some areas while maintaining distinct strengths.This article explores the latest patterns from the comprehensive survey paper from Alfaisal University, Saudi Arabia, synthesizing usability, performance, deployment, and ecosystem considerations […]
Google AI Released 5 New AI Agents/Platforms for Developers
Google Cloud recently unveiled five specialized AI agents designed to streamline developer workflows—reducing manual effort, accelerating analysis, and lowering the barrier to advanced data and code automation.Each agent addresses a distinct developer challenge, from data pipeline orchestration to enterprise-grade GitHub management.Here’s a detailed look at what these agents do, their technical underpinnings, and […]
Migrating to Model Context Protocol (MCP): An Adapter-First Playbook
Model Context Protocol (MCP) has rapidly emerged as a universal standard for connecting AI models to diverse applications, systems, and tools—imagine “USB-C for AI integrations,” as commonly described in the industry.For organizations accustomed to custom integrations, the migration to MCP can be transformative, simultaneously reducing technical debt and unlocking new interoperability benefits.The post Migrating to Model Context Protocol (MCP): An Adapter-First Playbook appeared first on MarkTechPost.
Hello, AI Formulas: Why =COPILOT() Is the Biggest Excel Upgrade in Years
Microsoft has officially introduced the COPILOT function in Excel for Windows and Mac, bringing the power of large language models (LLMs) directly into spreadsheets.This move represents a fundamental shift: AI is now a native feature, not just an external add-in or separate tool.Users can now analyze, summarize, and generate data using natural language […]
Signal and Noise: Unlocking Reliable LLM Evaluation for Better AI Decisions
Evaluating large language models (LLMs) is both scientifically and economically costly.As the field races toward ever-larger models, the methodology for evaluating and comparing them becomes increasingly critical—not just for benchmark scores, but for informed development decisions.Recent research from the Allen Institute for Artificial Intelligence (Ai2) introduces a robust framework centered around two fundamental […]
A Coding Implementation to Build a Complete Self-Hosted LLM Workflow with Ollama, REST API, and Gradio Chat Interface
In this tutorial, we implement a fully functional Ollama environment inside Google Colab to replicate a self-hosted LLM workflow.We begin by installing Ollama directly on the Colab VM using the official Linux installer and then launch the Ollama server in the background to expose the HTTP API on localhost:11434.The post A Coding Implementation to Build a Complete Self-Hosted LLM Workflow with Ollama, REST API, and Gradio Chat Interface appeared first on MarkTechPost.
Meet M3-Agent: A Multimodal Agent with Long-Term Memory and Enhanced Reasoning Capabilities
In the future, a home robot could manage daily chores itself and learn household patterns from ongoing experience.For a multimodal agent, this intelligence depends on (a) observing the world through multimodal sensors continuously, (b) storing its experience in long-term […]The post Meet M3-Agent: A Multimodal Agent with Long-Term Memory and Enhanced Reasoning Capabilities appeared first on MarkTechPost.
NVIDIA AI Releases Nemotron Nano 2 AI Models: A Production-Ready Enterprise AI Model Family and 6x Faster than Similar Sized Model
NVIDIA has unveiled the Nemotron Nano 2 family, introducing a line of hybrid Mamba-Transformer large language models (LLMs) that not only push state-of-the-art reasoning accuracy but also deliver up to 6× higher inference throughput than models of similar size.This release stands out with unprecedented transparency in data and methodology, as NVIDIA provides most of […]The post NVIDIA AI Releases Nemotron Nano 2 AI Models: A Production-Ready Enterprise AI Model Family and 6x Faster than Similar Sized Model appeared first on MarkTechPost.
Memp: A Task-Agnostic Framework that Elevates Procedural Memory to a Core Optimization Target in LLM-based Agent
LLM agents have become powerful enough to handle complex tasks, ranging from web research and report generation to data analysis and multi-step software workflows.However, they struggle with procedural memory, which is often rigid, manually designed, or locked inside model weights today.The post Memp: A Task-Agnostic Framework that Elevates Procedural Memory to a Core Optimization Target in LLM-based Agent appeared first on MarkTechPost.
Emerging Trends in AI Cybersecurity Defense: What’s Shaping 2025? Top AI Security Tools
The AI security arms race is in full swing.As cyber threats grow more sophisticated, organizations are reimagining defense strategies—with artificial intelligence taking center stage.Here’s a look at some of the most impactful trends you should watch in AI-powered cybersecurity defense.
BlackRock Introduces AlphaAgents: Advancing Equity Portfolio Construction with Multi-Agent LLM Collaboration
The use of artificial intelligence (AI) in financial markets has grown rapidly, with large language models (LLMs) increasingly applied to equity analysis, portfolio management, and stock selection.BlackRock research team proposed AlphaAgents for investment research.The AlphaAgents framework leverages the power of multi-agent systems to improve investment outcomes, reduce cognitive bias, and enhance the decision-making […]
Master Vibe Coding: Pros, Cons, and Best Practices for Data Engineers
Large-language-model (LLM) tools now let engineers describe pipeline goals in plain English and receive generated code—a workflow dubbed vibe coding.Used well, it can accelerate prototyping and documentation.Used carelessly, it can introduce silent data corruption, security risks, or unmaintainable code.
Qwen Team Introduces Qwen-Image-Edit: The Image Editing Version of Qwen-Image with Advanced Capabilities for Semantic and Appearance Editing
In the domain of multimodal AI, instruction-based image editing models are transforming how users interact with visual content.Just released in August 2025 by Alibaba’s Qwen Team, Qwen-Image-Edit builds on the 20B-parameter Qwen-Image foundation to deliver advanced editing capabilities.This model excels in semantic editing (e.g., style transfer and novel view synthesis) and appearance editing […]
Creating Dashboards Using Vizro MCP: Vizro is an Open-Source Python Toolkit by McKinsey
Vizro is an open-source Python toolkit by McKinsey that makes it easy to build beautiful, production-ready data visualization apps.With just a few lines of configuration (via JSON, YAML, or Python dictionaries), you can create multi-page dashboards that would normally take thousands of lines of code.Built on top of Plotly, Dash, and Pydantic, Vizro […]
Is Model Context Protocol MCP the Missing Standard in AI Infrastructure?
The explosive growth of artificial intelligence, particularly large language models (LLMs), has revolutionized how businesses operate, from automating customer service to enhancing data analysis.Yet, as enterprises integrate AI into core workflows, a persistent challenge emerges: how to securely and efficiently connect these models to real-world data sources without custom, fragmented integrations.The post Is Model Context Protocol MCP the Missing Standard in AI Infrastructure? appeared first on MarkTechPost.
Alibaba AI Team Just Released Ovis 2.5 Multimodal LLMs: A Major Leap in Open-Source AI with Enhanced Visual Perception and Reasoning Capabilities
Ovis2.5, the latest large multimodal language model (MLLM) from Alibaba’s AIDC-AI team, is making waves in the open-source AI community with its 9B and 2B parameter variants.Ovis2.5 sets new benchmarks for performance and efficiency by introducing technical advances geared toward native-resolution vision perception, deep multimodal reasoning, and robust OCR — tackling long-standing limitations faced […]The post Alibaba AI Team Just Released Ovis 2.5 Multimodal LLMs: A Major Leap in Open-Source AI with Enhanced Visual Perception and Reasoning Capabilities appeared first on MarkTechPost.
What is AI Inference? A Technical Deep Dive and Top 9 AI Inference Providers (2025 Edition)
Artificial Intelligence (AI) has evolved rapidly—especially in how models are deployed and operated in real-world systems.The core function that connects model training to practical applications is “inference”.This article offers a technical deep dive into AI inference as of 2025, covering its distinction from training, latency challenges for modern models, and optimization strategies such […]
Building an MCP-Powered AI Agent with Gemini and mcp-agent Framework: A Step-by-Step Implementation Guide
In this tutorial, we walk through building an advanced AI agent using the mcp-agent and Gemini.We start by setting up a robust environment with all the necessary dependencies and then implement an MCP tool server that provides structured services such as web search, data analysis, code execution, and weather information.The post Building an MCP-Powered AI Agent with Gemini and mcp-agent Framework: A Step-by-Step Implementation Guide appeared first on MarkTechPost.
Hugging Face Unveils AI Sheets: A Free, Open-Source No-Code Toolkit for LLM-Powered Datasets
Hugging Face has just released AI Sheets, a free, open-source, and local-first no-code tool designed to radically simplify dataset creation and enrichment with AI.AI Sheets aims to democratize access to AI-powered data handling by merging the intuitive spreadsheet interface with direct access to leading open-source Large Language Models (LLMs) like Qwen, Kimi, Llama 3, […]The post Hugging Face Unveils AI Sheets: A Free, Open-Source No-Code Toolkit for LLM-Powered Datasets appeared first on MarkTechPost.
How to Test an OpenAI Model Against Single-Turn Adversarial Attacks Using deepteam
In this tutorial, we’ll explore how to test an OpenAI model against single-turn adversarial attacks using deepteam. deepteam provides 10+ attack methods—like prompt injection, jailbreaking, and leetspeak—that expose weaknesses in LLM applications.It begins with simple baseline attacks and then applies more advanced techniques (known as attack enhancement) to mimic real-world malicious behavior.The post How to Test an OpenAI Model Against Single-Turn Adversarial Attacks Using deepteam appeared first on MarkTechPost.
What Is AI Red Teaming? Top 18 AI Red Teaming Tools (2025)
AI Red Teaming is the process of systematically testing artificial intelligence systems—especially generative AI and machine learning models—against adversarial attacks and security stress scenarios.while penetration testing targets known software flaws, red teaming probes for unknown AI-specific vulnerabilities, unforeseen risks, and emergent behaviors.Top 18 AI Red Teaming Tools (2025) appeared first on MarkTechPost.
Meet DeepFleet: Amazon’s New AI Models Suite that can Predict Future Traffic Patterns for Fleets of Mobile Robots
Amazon has reached a remarkable milestone by deploying its one-millionth robot across global fulfillment and sortation centers, solidifying its position as the world’s largest operator of industrial mobile robotics.This achievement coincides with the launch of DeepFleet, a groundbreaking suite of foundation models designed to enhance coordination among vast fleets of mobile robots.The post Meet DeepFleet: Amazon’s New AI Models Suite that can Predict Future Traffic Patterns for Fleets of Mobile Robots appeared first on MarkTechPost.
From Deployment to Scale: 11 Foundational Enterprise AI Concepts for Modern Businesses
In the era of artificial intelligence, enterprises face both unprecedented opportunities and complex challenges.Success hinges not just on adopting the latest tools, but on fundamentally rethinking how AI integrates with people, processes, and platforms.Here are eleven AI concepts every enterprise leader must understand to harness AI’s transformative potential, backed by the latest research […]
A Coding Guide to Build and Validate End-to-End Partitioned Data Pipelines in Dagster with Machine Learning Integration
In this tutorial, we implement an advanced data pipeline using Dagster.We set up a custom CSV-based IOManager to persist assets, define partitioned daily data generation, and process synthetic sales data through cleaning, feature engineering, and model training.Along the way, we add a data-quality asset check to validate nulls, ranges, and categorical values, and […]
Meet dots.ocr: A New 1.7B Vision-Language Model that Achieves SOTA Performance on Multilingual Document Parsing
dots.ocr is an open-source vision-language transformer model developed for multilingual document layout parsing and optical character recognition (OCR).It performs both layout detection and content recognition within a single architecture, supporting over 100 languages and a wide variety of structured and unstructured document types.Architecture Capabilities Benchmark Performance dots.ocr has been evaluated against modern document […]
Amazon Unveils Bedrock AgentCore Gateway: Redefining Enterprise AI Agent Tool Integration
Amazon Web Services (AWS) has launched the Amazon Bedrock AgentCore Gateway, a transformative managed service designed to simplify and scale AI agent-to-tool integrations for enterprises.As organizations seek to leverage AI agents in increasingly complex environments with hundreds of tools and services, the Gateway addresses critical pain points: interoperability, security, tool discovery, and infrastructure management—all […]The post Amazon Unveils Bedrock AgentCore Gateway: Redefining Enterprise AI Agent Tool Integration appeared first on MarkTechPost.
NVIDIA AI Just Released the Largest Open-Source Speech AI Dataset and State-of-the-Art Models for European Languages
Nvidia has taken a major leap in the development of multilingual speech AI, unveiling Granary, the largest open-source speech dataset for European languages, and two state-of-the-art models: Canary-1b-v2 and Parakeet-tdt-0.6b-v3.This release sets a new standard for accessible, high-quality resources in automatic speech recognition (ASR) and speech translation (AST), especially for underrepresented European languages.Granary: […]
R-Zero: A Fully Autonomous AI Framework that Generates Its Own Training Data from Scratch
Large Language Models (LLMs) have revolutionized fields from natural language understanding to reasoning and code generation.A team of researchers from Tencent AI Seattle Lab, Washington University, the University of Maryland, and the University of […]The post R-Zero: A Fully Autonomous AI Framework that Generates Its Own Training Data from Scratch appeared first on MarkTechPost.
This AI Paper Introduces ReaGAN: A Graph Agentic Network That Empowers Nodes with Autonomous Planning and Global Semantic Retrieval
How can we make every node in a graph its own intelligent agent—capable of personalized reasoning, adaptive retrieval, and autonomous decision-making?This is the core question explored by a group researchers from Rutgers University.The research team introduced ReaGAN—a Retrieval-augmented Graph Agentic Network that reimagines each node as an independent reasoning agent.
Salesforce AI Releases Moirai 2.0: Salesforce’s Latest Time Series Foundation Model Built on a Decoder‑only Transformer Architecture
Salesforce AI Research has unveiled Moirai 2.0, the latest advancement in the world of time series foundation models.Built atop a decoder-only transformer architecture, Moirai 2.0 sets a new bar for performance and efficiency, claiming the #1 spot on the GIFT-Eval benchmark-the gold standard for time-series forecasting model evaluation.Not only is it 44% faster […]
An Implementation Guide to Design Intelligent Parallel Workflows in Parsl for Multi-Tool AI Agent Execution
In this tutorial, we implement an AI agent pipeline using Parsl, leveraging its parallel execution capabilities to run multiple computational tasks as independent Python apps.We configure a local ThreadPoolExecutor for concurrency, define specialized tools such as Fibonacci computation, prime counting, keyword extraction, and simulated API calls, and coordinate them through a lightweight planner that […]The post An Implementation Guide to Design Intelligent Parallel Workflows in Parsl for Multi-Tool AI Agent Execution appeared first on MarkTechPost.
Europe’s Top AI Models of 2025: Multilingual, Open, and Enterprise-Ready
Europe’s AI ecosystem in 2025 is a robust arena of open innovation, multilingual capabilities, and enterprise-grade reasoning.Below, we present an in-depth, fact-checked review of the region’s most advanced AI models, with technical specifications, licensing, and standout strengths.The post Europe’s Top AI Models of 2025: Multilingual, Open, and Enterprise-Ready appeared first on MarkTechPost.
Top 6 Model Context Protocol (MCP) News Blogs (2025 Update)
As Model Context Protocol evolves into the “USB-C port for AI applications,” connecting AI agents to the world’s tools and data, these authoritative blogs and websites are essential for anyone aiming to leverage MCP for enterprise integration, development, or research.Here’s a list of the top MCP resources you need to follow in 2025 (LIVE): […]The post Top 6 Model Context Protocol (MCP) News Blogs (2025 Update) appeared first on MarkTechPost.
Efficient AI Agents Don’t Have to Be Expensive: Here’s Proof
Are AI agents getting too expensive to use at scale?Today’s most impressive AI agents can tackle massive, multi-step tasks using the reasoning power of large language […]The post Efficient AI Agents Don’t Have to Be Expensive: Here’s Proof appeared first on MarkTechPost.
Dynamic Fine-Tuning (DFT): Bridging the Generalization Gap in Supervised Fine-Tuning (SFT) for LLMs
Supervised Fine-Tuning (SFT) is a standard technique for adapting LLMs to new tasks by training them on expert demonstration datasets.It is valued for its simplicity and ability to develop expert-like behavior quickly, but often underperforms in generalization compared to reinforcement learning (RL).The post Dynamic Fine-Tuning (DFT): Bridging the Generalization Gap in Supervised Fine-Tuning (SFT) for LLMs appeared first on MarkTechPost.
Guardrails AI Introduces Snowglobe: The Simulation Engine for AI Agents and Chatbots
Guardrails AI has announced the general availability of Snowglobe, a breakthrough simulation engine designed to address one of the thorniest challenges in conversational AI: reliably testing AI Agents/chatbots at scale before they ever reach production.Tackling an Infinite Input Space with Simulation Evaluating AI agents—especially open-ended chatbots—has traditionally required painstaking manual scenario creation.The post Guardrails AI Introduces Snowglobe: The Simulation Engine for AI Agents and Chatbots appeared first on MarkTechPost.
Google AI Introduces Gemma 3 270M: A Compact Model for Hyper-Efficient, Task-Specific Fine-Tuning
Google AI has expanded the Gemma family with the introduction of Gemma 3 270M, a lean, 270-million-parameter foundation model built explicitly for efficient, task-specific fine-tuning.This model demonstrates robust instruction-following and advanced text structuring capabilities “out of the box,” meaning it’s ready for immediate deployment and customization with minimal additional training.The post Google AI Introduces Gemma 3 270M: A Compact Model for Hyper-Efficient, Task-Specific Fine-Tuning appeared first on MarkTechPost.
Meta AI Just Released DINOv3: A State-of-the-Art Computer Vision Model Trained with Self-Supervised Learning, Generating High-Resolution Image Features
Meta AI has just released DINOv3, a breakthrough self-supervised computer vision model that sets new standards for versatility and accuracy across dense prediction tasks, all without the need for labeled data.DINOv3 employs self-supervised learning (SSL) at an unprecedented scale, training on 1.7 billion images with a 7 billion parameter architecture.For the first time, […]
Top 12 API Testing Tools For 2025
API testing is a critical part of modern software development, ensuring that digital services remain secure, reliable, and fast.As APIs grow ever more vital across cloud, mobile, enterprise, and microservices ecosystems, the tools to test them must evolve to meet both technical and business needs.Here’s a well-researched guide to the top 12 API […]
Microsoft Releases POML (Prompt Orchestration Markup Language): Bringing Modularity and Scalability to LLM Prompts
Prompt engineering has become foundational in the development of advanced applications powered by Large Language Models (LLMs).As prompts have grown in complexity—incorporating dynamic components, multiple roles, structured data, and varied output formats—the limitations of unstructured text approaches have become evident.Microsoft released Prompt Orchestration Markup Language (POML), a novel open-source framework designed to bring […]
ByteDance Unveils ToolTrain: A New Tool-Integrated Reinforcement Learning RL Framework that Redefines Repo Deep Search
Issue localization involves identifying exact code locations that require modification to fix software problems, a process that often demands significant manual effort from developers, especially in large repositories.LLM-based agents enable language models to use various tools for dynamic […]The post ByteDance Unveils ToolTrain: A New Tool-Integrated Reinforcement Learning RL Framework that Redefines Repo Deep Search appeared first on MarkTechPost.
Top 10 AI Agent and Agentic AI News Blogs (2025 Update)
In the rapidly evolving field of agentic AI and AI Agents, staying informed is essential.Here’s a comprehensive, up-to-date list of the Top 10 AI Agent and Agentic AI News Blogs (2025 Update)—from industry leaders to academic voices—offering insights, tutorials, and reviews focused on AI agents and Agentic AI in 2025.The post Top 10 AI Agent and Agentic AI News Blogs (2025 Update) appeared first on MarkTechPost.
An Implementation Guide to Build a Modular Conversational AI Agent with Pipecat and HuggingFace
In this tutorial, we explore how we can build a fully functional conversational AI agent from scratch using the Pipecat framework.We walk through setting up a Pipeline that links together custom FrameProcessor classes, one for handling user input and generating responses with a HuggingFace model, and another for formatting and displaying the conversation flow.The post An Implementation Guide to Build a Modular Conversational AI Agent with Pipecat and HuggingFace appeared first on MarkTechPost.
Want the Latest AI Agent and Agentic AI News? These 10 Websites Are a Must-Visit! (2025 Update)
In the rapidly evolving field of agentic AI and AI Agents, staying informed is essential.Here’s a comprehensive, up-to-date list of the top blogs and websites—from industry leaders to academic voices—offering insights, tutorials, and reviews focused on AI agents and Agentic AI in 2025.These 10 Websites Are a Must-Visit!
Why Docker Matters for Artificial Intelligence AI Stack: Reproducibility, Portability, and Environment Parity
Artificial intelligence and machine learning workflows are notoriously complex, involving fast-changing code, heterogeneous dependencies, and the need for rigorously repeatable results.By approaching the problem from basic principles—what does AI actually need to be reliable, collaborative, and scalable—we find that container technologies like Docker are not a convenience, but a necessity for modern ML practitioners.The post Why Docker Matters for Artificial Intelligence AI Stack: Reproducibility, Portability, and Environment Parity appeared first on MarkTechPost.
Mistral AI Unveils Mistral Medium 3.1: Enhancing AI with Superior Performance and Usability
Mistral AI has introduced Mistral Medium 3.1, setting new standards in multimodal intelligence, enterprise readiness, and cost-efficiency for large language models (LLMs).Building on its rapidly expanding AI, Mistral continues to position itself as a European leader, pushing forward with frontier-class capabilities while breaking cost and deployment barriers.The post Mistral AI Unveils Mistral Medium 3.1: Enhancing AI with Superior Performance and Usability appeared first on MarkTechPost.
Nebius AI Advances Open-Weight LLMs Through Reinforcement Learning for Capable SWE Agents
The landscape of software engineering automation is evolving rapidly, driven by advances in Large Language Models (LLMs).However, most approaches to training capable agents rely on proprietary models or costly teacher-based methods, leaving open-weight LLMs with limited capabilities in real-world scenarios.A team of researchers from Nebius AI and Humanoid introduced a reinforcement learning framework […]
NVIDIA AI Releases ProRLv2: Advancing Reasoning in Language Models with Extended Reinforcement Learning RL
ProRLv2 is the latest version of NVIDIA’s Prolonged Reinforcement Learning (ProRL), designed specifically to push the boundaries of reasoning in large language models (LLMs).By scaling reinforcement learning (RL) steps from 2,000 up to 3,000, ProRLv2 systematically tests how extended RL can unlock new solution spaces, creativity, and high-level reasoning that were […]The post NVIDIA AI Releases ProRLv2: Advancing Reasoning in Language Models with Extended Reinforcement Learning RL appeared first on MarkTechPost.
Meet LEANN: The Tiniest Vector Database that Democratizes Personal AI with Storage-Efficient Approximate Nearest Neighbor (ANN) Search Index
Embedding-based search outperforms traditional keyword-based methods across various domains by capturing semantic similarity using dense vector representations and approximate nearest neighbor (ANN) search.However, the ANN data structure brings excessive storage overhead, often 1.5 to 7 times the size of the original raw data.The post Meet LEANN: The Tiniest Vector Database that Democratizes Personal AI with Storage-Efficient Approximate Nearest Neighbor (ANN) Search Index appeared first on MarkTechPost.
Zhipu AI Releases GLM-4.5V: Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Zhipu AI has officially released and open-sourced GLM-4.5V, a next-generation vision-language model (VLM) that significantly advances the state of open multimodal AI.Key Features and Design Innovations […]The post Zhipu AI Releases GLM-4.5V: Versatile Multimodal Reasoning with Scalable Reinforcement Learning appeared first on MarkTechPost.
Case Studies: Real-World Applications of Context Engineering
Context engineering has become a transformative force in moving from experimental AI demos to robust, production-grade systems across various industries.Below are distilled examples and evidence of real-world impact: 1. Insurance: Five Sigma & Agentic Underwriting 2.The post Case Studies: Real-World Applications of Context Engineering appeared first on MarkTechPost.
NVIDIA AI Introduces End-to-End AI Stack, Cosmos Physical AI Models and New Omniverse Libraries for Advanced Robotics
Nvidia made major waves at SIGGRAPH 2025 by unveiling a suite of new Cosmos world models, robust simulation libraries, and cutting-edge infrastructure—all designed to accelerate the next era of physical AI for robotics, autonomous vehicles, and industrial applications.Let’s break down the technological details, what this means for developers, and why it matters to the […]The post NVIDIA AI Introduces End-to-End AI Stack, Cosmos Physical AI Models and New Omniverse Libraries for Advanced Robotics appeared first on MarkTechPost.
Building a Secure and Memory-Enabled Cipher Workflow for AI Agents with Dynamic LLM Selection and API Integration
In this tutorial, we walk through building a compact but fully functional Cipher-based workflow.We start by securely capturing our Gemini API key in the Colab UI without exposing it in code.We then implement a dynamic LLM selection function that can automatically switch between OpenAI, Gemini, or Anthropic based on which API key is […]
NuMind AI Releases NuMarkdown-8B-Thinking: A Reasoning Breakthrough in OCR and Document-to-Markdown Conversion
NuMind AI has officially released NuMarkdown-8B-Thinking, an open-source (MIT License) reasoning OCR Vision-Language Model (VLM) that redefines how complex documents are digitized and structured.Unlike traditional OCR systems, NuMarkdown-8B-Thinking doesn’t just extract text—it thinks about a document’s layout, structure, and formatting before generating a precise, ready-to-use Markdown file.This makes it the first reasoning VLM […]
Genie Envisioner: A Unified Video-Generative Platform for Scalable, Instruction-Driven Robotic Manipulation
Embodied AI agents that can perceive, think, and act in the real world mark a key step toward the future of robotics.A central challenge is building scalable, reliable robotic manipulation, the skill of deliberately interacting with and controlling objects through selective contact.The post Genie Envisioner: A Unified Video-Generative Platform for Scalable, Instruction-Driven Robotic Manipulation appeared first on MarkTechPost.
The Best Chinese Open Agentic/Reasoning Models (2025): Expanded Review, Comparative Insights & Use Cases
China continues to set the pace in open-source large-language-model innovation, especially for agentic architectures and deep reasoning.Here is a comprehensive, up-to-date guide to the best Chinese open agentic/reasoning models, expanded with the newest and most influential entrants.1. Kimi K2 (Moonshot AI) 2.
The Complete Guide to DeepSeek-R1-0528 Inference Providers: Where to Run the Leading Open-Source Reasoning Model
DeepSeek-R1-0528 has emerged as a groundbreaking open-source reasoning model that rivals proprietary alternatives like OpenAI’s o1 and Google’s Gemini 2.5 Pro.With its impressive 87.5% accuracy on AIME 2025 tests and significantly lower costs, it’s become the go-to choice for developers and enterprises seeking powerful AI reasoning capabilities.This comprehensive guide covers all the major […]
Building an Advanced Portfolio Analysis and Market Intelligence Tool with OpenBB
In this tutorial, we dive deep into the advanced capabilities of OpenBB to perform comprehensive portfolio analysis and market intelligence.We start by constructing a tech-focused portfolio, fetching historical market data, and computing key performance metrics.We then explore advanced technical indicators, sector-level performance, market sentiment, and correlation-based risk analysis.
AI-Driven Antitrust and Competition Law: Algorithmic Collusion, Self-Learning Pricing Tools, and Legal Challenges in the US and EU
AI in Market Economics and Pricing Algorithms AI-driven pricing models, particularly those utilizing reinforcement learning (RL), can lead to outcomes resembling traditional collusion, fundamentally altering market dynamics.Unlike human-set strategies in oligopoly models, AI agents, like Q-learning, autonomously learn pricing strategies from data, often resulting in supra-competitive pricing due to agents’ ability to detect rivals’ […]The post AI-Driven Antitrust and Competition Law: Algorithmic Collusion, Self-Learning Pricing Tools, and Legal Challenges in the US and EU appeared first on MarkTechPost.
Using RouteLLM to Optimize LLM Usage
RouteLLM is a flexible framework for serving and evaluating LLM routers, designed to maximize performance while minimizing cost.Key features: In this tutorial, we’ll walk through how to: Installing the dependencies Loading OpenAI API Key To get an OpenAI API key, visit https://platform.openai.com/settings/organization/api-keys and generate a new key.The post Using RouteLLM to Optimize LLM Usage appeared first on MarkTechPost.
From 100,000 to Under 500 Labels: How Google AI Cuts LLM Training Data by Orders of Magnitude
Google Research has unveiled a groundbreaking method for fine-tuning large language models (LLMs) that slashes the amount of required training data by up to 10,000x, while maintaining or even improving model quality.This approach centers on active learning and focusing expert labeling efforts on the most informative examples—the “boundary cases” where model uncertainty peaks.The post From 100,000 to Under 500 Labels: How Google AI Cuts LLM Training Data by Orders of Magnitude appeared first on MarkTechPost.
AI Agent Trends of 2025: A Transformative Landscape
The year 2025 marks a defining moment in the evolution of artificial intelligence, ushering in an era where agentic systems—autonomous AI agents capable of complex reasoning and coordinated action—are transforming enterprise workflows, research, software development, and day-to-day user experiences.This articles focuses on five core AI agent trends for 2025: Agentic RAG, Voice Agents, AI […]The post AI Agent Trends of 2025: A Transformative Landscape appeared first on MarkTechPost.
9 Agentic AI Workflow Patterns Transforming AI Agents in 2025
AI agents are at a pivotal moment: simply calling a language model is no longer enough for production-ready solutions.In 2025, intelligent automation depends on orchestrated, agentic workflows—modular coordination blueprints that transform isolated AI calls into systems of autonomous, adaptive, and self-improving agents.Here’s how nine workflow patterns can unlock the next generation of scalable, […]
Building an Advanced PaperQA2 Research Agent with Google Gemini for Scientific Literature Analysis
In this tutorial, we walk through building an advanced PaperQA2 AI Agent powered by Google’s Gemini model, designed specifically for scientific literature analysis.We set up the environment in Google Colab/Notebook, configure the Gemini API, and integrate it seamlessly with PaperQA2 to process and query multiple research papers.The post Building an Advanced PaperQA2 Research Agent with Google Gemini for Scientific Literature Analysis appeared first on MarkTechPost.
Graph-R1: An Agentic GraphRAG Framework for Structured, Multi-Turn Reasoning with Reinforcement Learning
Introduction Large Language Models (LLMs) have set new benchmarks in natural language processing, but their tendency for hallucination—generating inaccurate outputs—remains a critical issue for knowledge-intensive applications.Retrieval-Augmented Generation (RAG) frameworks attempt to solve this by incorporating external knowledge into language generation.The post Graph-R1: An Agentic GraphRAG Framework for Structured, Multi-Turn Reasoning with Reinforcement Learning appeared first on MarkTechPost.
Mixture-of-Agents (MoA): A Breakthrough in LLM Performance
The Mixture-of-Agents (MoA) architecture is a transformative approach for enhancing large language model (LLM) performance, especially on complex, open-ended tasks where a single model can struggle with accuracy, reasoning, or domain specificity.How the Mixture-of-Agents Architecture Works Why Is MoA Superior to Single-Model LLMs?The post Mixture-of-Agents (MoA): A Breakthrough in LLM Performance appeared first on MarkTechPost.
FAQs: Everything You Need to Know About AI Agents in 2025
What is an AI agent (2025 definition)?An AI agent is a goal-directed loop built around a capable model (often multimodal) and a set of tools/actuators.The post FAQs: Everything You Need to Know About AI Agents in 2025 appeared first on MarkTechPost.
Technical Deep Dive: Automating LLM Agent Mastery for Any MCP Server with MCP- RL and ART
Introduction Empowering large language models (LLMs) to fluidly interact with dynamic, real-world environments is a new frontier for AI engineering.The Model Context Protocol (MCP) specification offers a standardized gateway through which LLMs can interface with arbitrary external systems—APIs, file systems, databases, applications, or tools—without needing custom glue code or brittle prompt hacks each time.The post Technical Deep Dive: Automating LLM Agent Mastery for Any MCP Server with MCP- RL and ART appeared first on MarkTechPost.
Alibaba Qwen Unveils Qwen3-4B-Instruct-2507 and Qwen3-4B-Thinking-2507: Refreshing the Importance of Small Language Models
Smaller Models with Smarter Performance and 256K Context Support Alibaba’s Qwen team has introduced two powerful additions to its small language model lineup: Qwen3-4B-Instruct-2507 and Qwen3-4B-Thinking-2507.Despite having only 4 billion parameters, these models deliver exceptional capabilities across general-purpose and expert-level tasks while running efficiently on consumer-grade hardware.Both are designed with native 256K token […]
VL-Cogito: Advancing Multimodal Reasoning with Progressive Curriculum Reinforcement Learning
Multimodal reasoning, where models integrate and interpret information from multiple sources such as text, images, and diagrams, is a frontier challenge in AI.VL-Cogito is a state-of-the-art Multimodal Large Language Model (MLLM) proposed by DAMO Academy (Alibaba Group) and partners, introducing a robust reinforcement learning pipeline that fundamentally upgrades the reasoning skills of large models […]The post VL-Cogito: Advancing Multimodal Reasoning with Progressive Curriculum Reinforcement Learning appeared first on MarkTechPost.
A Developer’s Guide to OpenAI’s GPT-5 Model Capabilities
In this tutorial, we’ll explore the new capabilities introduced in OpenAI’s latest model, GPT-5.The update brings several powerful features, including the Verbosity parameter, Free-form Function Calling, Context-Free Grammar (CFG), and Minimal Reasoning.We’ll look at what they do and how to use them in practice.
Cloudflare vs Perplexity: The Battle Over AI Web Scraping Heats Up
Reading through Cloudflare’s detailed exposé and the extensive media coverage, the controversy surrounding Perplexity AI’s web scraping practices is deeper — and more polarizing — than it first appears.Cloudflare accuses Perplexity of systematically ignoring website blocks and masking its identity to scrape data from sites that have opted out, raising serious questions about ethics, […]The post Cloudflare vs Perplexity: The Battle Over AI Web Scraping Heats Up appeared first on MarkTechPost.
A Code Implementation to Build a Multi-Agent Research System with OpenAI Agents, Function Tools, Handoffs, and Session Memory
In this tutorial, we begin by showcasing the power of OpenAI Agents as the driving force behind our multi-agent research system.We set up our Colab environment with the OpenAI API key, installed the OpenAI Agents SDK, and then defined custom function tools, web_search, analyze_data, and save_research, to harness the agents’ capabilities.The post A Code Implementation to Build a Multi-Agent Research System with OpenAI Agents, Function Tools, Handoffs, and Session Memory appeared first on MarkTechPost.
Meta CLIP 2: The First Contrastive Language-Image Pre-training (CLIP) Trained with Worldwide Image-Text Pairs from Scratch
Contrastive Language-Image Pre-training (CLIP) has become important for modern vision and multimodal models, enabling applications such as zero-shot image classification and serving as vision encoders in MLLMs.However, most CLIP variants, including Meta CLIP, are limited to English-only data curation, ignoring a significant amount of non-English content from the worldwide web.The post Meta CLIP 2: The First Contrastive Language-Image Pre-training (CLIP) Trained with Worldwide Image-Text Pairs from Scratch appeared first on MarkTechPost.
What is a Proxy Server? A Technical Deep Dive with Trends and Top Proxy Servers (2025 Edition)
Introduction A proxy server is a vital intermediary between clients and destination servers, facilitating both security and speed in the modern internet.In 2025, with digital privacy, enterprise security, and data-driven automation to the forefront, proxy servers are indispensable for individuals and organizations.The global web proxy market is projected to reach $50 billion by […]
Proxy Servers Explained: Types, Use Cases & Trends in 2025 [Technical Deep Dive]
Introduction A proxy server is a vital intermediary between clients and destination servers, facilitating both security and speed in the modern internet.In 2025, with digital privacy, enterprise security, and data-driven automation to the forefront, proxy servers are indispensable for individuals and organizations.The global web proxy market is projected to reach $50 billion by […]
Meet CoAct-1: A Novel Multi-Agent System that Synergistically Combines GUI-based Control with Direct Programmatic Execution
A Team of researchers from USC, Salesforce AI and University of Washington have introduced CoAct-1, a pioneering multi-agent computer-using agent (CUA) that marks a significant leap in autonomous computer operation.By elevating coding to a first-class action—on par with traditional GUI manipulation—CoAct-1 overcomes longstanding challenges of efficiency and reliability in complex, long-horizon computer tasks.The post Meet CoAct-1: A Novel Multi-Agent System that Synergistically Combines GUI-based Control with Direct Programmatic Execution appeared first on MarkTechPost.
NVIDIA XGBoost 3.0: Training Terabyte-Scale Datasets with Grace Hopper Superchip
NVIDIA has unveiled a major milestone in scalable machine learning: XGBoost 3.0, now able to train gradient-boosted decision tree (GBDT) models from gigabytes up to 1 terabyte (TB) on a single GH200 Grace Hopper Superchip.The breakthrough enables companies to process immense datasets for applications like fraud detection, credit risk modeling, and algorithmic trading, simplifying […]The post NVIDIA XGBoost 3.0: Training Terabyte-Scale Datasets with Grace Hopper Superchip appeared first on MarkTechPost.
A Coding Implementation to Advanced LangGraph Multi-Agent Research Pipeline for Automated Insights Generation
We build an advanced LangGraph multi-agent system that leverages Google’s free-tier Gemini model for end-to-end research workflows.In this tutorial, we start by installing the necessary libraries, LangGraph, LangChain-Google-GenAI, and LangChain-Core, then walk through defining a structured state, simulating research and analysis tools, and wiring up three specialized agents: Research, Analysis, and Report.The post A Coding Implementation to Advanced LangGraph Multi-Agent Research Pipeline for Automated Insights Generation appeared first on MarkTechPost.
OpenAI Just Released GPT-5: The Smartest, Fastest, and Most Useful OpenAI Model
OpenAI just released GPT-5, marking a substantial leap in generative AI, introducing advanced capabilities that cater to both general and highly specialized tasks.This article provides a deep technical dive into GPT-5’s architecture, new features, performance improvements, and the strategic implications for developers, enterprises, and the AI ecosystem.The post OpenAI Just Released GPT-5: The Smartest, Fastest, and Most Useful OpenAI Model appeared first on MarkTechPost.
Google AI Releases DeepPolisher: A New Deep Learning Tool that Improves the Accuracy of Genome Assemblies by Precisely Correcting Base-Level Errors
Google AI, in collaboration with the UC Santa Cruz Genomics Institute, has introduced DeepPolisher, a cutting-edge deep learning tool designed to substantially improve the accuracy of genome assemblies by correcting base-level errors.Its notable efficacy was recently demonstrated in advancing the Human Pangenome Reference, a major milestone in genomics research.The post Google AI Releases DeepPolisher: A New Deep Learning Tool that Improves the Accuracy of Genome Assemblies by Precisely Correcting Base-Level Errors appeared first on MarkTechPost.
Alibaba Introduces Group Sequence Policy Optimization (GSPO): An Efficient Reinforcement Learning Algorithm that Powers the Qwen3 Models
Reinforcement learning (RL) plays a crucial role in scaling language models, enabling them to solve complex tasks such as competition-level mathematics and programming through deeper reasoning.However, achieving stable and reliable training dynamics is a challenge when scaling RL with larger computational resources.The post Alibaba Introduces Group Sequence Policy Optimization (GSPO): An Efficient Reinforcement Learning Algorithm that Powers the Qwen3 Models appeared first on MarkTechPost.
MoE Architecture Comparison: Qwen3 30B-A3B vs. GPT-OSS 20B
This article provides a technical comparison between two recently released Mixture-of-Experts (MoE) transformer models: Alibaba’s Qwen3 30B-A3B (released April 2025) and OpenAI’s GPT-OSS 20B (released August 2025).Both models represent distinct approaches to MoE architecture design, balancing computational efficiency with performance across different deployment scenarios.The post MoE Architecture Comparison: Qwen3 30B-A3B vs. GPT-OSS 20B appeared first on MarkTechPost.
Google DeepMind Introduces Genie 3: A General Purpose World Model that can Generate an Unprecedented Diversity of Interactive Environments
Google DeepMind has announced Genie 3, a revolutionary AI system capable of generating interactive, physically consistent virtual worlds from simple text prompts.This marks a substantial leap in the field of world models—a class of AI designed to understand and simulate environments, not merely render them, but produce dynamic spaces you can move through and […]The post Google DeepMind Introduces Genie 3: A General Purpose World Model that can Generate an Unprecedented Diversity of Interactive Environments appeared first on MarkTechPost.
Model Context Protocol (MCP) FAQs: Everything You Need to Know in 2025
The Model Context Protocol (MCP) has rapidly become a foundational standard for connecting large language models (LLMs) and other AI applications with the systems and data they need to be genuinely useful.In 2025, MCP is widely adopted, reshaping how enterprises, developers, and end-users experience AI-powered automation, knowledge retrieval, and real-time decision making.The post Model Context Protocol (MCP) FAQs: Everything You Need to Know in 2025 appeared first on MarkTechPost.
This AI Paper Introduces C3: A Bilingual Benchmark Dataset and Evaluation Framework for Complex Spoken Dialogue Modeling
Spoken Dialogue Models (SDMs) are at the frontier of conversational AI, enabling seamless spoken interactions between humans and machines.Yet, as SDMs become integral to digital assistants, smart devices, and customer service bots, evaluating their true ability to handle the real-world intricacies of human dialogue remains a significant challenge.A new research paper from China […]
A Coding Implementation to Build a Self-Adaptive Goal-Oriented AI Agent Using Google Gemini and the SAGE Framework
In this tutorial, we dive into building an advanced AI agent system based on the SAGE framework, Self-Adaptive Goal-oriented Execution, using Google’s Gemini API.We walk through each core component of the framework: Self-Assessment, Adaptive Planning, Goal-oriented Execution, and Experience Integration.By combining these, we aim to create an intelligent, self-improving agent that can deconstruct […]
OpenAI Just Released the Hottest Open-Weight LLMs: gpt-oss-120B (Runs on a High-End Laptop) and gpt-oss-20B (Runs on a Phone)
OpenAI has just sent seismic waves through the AI world: for the first time since GPT-2 hit the scene in 2019, the company is releasing not one, but TWO open-weight language models.Meet gpt-oss-120b and gpt-oss-20b—models that anyone can download, inspect, fine-tune, and run on their own hardware.The post OpenAI Just Released the Hottest Open-Weight LLMs: gpt-oss-120B (Runs on a High-End Laptop) and gpt-oss-20B (Runs on a Phone) appeared first on MarkTechPost.
Too Much Thinking Can Break LLMs: Inverse Scaling in Test-Time Compute
Recent advances in large language models (LLMs) have encouraged the idea that letting models “think longer” during inference usually improves their accuracy and robustness.Practices like chain-of-thought prompting, step-by-step explanations, and increasing “test-time compute” are now standard techniques in the field.However, the Anthropic-led study “Inverse Scaling in Test-Time Compute” delivers a compelling counterpoint: in […]
A Coding Guide to Build a Scalable Multi-Agent System with Google ADK
In this tutorial, we explore the advanced capabilities of Google’s Agent Development Kit (ADK) by building a multi-agent system equipped with specialized roles and tools.We guide you through creating agents tailored for tasks such as web research, mathematical computation, data analysis, and content creation.By integrating Google Search, asynchronous execution, and modular architecture, we […]
Apple Researchers Introduce FastVLM: Achieving State-of-the-Art Resolution-Latency-Accuracy Trade-off in Vision Language Models
Vision Language Models (VLMs) allow both text inputs and visual understanding.However, image resolution is crucial for VLM performance for processing text and chart-rich data.Increasing image resolution creates significant challenges.
Is Vibe Coding Safe for Startups? A Technical Risk Audit Based on Real-World Use Cases
With limited engineering resources, many are exploring AI-driven development environments—collectively referred to as “Vibe Coding”—as a shortcut to launch minimum viable products (MVPs) quickly.These platforms promise seamless code generation from natural language prompts, AI-powered […]The post Is Vibe Coding Safe for Startups?
MiroMind-M1: Advancing Open-Source Mathematical Reasoning via Context-Aware Multi-Stage Reinforcement Learning
Large language models (LLMs) have recently demonstrated remarkable progress in multi-step reasoning, establishing mathematical problem-solving as a rigorous benchmark for assessing advanced capabilities.While proprietary models like GPT-4o and Claude Sonnet 4 lead performance, their closed-source nature impedes transparency and reproducibility.Addressing these gaps, MiroMind AI Released the MiroMind-M1 series, a fully open-source pipeline—spanning datasets, […]
Rubrics as Rewards (RaR): A Reinforcement Learning Framework for Training Language Models with Structured, Multi-Criteria Evaluation Signals
Reinforcement Learning with Verifiable Rewards (RLVR) allows LLMs to perform complex reasoning on tasks with clear, verifiable outcomes, with strong performance in mathematics and coding.However, many real-world scenarios lack such explicit verifiable answers, posing a challenge for training models without direct reward signals.The post Rubrics as Rewards (RaR): A Reinforcement Learning Framework for Training Language Models with Structured, Multi-Criteria Evaluation Signals appeared first on MarkTechPost.
Building a Comprehensive AI Agent Evaluation Framework with Metrics, Reports, and Visual Dashboards
In this tutorial, we walk through the creation of an advanced AI evaluation framework designed to assess the performance, safety, and reliability of AI agents.We begin by implementing a comprehensive AdvancedAIEvaluator class that leverages multiple evaluation metrics, such as semantic similarity, hallucination detection, factual accuracy, toxicity, and bias analysis.Using Python’s object-oriented programming, multithreading […]
Implementing Self-Refine Technique Using Large Language Models LLMs
This tutorial demonstrates how to implement the Self-Refine technique using Large Language Models (LLMs) with Mirascope, a powerful framework for building structured prompt workflows.Self-Refine is a prompt engineering strategy where the model evaluates its own output, generates feedback, and iteratively improves its response based on that feedback.The post Implementing Self-Refine Technique Using Large Language Models LLMs appeared first on MarkTechPost.
It’s Okay to Be “Just a Wrapper”: Why Solution-Driven AI Companies Win
In today’s rapidly evolving AI landscape, many founders and observers find themselves preoccupied with the idea that successful startups must build foundational technology from scratch.Nowhere is this narrative more prevalent than among those launching so-called “LLM wrappers” — companies whose core offering builds on top of large language models (LLMs) like GPT or Claude.The post It’s Okay to Be “Just a Wrapper”: Why Solution-Driven AI Companies Win appeared first on MarkTechPost.
Safeguarding Agentic AI Systems: NVIDIA’s Open-Source Safety Recipe
As large language models (LLMs) evolve from simple text generators to agentic systems —able to plan, reason, and autonomously act—there is a significant increase in both their capabilities and associated risks.Enterprises are rapidly adopting agentic AI for automation, but this trend exposes organizations to new challenges: goal misalignment, prompt injection, unintended behaviors, data leakage, […]The post Safeguarding Agentic AI Systems: NVIDIA’s Open-Source Safety Recipe appeared first on MarkTechPost.
9 Open Source Cursor Alternatives You Should Use in 2025
The demand for AI-powered coding tools has exploded—with open-source alternatives now rivaling commercial solutions like Cursor in features, flexibility, and privacy.Zed Zed is a high-performance, open-source code editor designed for both humans and AI collaboration.Built by the […]
Amazon Develops an AI Architecture that Cuts Inference Time 30% by Activating Only Relevant Neurons
Amazon researchers developed a new AI architecture that cuts inference time by 30% by selecting only task-relevant neurons, similar to how the brain uses specialized regions for specific tasks.This breakthrough approach addresses one of the biggest challenges facing large AI models: the computational expense and latency associated with activating every neuron for every request, […]The post Amazon Develops an AI Architecture that Cuts Inference Time 30% by Activating Only Relevant Neurons appeared first on MarkTechPost.
Microsoft Edge Launches Copilot Mode to Redefine Web Browsing for the AI Era
Microsoft has taken a major leap into the future of web browsing with the launch of Copilot Mode in Edge, positioning it as the company’s first real step toward an AI-native browser.This marks a pivotal moment not just for Edge, but for the entire concept of what a browser can be in the era […]The post Microsoft Edge Launches Copilot Mode to Redefine Web Browsing for the AI Era appeared first on MarkTechPost.
Creating a Knowledge Graph Using an LLM
In this tutorial, we’ll show how to create a Knowledge Graph from an unstructured document using an LLM.While traditional NLP methods have been used for extracting entities and relationships, Large Language Models (LLMs) like GPT-4o-mini make this process more accurate and context-aware.LLMs are especially useful when working with messy, unstructured data.
Zhipu AI Just Released GLM-4.5 Series: Redefining Open-Source Agentic AI with Hybrid Reasoning
The landscape of AI foundation models is evolving rapidly, but few entries have been as significant in 2025 as the arrival of Z.ai’s GLM-4.5 series: GLM-4.5 and its lighter sibling GLM-4.5-Air.Unveiled by Zhipu AI, these models set remarkably high standards for unified agentic capabilities and open access, aiming to bridge the gap between reasoning, […]The post Zhipu AI Just Released GLM-4.5 Series: Redefining Open-Source Agentic AI with Hybrid Reasoning appeared first on MarkTechPost.
The U.S. White House Releases AI Playbook: A Bold Strategy to Lead the Global AI Race
The White House just released the U.S. AI Playbook—formally titled “America’s AI Action Plan”—a sweeping, high-impact federal strategy that clarifies one thing: the United States is going all in on artificial intelligence.Whether you’re in Silicon Valley, leading a Fortune 500, or managing a critical government agency, the message is unambiguous: scale AI fast, dismantle […]The post The U.S. White House Releases AI Playbook: A Bold Strategy to Lead the Global AI Race appeared first on MarkTechPost.
Building a Context-Aware Multi-Agent AI System Using Nomic Embeddings and Gemini LLM
In this tutorial, we walk through the complete implementation of an advanced AI agent system powered by Nomic Embeddings and Google’s Gemini.We design the architecture from the ground up, integrating semantic memory, contextual reasoning, and multi-agent orchestration into a single intelligent framework.Using LangChain, Faiss, and LangChain-Nomic, we equip our agents with the ability […]
VLM2Vec-V2: A Unified Computer Vision Framework for Multimodal Embedding Learning Across Images, Videos, and Visual Documents
Embedding models act as bridges between different data modalities by encoding diverse multimodal information into a shared dense representation space.However, existing multimodal embedding models are trained on datasets such as MMEB and M-BEIR, with most focus only […]The post VLM2Vec-V2: A Unified Computer Vision Framework for Multimodal Embedding Learning Across Images, Videos, and Visual Documents appeared first on MarkTechPost.
Key Factors That Drive Successful MCP Implementation and Adoption
The Model Context Protocol (MCP) is changing how intelligent agents interact with backend services, applications, and data.A successful MCP implementation project hinges on much more than writing protocol-compliant code.Systematic adoption involves architecture, security, user experience, and operational rigor.
NVIDIA AI Dev Team Releases Llama Nemotron Super v1.5: Setting New Standards in Reasoning and Agentic AI
The landscape of artificial intelligence continues to evolve rapidly, with breakthroughs that push the boundaries of what models can achieve in reasoning, efficiency, and application versatility.The latest release from NVIDIA—the Llama Nemotron Super v1.5—represents a remarkable leap in both performance and usability, especially for agentic and reasoning-intensive tasks.The post NVIDIA AI Dev Team Releases Llama Nemotron Super v1.5: Setting New Standards in Reasoning and Agentic AI appeared first on MarkTechPost.
Building a Multi-Node Graph-Based AI Agent Framework for Complex Task Automation
In this tutorial, we guide you through the development of an advanced Graph Agent framework, powered by the Google Gemini API.Our goal is to build intelligent, multi-step agents that execute tasks through a well-defined graph structure of interconnected nodes.The post Building a Multi-Node Graph-Based AI Agent Framework for Complex Task Automation appeared first on MarkTechPost.
Why Context Matters: Transforming AI Model Evaluation with Contextualized Queries
Language model users often ask questions without enough detail, making it hard to understand what they want.Current evaluation methods often […]The post Why Context Matters: Transforming AI Model Evaluation with Contextualized Queries appeared first on MarkTechPost.
GenSeg: Generative AI Transforms Medical Image Segmentation in Ultra Low-Data Regimes
Medical image segmentation is at the heart of modern healthcare AI, enabling crucial tasks such as disease detection, progression monitoring, and personalized treatment planning.In disciplines like dermatology, radiology, and cardiology, the need for precise segmentation—assigning a class to every pixel in a medical image—is acute.Yet, the main obstacle remains: the scarcity of large, expertly […]
REST: A Stress-Testing Framework for Evaluating Multi-Problem Reasoning in Large Reasoning Models
However, current evaluation approaches primarily focus on single-question testing, which reveals significant limitations.This article introduces REST (Reasoning Evaluation through Simultaneous Testing) — a novel multi-problem stress-testing framework designed to push LRMs beyond isolated problem-solving […]The post REST: A Stress-Testing Framework for Evaluating Multi-Problem Reasoning in Large Reasoning Models appeared first on MarkTechPost.
URBAN-SIM: Advancing Autonomous Micromobility with Scalable Urban Simulation
Micromobility solutions—such as delivery robots, mobility scooters, and electric wheelchairs—are rapidly transforming short-distance urban travel.Despite their growing popularity as flexible, eco-friendly transport alternatives, most micromobility devices still rely heavily on human control.The post URBAN-SIM: Advancing Autonomous Micromobility with Scalable Urban Simulation appeared first on MarkTechPost.
How Memory Transforms AI Agents: Insights and Leading Solutions in 2025
The importance of memory in AI agents cannot be overstated.As artificial intelligence matures from simple statistical models to autonomous agents, the ability to remember, learn, and adapt becomes a foundational capability.Memory distinguishes basic reactive bots from truly interactive, context-aware digital entities capable of supporting nuanced, humanlike interactions and decision-making.
NVIDIA AI Releases GraspGen: A Diffusion-Based Framework for 6-DOF Grasping in Robotics
Robotic grasping is a cornerstone task for automation and manipulation, critical in domains spanning from industrial picking to service and humanoid robotics.Despite decades of research, achieving robust, general-purpose 6-degree-of-freedom (6-DOF) grasping remains a challenging open problem.Recently, NVIDIA unveiled GraspGen, a novel diffusion-based grasp generation framework that promises to bring state-of-the-art (SOTA) performance with unprecedented […]
Google DeepMind Introduces Aeneas: AI-Powered Contextualization and Restoration of Ancient Latin Inscriptions
The discipline of epigraphy, focused on studying texts inscribed on durable materials like stone and metal, provides critical firsthand evidence for understanding the Roman world.The field faces numerous challenges including fragmentary inscriptions, uncertain dating, diverse geographical provenance, widespread use of abbreviations, and a large and rapidly growing corpus of over 176,000 Latin inscriptions, with […]The post Google DeepMind Introduces Aeneas: AI-Powered Contextualization and Restoration of Ancient Latin Inscriptions appeared first on MarkTechPost.
Building a GPU-Accelerated Ollama LangChain Workflow with RAG Agents, Multi-Session Chat Performance Monitoring
In this tutorial, we build a GPU‑capable local LLM stack that unifies Ollama and LangChain.We install the required libraries, launch the Ollama server, pull a model, and wrap it in a custom LangChain LLM, allowing us to control temperature, token limits, and context.The post Building a GPU-Accelerated Ollama LangChain Workflow with RAG Agents, Multi-Session Chat Performance Monitoring appeared first on MarkTechPost.
RoboBrain 2.0: The Next-Generation Vision-Language Model Unifying Embodied AI for Advanced Robotics
Advancements in artificial intelligence are rapidly closing the gap between digital reasoning and real-world interaction.At the forefront of this progress is embodied AI—the field focused on enabling robots to perceive, reason, and act effectively in physical environments.The post RoboBrain 2.0: The Next-Generation Vision-Language Model Unifying Embodied AI for Advanced Robotics appeared first on MarkTechPost.
EraRAG: A Scalable, Multi-Layered Graph-Based Retrieval System for Dynamic and Growing Corpora
Large Language Models (LLMs) have revolutionized many areas of natural language processing, but they still face critical limitations when dealing with up-to-date facts, domain-specific information, or complex multi-hop reasoning.Retrieval-Augmented Generation (RAG) approaches aim to address these gaps by allowing language models to retrieve and integrate information from external sources.The post EraRAG: A Scalable, Multi-Layered Graph-Based Retrieval System for Dynamic and Growing Corpora appeared first on MarkTechPost.
FEEDER: A Pre-Selection Framework for Efficient Demonstration Selection in LLMs
LLMs have demonstrated exceptional performance across multiple tasks by utilizing few-shot inference, also known as in-context learning (ICL).The main problem lies in selecting the most representative demonstrations from large training datasets.The post FEEDER: A Pre-Selection Framework for Efficient Demonstration Selection in LLMs appeared first on MarkTechPost.
Alibaba Qwen Introduces Qwen3-MT: Next-Gen Multilingual Machine Translation Powered by Reinforcement Learning
Alibaba has introduced Qwen3-MT (qwen-mt-turbo) via Qwen API, its latest and most advanced machine translation model, designed to break language barriers with unprecedented accuracy, speed, and flexibility.Trained on trillions of multilingual tokens, Qwen3-MT supports over 92 languages—covering more than 95% of the global population.Leveraging cutting-edge architecture, reinforcement learning, and rich customization options, it delivers […]
DualDistill and Agentic-R1: How AI Combines Natural Language and Tool Use for Superior Math Problem Solving
Existing long-CoT reasoning models have achieved state-of-the-art performance in mathematical reasoning by generating reasoning trajectories with iterative self-verification and refinement.However, open-source long-CoT models depend only on natural language reasoning traces, making them computationally expensive and prone to errors without verification mechanisms.The post DualDistill and Agentic-R1: How AI Combines Natural Language and Tool Use for Superior Math Problem Solving appeared first on MarkTechPost.
Unsupervised System 2 Thinking: The Next Leap in Machine Learning with Energy-Based Transformers
Artificial intelligence research is rapidly evolving beyond pattern recognition and toward systems capable of complex, human-like reasoning.The latest breakthrough in this pursuit comes from the introduction of Energy-Based Transformers (EBTs)—a family of neural architectures specifically designed to enable “System 2 Thinking” in machines without relying on domain-specific supervision or restrictive training signals.The post Unsupervised System 2 Thinking: The Next Leap in Machine Learning with Energy-Based Transformers appeared first on MarkTechPost.
A Coding Guide to Build a Tool-Calling ReAct Agent Fusing Prolog Logic with Gemini and LangGraph
In this tutorial, we are walking through a hands-on fusion of symbolic logic and generative AI.We set up PySwip to embed a Prolog knowledge base, wrap its predicates as LangChain tools, and then wire everything into a ReAct-style agent.Along the way, we are crafting family-relationship rules, mathematical predicates like factorial, and list utilities, […]
GitHub Introduces Vibe Coding with Spark: Revolutionizing Intelligent App Development in a Flash
GitHub has introduced Spark, a groundbreaking addition to its suite of developer tools, aimed at revolutionizing the way full-stack intelligent applications are built and deployed.With Spark, available in public preview for Copilot Pro+ subscribers, developers can go from idea to a fully deployed app in minutes—all using natural language prompts and without the usual […]The post GitHub Introduces Vibe Coding with Spark: Revolutionizing Intelligent App Development in a Flash appeared first on MarkTechPost.
Google Researchers Introduced LSM-2 with Adaptive and Inherited Masking (AIM): Enabling Direct Learning from Incomplete Wearable Data
Introduction Wearable devices are transforming health monitoring by enabling continuous collection of physiological and behavioral signals such as heart rate, activity, temperature, and skin conductance.However, the real-world data that these devices generate is highly prone to missingness due to sensor failures, device removal, charging, motion artifacts, battery-saving modes, and other interruptions.The post Google Researchers Introduced LSM-2 with Adaptive and Inherited Masking (AIM): Enabling Direct Learning from Incomplete Wearable Data appeared first on MarkTechPost.
7 MCP Server Best Practices for Scalable AI Integrations in 2025
Model Context Protocol (MCP) servers have fast become a backbone for scalable, secure, and agentic application integrations, especially as organizations seek to expose their services to AI-driven workflows while keeping developer experience, performance, and security intact.Here are seven data-driven best practices for building, testing, and packaging robust MCP servers.The post 7 MCP Server Best Practices for Scalable AI Integrations in 2025 appeared first on MarkTechPost.
This AI Paper Introduces PyVision: A Python-Centric Framework Where AI Writes Tools as It Thinks
Visual reasoning tasks challenge artificial intelligence models to interpret and process visual information using both perception and logical reasoning.These tasks span a wide range of applications, including medical diagnostics, visual math, symbolic puzzles, and image-based question answering.The post This AI Paper Introduces PyVision: A Python-Centric Framework Where AI Writes Tools as It Thinks appeared first on MarkTechPost.
GPT-4o Understands Text, But Does It See Clearly? A Benchmarking Study of MFMs on Vision Tasks
Multimodal foundation models (MFMs) like GPT-4o, Gemini, and Claude have shown rapid progress recently, especially in public demos.While their language skills are well studied, their true ability to understand visual information remains unclear.Most benchmarks used today focus heavily on text-based tasks, such as VQA or classification, which often reflect language strengths more than […]
SYNCOGEN: A Machine Learning Framework for Synthesizable 3D Molecular Generation Through Joint Graph and Coordinate Modeling
Introduction: The Challenge of Synthesizable Molecule Generation In modern drug discovery, generative molecular design models have greatly expanded the chemical space available to researchers, enabling rapid exploration of new compounds.Yet, a major challenge remains: many AI-generated molecules are difficult or impossible to synthesize in the laboratory, limiting their practical value in pharmaceutical and chemical development.The post SYNCOGEN: A Machine Learning Framework for Synthesizable 3D Molecular Generation Through Joint Graph and Coordinate Modeling appeared first on MarkTechPost.
A Code Implementation to Efficiently Leverage LangChain to Automate PubMed Literature Searches, Parsing, and Trend Visualization
In this tutorial, we are excited to introduce the Advanced PubMed Research Assistant, which guides you through building a streamlined pipeline for querying and analyzing biomedical literature.In this tutorial, we focus on leveraging the PubmedQueryRun tool to perform targeted searches, such as “CRISPR gene editing,” and then parse, cache, and explore those results.The post A Code Implementation to Efficiently Leverage LangChain to Automate PubMed Literature Searches, Parsing, and Trend Visualization appeared first on MarkTechPost.
Amazon Researchers Reveal Mitra: Advancing Tabular Machine Learning with Synthetic Priors
Introduction Amazon researchers have released Mitra, a cutting-edge foundation model purpose-built for tabular data.Unlike traditional approaches that tailor a bespoke model for every dataset, Mitra harnesses the power of in-context learning (ICL) and synthetic data pretraining, achieving state-of-the-art performance across tabular machine learning benchmarks.Integrated into AutoGluon 1.4, Mitra is designed to generalize robustly, offering a transformative […]
AI Guardrails and Trustworthy LLM Evaluation: Building Responsible AI Systems
Introduction: The Rising Need for AI Guardrails As large language models (LLMs) grow in capability and deployment scale, the risk of unintended behavior, hallucinations, and harmful outputs increases.The recent surge in real-world AI integrations across healthcare, finance, education, and defense sectors amplifies the demand for robust safety mechanisms.The post AI Guardrails and Trustworthy LLM Evaluation: Building Responsible AI Systems appeared first on MarkTechPost.
Qwen Releases Qwen3-Coder-480B-A35B-Instruct: Its Most Powerful Open Agentic Code Model Yet
Introduction Qwen has unveiled Qwen3-Coder-480B-A35B-Instruct, their most powerful open agentic code model released to date.With a distinctive Mixture-of-Experts (MoE) architecture and comprehensive agentic coding capabilities, Qwen3-Coder not only sets a new standard for open-source coding models but also redefines what’s possible for large-scale, autonomous developer assistance.Model Architecture and Specifications Key Features Mixture-of-Experts Design The […]
Are We Ready for Production-Grade Apps With Vibe Coding? A Look at the Replit Fiasco
The Allure and The Hype Vibe coding—constructing applications through conversational AI rather than writing traditional code—has surged in popularity, with platforms like Replit promoting themselves as safe havens for this trend.The promise: democratized software creation, fast development cycles, and accessibility for those with little to no coding background.A Look at the Replit Fiasco appeared first on MarkTechPost.
Building a Versatile Multi‑Tool AI Agent Using Lightweight Hugging Face Models
In this tutorial, we begin by setting up a compact yet capable AI agent that runs smoothly, leveraging Hugging Face transformers.We integrate dialog generation, question‑answering, sentiment analysis, web search stubs, weather look‑ups, and a safe calculator into a single Python class.As we progress, we install only the essential libraries, load lightweight models that respect […]
Context Engineering for AI Agents: Key Lessons from Manus
Building effective AI agents means more than just picking a powerful language model.As the Manus project discovered, how you design and manage the “context” – the information the AI processes to make decisions – is paramount.This “context engineering” directly impacts an agent’s speed, cost, reliability, and intelligence.
Top 15+ Most Affordable Proxy Providers 2025
The global proxy market is experiencing rapid expansion in 2025, with the industry estimated to be valued at $2.5billion and exhibiting a robust growth rate of 18% compound annual growth rate (CAGR) driven by booming demand for residential proxies, real-time data collection for AI, and the rise of cloud-based proxy services.AI-powered use cases are now […]The post Top 15+ Most Affordable Proxy Providers 2025 appeared first on MarkTechPost.
The Ultimate Guide to Vibe Coding: Benefits, Tools, and Future Trends
Introduction Vibe Coding is redefining the software landscape by harnessing artificial intelligence to make code creation faster, more intuitive, and accessible to virtually anyone.In 2025, this trend has moved from buzzword to mainstream, ushering in a new era where software projects ride on creativity and natural language—“the vibe”—not just technical know-how.The post The Ultimate Guide to Vibe Coding: Benefits, Tools, and Future Trends appeared first on MarkTechPost.
Meet WrenAI: The Open-Source AI Business Intelligence Agent for Natural Language Data Analytics
WrenAI is an open-source Generative Business Intelligence (GenBI) agent developed by Canner, designed to enable seamless, natural-language interaction with structured data.It targets both technical and non-technical teams, providing the tools to query, analyze, and visualize data without writing SQL.All capabilities and integrations are verified against the official documentation and latest releases.
This AI Paper from Alibaba Introduces Lumos-1: A Unified Autoregressive Video Generator Leveraging MM-RoPE and AR-DF for Efficient Spatiotemporal Modeling
Autoregressive video generation is a rapidly evolving research domain.It focuses on the synthesis of videos frame-by-frame using learned patterns of both spatial arrangements and temporal dynamics.The post This AI Paper from Alibaba Introduces Lumos-1: A Unified Autoregressive Video Generator Leveraging MM-RoPE and AR-DF for Efficient Spatiotemporal Modeling appeared first on MarkTechPost.
TikTok Researchers Introduce SWE-Perf: The First Benchmark for Repository-Level Code Performance Optimization
Introduction As large language models (LLMs) advance in software engineering tasks—ranging from code generation to bug fixing—performance optimization remains an elusive frontier, especially at the repository level.To bridge this gap, researchers from TikTok and collaborating institutions have introduced SWE-Perf—the first benchmark specifically designed to evaluate the ability of LLMs to optimize code performance in […]The post TikTok Researchers Introduce SWE-Perf: The First Benchmark for Repository-Level Code Performance Optimization appeared first on MarkTechPost.
Allen Institute for AI-Ai2 Unveils AutoDS: A Bayesian Surprise-Driven Engine for Open-Ended Scientific Discovery
The Allen Institute for Artificial Intelligence (AI2) has introduced AutoDS (Autonomous Discovery via Surprisal), a groundbreaking prototype engine for open-ended autonomous scientific discovery.Distinct from conventional AI research assistants that depend on human-defined objectives or queries, AutoDS autonomously generates, tests, and iterates on hypotheses by quantifying and seeking out “Bayesian surprise”—a principled measure of genuine […]The post Allen Institute for AI-Ai2 Unveils AutoDS: A Bayesian Surprise-Driven Engine for Open-Ended Scientific Discovery appeared first on MarkTechPost.
Building a Smart Python-to-R Code Converter with Gemini AI-Powered Validation and Feedback
In this tutorial, we delve into the creation of an intelligent Python-to-R code converter that integrates Google’s free Gemini API for validation and improvement suggestions.We start by defining the conversion logic, mapping Python functions, libraries, and syntactic patterns to their closest R equivalents.Then, we leverage Gemini AI to assess the quality of our […]
MIRIX: A Modular Multi-Agent Memory System for Enhanced Long-Term Reasoning and Personalization in LLM-Based Agents
However, a critical dimension remains underexplored: memory—the capacity of agents to persist, recall, and reason over user-specific information across time.Without persistent memory, most LLM-based agents remain stateless, unable to build context beyond a single prompt, limiting their usefulness in […]The post MIRIX: A Modular Multi-Agent Memory System for Enhanced Long-Term Reasoning and Personalization in LLM-Based Agents appeared first on MarkTechPost.
Can LLM Reward Models Be Trusted? Master-RM Exposes and Fixes Their Weaknesses
Generative reward models, where large language models (LLMs) serve as evaluators, are gaining prominence in reinforcement learning with verifiable rewards (RLVR).These models are preferred over rule-based systems for tasks involving open-ended or complex responses.Instead of relying on strict rules, LLMs compare a candidate response to a reference answer and generate binary feedback.
Model Context Protocol (MCP) for Enterprises: Secure Integration with AWS, Azure, and Google Cloud- 2025 Update
The Model Context Protocol (MCP), open-sourced by Anthropic in November 2024, has rapidly become the cross-cloud standard for connecting AI agents to tools, services, and data across the enterprise landscape.Since its release, major cloud vendors and leading AI providers have shipped first-party MCP integrations, and independent platforms are quickly expanding the ecosystem.The post Model Context Protocol (MCP) for Enterprises: Secure Integration with AWS, Azure, and Google Cloud- 2025 Update appeared first on MarkTechPost.
NVIDIA AI Releases OpenReasoning-Nemotron: A Suite of Reasoning-Enhanced LLMs Distilled from DeepSeek R1 0528
NVIDIA AI has introduced OpenReasoning-Nemotron, a family of large language models (LLMs) designed to excel in complex reasoning tasks across mathematics, science, and code.This model suite—comprising 1.5B, 7B, 14B, and 32B parameter versions—has been distilled from the 671B DeepSeek R1 0528 model, capturing its high-level reasoning capabilities in significantly smaller and more efficient models.The post NVIDIA AI Releases OpenReasoning-Nemotron: A Suite of Reasoning-Enhanced LLMs Distilled from DeepSeek R1 0528 appeared first on MarkTechPost.
Maybe Physics-Based AI Is the Right Approach: Revisiting the Foundations of Intelligence
Over the past decade, deep learning has revolutionized artificial intelligence, driving breakthroughs in image recognition, language modeling, and game playing.Yet, persistent limitations have surfaced: data inefficiency, lack of robustness to distribution shifts, high energy demand, and a superficial grasp of physical laws.As AI adoption deepens into critical sectors—from climate forecasting to medicine—these constraints […]
Building a Modern Async Configuration Management System with Type Safety and Hot Reloading
In this tutorial, we guide you through the design and functionality of AsyncConfig, a modern, async-first configuration management library for Python.We build it from the ground up to support powerful features, including type-safe dataclass-based configuration loading, multiple configuration sources (such as environment variables, files, and dictionaries), and hot reloading using watchdog.The post Building a Modern Async Configuration Management System with Type Safety and Hot Reloading appeared first on MarkTechPost.
Deep Research Agents: A Systematic Roadmap for LLM-Based Autonomous Research Systems
A team of researchers from University of Liverpool, Huawei Noah’s Ark Lab, University of Oxford and University College London presents a report explaining Deep Research Agents (DR agents), a new paradigm in autonomous research.These systems are powered by Large Language Models (LLMs) and designed to handle complex, long-horizon tasks that require dynamic reasoning, adaptive […]The post Deep Research Agents: A Systematic Roadmap for LLM-Based Autonomous Research Systems appeared first on MarkTechPost.
MemAgent: A Reinforcement Learning Framework Redefining Long-Context Processing in LLMs
Handling extremely long documents remains a persistent challenge for large language models (LLMs).Even with techniques such as length extrapolation and sparse attention, models often suffer from performance degradation and high computational costs.To address this, researchers from ByteDance Seed and Tsinghua University introduce MemAgent, a reinforcement learning-based memory agent designed to enable long-context processing […]
The Definitive Guide to AI Agents: Architectures, Frameworks, and Real-World Applications (2025)
What is an AI Agent?An AI Agent is an autonomous software system that can perceive its environment, interpret data, reason, and execute actions to achieve specific goals without explicit human intervention.The post The Definitive Guide to AI Agents: Architectures, Frameworks, and Real-World Applications (2025) appeared first on MarkTechPost.
Building a Multi-Agent AI Research Team with LangGraph and Gemini for Automated Reporting
In this tutorial, we build a complete multi-agent research team system using LangGraph and Google’s Gemini API.We utilize role-specific agents, Researcher, Analyst, Writer, and Supervisor, each responsible for a distinct part of the research pipeline.Together, these agents collaboratively gather data, analyze insights, synthesize a report, and coordinate the workflow.
This AI Paper Introduces ARAG: A Multi-Agent RAG Framework for Context-Aware and Personalized Recommendations
Personalized recommendations have become a vital component of many digital systems, aiming to surface content, products, or services that align with user preferences.The process relies on analyzing past behavior, interactions, and patterns to predict what users are likely to find relevant.The post This AI Paper Introduces ARAG: A Multi-Agent RAG Framework for Context-Aware and Personalized Recommendations appeared first on MarkTechPost.
You Don’t Need to Share Data to Train a Language Model Anymore—FlexOlmo Demonstrates How
The development of large-scale language models (LLMs) has historically required centralized access to extensive datasets, many of which are sensitive, copyrighted, or governed by usage restrictions.This constraint severely limits the participation of data-rich organizations operating in regulated or proprietary environments.FlexOlmo—introduced by researchers at the Allen Institute for AI and collaborators—proposes a modular training […]
o1 Style Thinking with Chain-of-Thought Reasoning using Mirascope
In this tutorial, we’ll explore how to implement Chain-of-Thought (CoT) reasoning using the Mirascope library and Groq’s LLaMA 3 model.Rather than having the model jump straight to an answer, CoT reasoning encourages it to break the problem down into logical steps—much like how a human would solve it.This approach improves accuracy, transparency, and […]
EG-CFG: Enhancing Code Generation with Real-Time Execution Feedback
LLMs have made impressive strides in generating code for various programming tasks.However, they mostly rely on recognizing patterns from static code examples rather than understanding how the code behaves during execution.The post EG-CFG: Enhancing Code Generation with Real-Time Execution Feedback appeared first on MarkTechPost.
AegisLLM: Scaling LLM Security Through Adaptive Multi-Agent Systems at Inference Time
The Growing Threat Landscape for LLMs LLMs are key targets for fast-evolving attacks, including prompt injection, jailbreaking, and sensitive data exfiltration.It is necessary to adapt defense mechanisms that move beyond static safeguards because of the fluid nature of these threats.Current LLM security techniques suffer due to their reliance on static, training-time interventions.
OpenAI Introduces ChatGPT Agent: From Research to Real-World Automation
On July 17, 2025, OpenAI launched ChatGPT Agent, transforming ChatGPT from a conversational assistant into a unified AI agent capable of autonomously executing complex, multi‑step tasks—from web browsing to code execution—on a virtual computer environment.Bridging Previous Capabilities ChatGPT Agent builds on two earlier tools: Individually, both had limitations: Operator could interface but couldn’t perform in‑depth analysis;The post OpenAI Introduces ChatGPT Agent: From Research to Real-World Automation appeared first on MarkTechPost.
GLM-4.1V-Thinking: Advancing General-Purpose Multimodal Understanding and Reasoning
Vision-language models (VLMs) play a crucial role in today’s intelligent systems by enabling a detailed understanding of visual content.The complexity of multimodal intelligence tasks has grown, ranging from scientific problem-solving to the development of autonomous agents.Current demands on VLMs have far exceeded simple visual content perception, with increasing attention on advanced reasoning.
Mirage: Multimodal Reasoning in VLMs Without Rendering Images
While VLMs are strong at understanding both text and images, they often rely solely on text when reasoning, limiting their ability to solve tasks that require visual thinking, such as spatial puzzles.Although some recent models can generate both […]The post Mirage: Multimodal Reasoning in VLMs Without Rendering Images appeared first on MarkTechPost.
NVIDIA AI Releases Canary-Qwen-2.5B: A State-of-the-Art ASR-LLM Hybrid Model with SoTA Performance on OpenASR Leaderboard
NVIDIA has just released Canary-Qwen-2.5B, a groundbreaking automatic speech recognition (ASR) and language model (LLM) hybrid, which now tops the Hugging Face OpenASR leaderboard with a record-setting Word Error Rate (WER) of 5.63%.Licensed under CC-BY, this model is both commercially permissive and open-source, pushing forward enterprise-ready speech AI without usage restrictions.This release marks […]
Google Search Just Got a Major AI Upgrade: Gemini 2.5 Pro, Deep Search, and Agentic Intelligence
Google is transforming how we interact with Search.With the recent rollout of Gemini 2.5 Pro, Deep Search, and a powerful new agentic feature, Google is making its search engine smarter, more interactive, and vastly more contextual.These features are currently limited to US users, but they mark a massive shift in how Google Search […]
The 20 Hottest Agentic AI Tools And Agents Of 2025 (So Far)
Research & Cutting‑Edge Agents Frameworks & SDKs Toolkits & Low‑Code Platforms Enterprise & Cloud‑Scale Platforms Reach the most influential AI developers worldwide. 1M+ monthly readers, 500K+ community builders, infinite possibilities. [Explore Sponsorship]The post The 20 Hottest Agentic AI Tools And Agents Of 2025 (So Far) appeared first on MarkTechPost.
Mistral AI Releases Voxtral: The World’s Best (and Open) Speech Recognition Models
Mistral AI has released Voxtral, a family of open-weight models—Voxtral-Small-24B and Voxtral-Mini-3B—designed to handle both audio and text inputs.Built on top of Mistral’s language modeling framework, these models integrate automatic speech recognition (ASR) with natural language understanding capabilities.Released under the Apache 2.0 license, Voxtral provides practical solutions for transcription, summarization, question answering, and […]
A Coding Guide to Build an AI Code-Analysis Agent with Griffe
In this tutorial, we begin by diving into Griffe, positioning it as the center of our advanced AI Code Analyzer.By leveraging Griffe’s rich introspection capabilities, we can seamlessly load, traverse, and dissect Python package structures in real-time.This tutorial guides you through the process of integrating Griffe with complementary libraries, such as NetworkX for […]
JarvisArt: A Human-in-the-Loop Multimodal Agent for Region-Specific and Global Photo Editing
Bridging the Gap Between Artistic Intent and Technical Execution Photo retouching is a core aspect of digital photography, enabling users to manipulate image elements such as tone, exposure, and contrast to create visually compelling content.Whether for professional purposes or personal expression, users often seek to enhance images in ways that align with specific aesthetic […]The post JarvisArt: A Human-in-the-Loop Multimodal Agent for Region-Specific and Global Photo Editing appeared first on MarkTechPost.
NeuralOS: A Generative Framework for Simulating Interactive Operating System Interfaces
Transforming Human-Computer Interaction with Generative Interfaces Recent advances in generative models are transforming the way we interact with computers, making experiences more natural, adaptive, and personalized.Now, with the rise of LLMs and multimodal AI, users can engage […]The post NeuralOS: A Generative Framework for Simulating Interactive Operating System Interfaces appeared first on MarkTechPost.