AI research news and paper summaries.
In this tutorial, we build a Groq-powered agentic research workflow that runs directly using Groqâs free OpenAI-compatible inference endpoint The post A Groq-Powered Agentic Research Assistant with LangGraph, Tool Calling, Sub-Agents, and Agentic Memory: Lets Built It appeared first on MarkTechPost.
CopilotKit Intelligence adds a managed persistence layer on top of the open-source CopilotKit stack, giving agents the ability to retain context, state, and interaction history without custom storage infrastructure The post CopilotKit Introduces Enterprise Intelligence Platform That Gives Agentic Applications Persistent Memory Across Sessions and Devices appeared first on MarkTechPost.
Google Introduces MTP Drafters for Gemma 4 Family Using Speculative Decoding to Achieve Up to 3x Speedup The post Google AI Releases Multi-Token Prediction (MTP) Drafters for Gemma 4: Delivering Up to 3x Faster Inference Without Quality Loss appeared first on MarkTechPost.
There is a particular kind of irony that the legal profession rarely gets to witness in such pristine form. In May 2025, Latham & Watkins a firm that routinely bills over $2,000 an hour for its partners and counts Anthropic among its clients filed a court declaration in Concord Music Group v. Anthropic that contained […] The post When Claude Hallucinates in Court: The Latham & Watkins Incident and What It Means for Attorney Liability appeared first on MarkTechPost.
In this tutorial, we build a fully interactive, multi-page web application using NiceGUI. We start by setting up the environment and designing a reusable layout that includes navigation, theming, and dark mode support. As we move forward, we implement a live dashboard with real-time metrics and charts, demonstrating reactive bindings and timed updates. We then […] The post How to Build a Fully Interactive Multi-Page NiceGUI Application with Real-Time Dashboard, CRUD Operations, File Upload
The Inworld AI's new model conditions on full audio context, not just transcripts â a meaningful architectural shift for voice-first AI agents The post Inworld AI Launches Realtime TTS-2: A Closed-Loop Voice Model That Adapts to How You Actually Talk appeared first on MarkTechPost.
Voice AI has a dirty secret. Most text-to-speech systems sound fine â until they don’t. They can read a sentence. What they cannot do is mean it. The rhythm is off. The emotion is flat. The speaker sounds like themselves for two seconds, then drifts into generic synthetic territory. That gap between intelligible audio and […] The post Closing the ‘Expressivity Gap’: How Mistral’s Voxtral TTS is Redefining Multilingual Voice Cloning with a Hybrid Autoregressive and F
In this tutorial, we build a complete skill-based agent system for large language models and explore how modular capabilities can be structured like an operating system for AI agents. We define reusable skills, attach metadata and schemas to them, register them in a central registry, and enable dynamic orchestration through tool calling and multi-step reasoning. […] The post Build a Modular Skill-Based Agent System for LLMs with Dynamic Tool Routing in Python appeared first on MarkTechPost
How momentum optimizes gradient descent by dampening oscillations and accelerating convergence on complex The post Why Gradient Descent Zigzags and How Momentum Fixes It appeared first on MarkTechPost.
A push-based notification system for Batch API, Deep Research, and video generation tasks arrives with built-in security, retry guarantees, and two configuration modes. The post Google Adds Event-Driven Webhooks to the Gemini API, Eliminating the Need for Polling in Long-Running AI Jobs appeared first on MarkTechPost.
In this tutorial, we walk through a complete, end-to-end workflow for correcting bias in survey data using the balance library. We simulate a realistic population, deliberately introduce sampling bias, and then apply multiple re-weighting techniques to recover unbiased estimates. We focus on four widely used methods: Inverse Probability Weighting (IPW), Covariate Balancing Propensity Scores (CBPS), […] The post A Coding Guide to Survey Bias Correction Using Facebook Research Balance with I
Zyphra Introduces Tensor and Sequence Parallelism (TSP): A Folded Parallelism Strategy That Reduces Both Parameter and Activation Memory Across the Same GPU Axis The post Zyphra Introduces Tensor and Sequence Parallelism (TSP): A Hardware-Aware Training and Inference Strategy That Delivers 2.6x Throughput Over Matched TP+SP Baselines appeared first on MarkTechPost.
In this tutorial, we walk through an end-to-end implementation of an advanced machine learning pipeline using ZenML. We begin by setting up the environment and initializing a ZenML project, then define a custom materializer that enables seamless serialization and metadata extraction for a domain-specific dataset object. As we progress, we build a modular pipeline that […] The post How to Build an End-to-End Production Grade Machine Learning Pipeline with ZenML, Including Custom Materialize
Discover the top search and fetch APIs for AI agents in 2026. Compare tools like TinyFish, Tavily, and Firecrawl based on latency, token efficiency, and free tiers to optimize your agent's web retrieval. The post Top Search and Fetch APIs for Building AI Agents in 2026: Tools, Tradeoffs, and Free Tiers appeared first on MarkTechPost.
Most developers treat prompting as an afterthoughtâwrite something reasonable, observe the output, and iterate if needed. That approach works until reliability becomes critical. As LLMs move into production systems, the difference between a prompt that usually works and one that works consistently becomes an engineering concern. In response, the research community has formalized prompting into […] The post A Developerâs Guide to Systematic Prompting: Mastering Negative Constraints, Structu
In this tutorial, we take a deep dive into the TaskTrove dataset on Hugging Face and build a complete, practical workflow to efficiently explore it. Instead of downloading the full multi-gigabyte dataset, we stream it directly and work with individual samples in real time. We begin by setting up the environment and inspecting the raw […] The post A Coding Implementation to Explore and Analyze the TaskTrove Dataset with Streaming Parsing Visualization and Verifier Detection appeared first o
Sakana AI Introduces KAME: A Tandem Architecture That Injects Real-Time LLM Knowledge Into Speech-to-Speech Conversational AI Without Adding Latency The post Sakana AI Introduces KAME: A Tandem Speech-to-Speech Architecture That Injects LLM Knowledge in Real Time appeared first on MarkTechPost.
A model can behave perfectly one moment and degrade the nextâwithout any change to your data, pipeline, or logic. The root cause often lies in something far more subtle: how your input is tokenized. Before a model processes text, it converts it into token IDs, and even minor formatting differencesâlike spacing, line breaks, or punctuationâcan […] The post What is Tokenization Drift and How to Fix It? appeared first on MarkTechPost.
Mistral AI's latest release brings async cloud-based coding sessions, a new 128B flagship model, and an agentic Work mode to Le Chat â a meaningful step forward for developers building with AI agents. The post Mistral AI Launches Remote Agents in Vibe and Mistral Medium 3.5 with 77.6% SWE-Bench Verified Score appeared first on MarkTechPost.
Build a Multi-Agent AI Workflow for Biological Network Modeling, Protein Interactions, Metabolism, and Cell Signaling Simulation The post Build a Multi-Agent AI Workflow for Biological Network Modeling, Protein Interactions, Metabolism, and Cell Signaling Simulation appeared first on MarkTechPost.
In this tutorial, we explore the lambda/hermes-agent-reasoning-traces dataset to understand how agent-based models think, use tools, and generate responses across multi-turn conversations. We start by loading and inspecting the dataset, examining its structure, categories, and conversational format to get a clear idea of the available information. We then build simple parsers to extract key components […] The post A Coding Implementation to Parsing, Analyzing, Visualizing, and Fine-Tuning
A new paper from NVIDIA Research integrates speculative decoding directly into NeMo RL with a vLLM backend, delivering lossless rollout acceleration at both 8B and projected 235B model scales. The post A New NVIDIA Research Shows Speculative Decoding in NeMo RL Achieves 1.8Ă Rollout Generation Speedup at 8B and Projects 2.5Ă End-to-End Speedup at 235B appeared first on MarkTechPost.
In this tutorial, we explore how we can decode linguistic features directly from brain signals using a modern neuroAI pipeline. We work with MEG data and build an end-to-end system that transforms raw neural activity into meaningful predictions, in this case, estimating word length from brain responses. We set up the environment, load and process […] The post A Coding Implementation of End-to-End Brain Decoding from MEG Signals Using NeuralSet and Deep Learning for Predicting Linguistic Fe
Meta Introduces Autodata: An Agentic Framework That Turns AI Models into Autonomous Data Scientists for High-Quality Training Data Creation The post Meta Introduces Autodata: An Agentic Framework That Turns AI Models into Autonomous Data Scientists for High-Quality Training Data Creation appeared first on MarkTechPost.
In this tutorial, we walk through a complete, hands-on journey of post-training large language models using the powerful TRL (Transformer Reinforcement Learning) library ecosystem. We start from a lightweight base model and progressively apply four key techniques: Supervised Fine-Tuning (SFT), Reward Modeling (RM), Direct Preference Optimization (DPO), and Group Relative Policy Optimization (GRPO). Also, we […] The post A Coding Guide on LLM Post Training with TRL from Supervised Fine Tuni
Qwen Team Introduces Qwen-Scope: An Open-Source Sparse Autoencoder Suite That Turns LLM Internals into Practical Development Tools The post Qwen AI Releases Qwen-Scope: An Open-Source Sparse AutoEncoders (SAE) Suite That Turns LLM Internal Features into Practical Development Tools appeared first on MarkTechPost.
In this tutorial, we build the entire Agentic UI stack from the ground up using plain Python, without relying on external frameworks to abstract away the core ideas. We implement the AG-UI event stream to make agent behavior observable in real time, and we bring in A2UI as a declarative layer that allows interfaces to […] The post A Coding Deep Dive into Agentic UI, Generative UI, State Synchronization, and Interrupt-Driven Approval Flows appeared first on MarkTechPost.
Moonshot AI releases FlashKDA, a high-performance implementation of Kimi Delta Attention that plugs directly into the flash-linear-attention ecosystem â and benchmarks show it's meaningfully faster. The post Moonshot AI Open-Sources FlashKDA: CUTLASS Kernels for Kimi Delta Attention with Variable-Length Batching and H20 Benchmarks appeared first on MarkTechPost.
Microsoft Research's World-R1 Uses Reinforcement Learning to Force 3D Consistency Into Text-to-Video Models The post Microsoft Research’s World-R1 Uses Flow-GRPO and 3D-Aware Rewards to Inject Geometric Consistency Into Wan 2.1 Without Architectural Changes appeared first on MarkTechPost.
A Coding Implementation on Pyright Type Checking Covering Generics, Protocols, Strict Mode, Type Narrowing, and Modern Python Typing The post A Coding Implementation on Pyright Type Checking Covering Generics, Protocols, Strict Mode, Type Narrowing, and Modern Python Typing appeared first on MarkTechPost.
IBM Releases Granite Speech 4.1 2B and Its Non-Autoregressive Twin â Compact ASR Models Built for Enterprise The post IBM Releases Two Granite Speech 4.1 2B Models: Autoregressive ASR with Translation and Non-Autoregressive Editing for Fast Inference appeared first on MarkTechPost.
Cursor Launches TypeScript SDK to Let Developers Build and Deploy Programmatic Coding Agents The post Cursor Introduces a TypeScript SDK for Building Programmatic Coding Agents With Sandboxed Cloud VMs, Subagents, Hooks, and Token-Based Pricing appeared first on MarkTechPost.
Top 10 KV Cache Compression Techniques for LLM Inference: Reducing Memory Overhead Across Eviction, Quantization, and Low-Rank Methods The post Top 10 KV Cache Compression Techniques for LLM Inference: Reducing Memory Overhead Across Eviction, Quantization, and Low-Rank Methods appeared first on MarkTechPost.
The QwenLM team has released FlashQLA, a new kernel library that dramatically accelerates the forward and backward passes of Gated Delta Network (GDN) Chunked Prefill, targeting both large-scale pretraining and edge-side agentic inference scenarios. The post Qwen Team Releases FlashQLA: a High-Performance Linear Attention Kernel Library That Achieves Up to 3Ă Speedup on NVIDIA Hopper GPUs appeared first on MarkTechPost.
In this tutorial, we build a complete, production-style pipeline for detecting and redacting personally identifiable information using the OpenAI Privacy Filter. We begin by setting up the environment and loading a token classification model that identifies multiple categories of sensitive data, including names, emails, phone numbers, addresses, and secrets. We then design helper functions to […] The post Step by Step Guide to Build a Complete PII Detection and Redaction Pipeline with Open
Introducing NeuralSet: Meta's Simple, Fast, and Scalable Python Package That Bridges Neuroscience and AI The post Meta FAIR Releases NeuralSet: A Python Package for Neuro-AI That Supports fMRI, M/EEG, Spikes, and HuggingFace Embeddings appeared first on MarkTechPost.
smol-audio Is the Audio AI Cookbook Practitioners Have Been Waiting For The post smol-audio: A Colab-Friendly Notebook Collection for Fine-Tuning Whisper, Parakeet, Voxtral, Granite Speech, and Audio Flamingo 3 appeared first on MarkTechPost.
In this tutorial, we build a complete end-to-end pipeline using NVIDIA Model Optimizer to train, prune, and fine-tune a deep learning model directly in Google Colab. We start by setting up the environment and preparing the CIFAR-10 dataset, then define a ResNet architecture and train it to establish a strong baseline. From there, we apply […] The post Step by Step Guide to Build an End-to-End Model Optimization Pipeline with NVIDIA Model Optimizer Using FastNAS Pruning and Fine-Tuning appe
The landscape of open-source artificial intelligence has shifted from purely generative models toward systems capable of complex, multi-step reasoning. While proprietary ‘reasoning’ models have dominated the conversation, Arcee AI has released Trinity Large Thinking. This release is an open-weight reasoning model distributed under the Apache 2.0 license, positioning it as a transparent alternative for developers […] The post Arcee AI Releases Trinity Large Thinking: An Apache 2
Run Googleâs latest omni-capable open models faster on NVIDIA RTX AI PCs, from NVIDIA Jetson Orin Nano, GeForce RTX desktops to the new DGX Spark, to build personalized, always-on AI assistants like OpenClaw without paying a massive “token tax” for every action. The landscape of modern AI is shifting rapidly. We are moving away from […] The post Defeating the âToken Taxâ: How Google Gemma 4, NVIDIA, and OpenClaw are Revolutionizing Local Agentic AI: From RTX Desktops to DGX Spa
IBM has announced the release of Granite 4.0 3B Vision, a vision-language model (VLM) engineered specifically for enterprise-grade document data extraction. Departing from the monolithic approach of larger multimodal models, the 4.0 Vision release is architected as a specialized adapter designed to bring high-fidelity visual reasoning to the Granite 4.0 Micro language backbone. This release […] The post IBM Releases Granite 4.0 3B Vision: A New Vision Language Model for Enterprise Grade Do
In this tutorial, we build a complete AgentScope workflow from the ground up and run everything in Colab. We start by wiring OpenAI through AgentScope and validating a basic model call to understand how messages and responses are handled. From there, we define custom tool functions, register them in a toolkit, and inspect the auto-generated […] The post How to Build Production Ready AgentScope Workflows with ReAct Agents, Custom Tools, Multi-Agent Debate, Structured Output and Concurrent P
In the field of vision-language models (VLMs), the ability to bridge the gap between visual perception and logical code execution has traditionally faced a performance trade-off. Many models excel at describing an image but struggle to translate that visual information into the rigorous syntax required for software engineering. Zhipu AI’s (Z.ai) GLM-5V-Turbo is a vision […] The post Z.ai Launches GLM-5V-Turbo: A Native Multimodal Vision Coding Model Optimized for OpenClaw and High-Ca
In this tutorial, we build and run a Colab workflow for Gemma 3 1B Instruct using Hugging Face Transformers and HF Token, in a practical, reproducible, and easy-to-follow step-by-step manner. We begin by installing the required libraries, securely authenticating with our Hugging Face token, and loading the tokenizer and model onto the available device with […] The post How to Build a Production-Ready Gemma 3 1B Instruct Generation AI Pipeline with Hugging Face Transformers, Chat Templates,
Hugging Face has officially released TRL (Transformer Reinforcement Learning) v1.0, marking a pivotal transition for the library from a research-oriented repository to a stable, production-ready framework. For AI professionals and developers, this release codifies the Post-Training pipelineâthe essential sequence of Supervised Fine-Tuning (SFT), Reward Modeling, and Alignmentâinto a unified, standardized API. In the early stages […] The post Hugging Face Releases TRL v1.0: A Unified Post-T
Google has announced the release of Veo 3.1 Lite, a new model tier within its generative video portfolio designed to address the primary bottleneck for production-scale deployments: pricing. While the generative video space has seen rapid progress in visual fidelity, the cost per second of generated content has remained high, often prohibitive for developers building […] The post Google AI Releases Veo 3.1 Lite: Giving Developers Low Cost High Speed Video Generation via The Gemini API appe
In the current landscape of generative AI, the ‘scaling laws’ have generally dictated that more parameters equal more intelligence. However, Liquid AI is challenging this convention with the release of LFM2.5-350M. This model is actually a technical case study in intelligence density with additional pre-training (from 10T to 28T tokens) and large-scale reinforcement learning The […] The post Liquid AI Released LFM2.5-350M: A Compact 350M Parameter Model Trained on 28T Tokens wi
In this tutorial, we work directly with the A-Evolve framework in Colab and build a complete evolutionary agent pipeline from the ground up. We set up the repository, configure an OpenAI-powered agent, define a custom benchmark, and build our own evolution engine to see how A-Evolve actually improves an agent through iterative workspace mutations. Through […] The post How to Build and Evolve a Custom OpenAI Agent with A-Evolve Using Benchmarks, Skills, Memory, and Workspace Mutations appea
The landscape of multimodal large language models (MLLMs) has shifted from experimental ‘wrappers’âwhere separate vision or audio encoders are stitched onto a text-based backboneâto native, end-to-end ‘omnimodal’ architectures. Alibaba Qwen team latest release, Qwen3.5-Omni, represents a significant milestone in this evolution. Designed as a direct competitor to flagship models like Gemini 3.1 Pro, the Qwen3.5-Omni […] The post Alibaba Qwen Team Releases Qwen3.5 Omn
Microsoft has announced the release of Harrier-OSS-v1, a family of three multilingual text embedding models designed to provide high-quality semantic representations across a wide range of languages. The release includes three distinct scales: a 270M parameter model, a 0.6B model, and a 27B model. The Harrier-OSS-v1 models achieved state-of-the-art (SOTA) results on the Multilingual MTEB […] The post Microsoft AI Releases Harrier-OSS-v1: A New Family of Multilingual Embedding Models Hittin
In the world of voice AI, the difference between a helpful assistant and an awkward interaction is measured in milliseconds. While text-based Retrieval-Augmented Generation (RAG) systems can afford a few seconds of ‘thinking’ time, voice agents must respond within a 200ms budget to maintain a natural conversational flow. Standard production vector database queries typically add […] The post Salesforce AI Research Releases VoiceAgentRAG: A Dual-Agent Memory Router that Cuts Voic
In the development of autonomous agents, the technical bottleneck is shifting from model reasoning to the execution environment. While Large Language Models (LLMs) can generate code and multi-step plans, providing a functional and isolated environment for that code to run remains a significant infrastructure challenge. Agent-Infraâs Sandbox, an open-source project, addresses this by providing an […] The post Agent-Infra Releases AIO Sandbox: An All-in-One Runtime for AI Agents with Browser
In this tutorial, we build and explore the CAI Cybersecurity AI Framework step by step in Colab using an OpenAI-compatible model. We begin by setting up the environment, securely loading the API key, and creating a base agent. We gradually move into more advanced capabilities such as custom function tools, multi-agent handoffs, agent orchestration, input […] The post How to Build Advanced Cybersecurity AI Agents with CAI Using Tools, Guardrails, Handoffs, and Multi-Agent Workflows appeared
Google has released Gemini 3.1 Flash Live in preview for developers through the Gemini Live API in Google AI Studio. This model targets low-latency, more natural, and more reliable real-time voice interactions, serving as Googleâs ‘highest-quality audio and speech model to date.’ By natively processing multimodal streams, the release provides a technical foundation for building […] The post Google Releases Gemini 3.1 Flash Live: A Real-Time Multimodal Voice Model for Low-Latenc
In this tutorial, we work directly with Qwen3.5 models distilled with Claude-style reasoning and set up a Colab pipeline that lets us switch between a 27B GGUF variant and a lightweight 2B 4-bit version with a single flag. We start by validating GPU availability, then conditionally install either llama.cpp or transformers with bitsandbytes, depending on […] The post A Coding Implementation to Run Qwen3.5 Reasoning Models Distilled with Claude-Style Thinking Using GGUF and 4-Bit Quantizatio
In the landscape of enterprise AI, the bridge between unstructured audio and actionable text has often been a bottleneck of proprietary APIs and complex cascaded pipelines. Today, Cohereâa company traditionally known for its text-generation and embedding modelsâhas officially stepped into the Automatic Speech Recognition (ASR) market with the release of their latest model ‘Cohere Transcribe‘. […] The post Cohere AI Releases Cohere Transcribe: A SOTA Automatic Speech Recognition
Tencent AI Lab has released Covo-Audio, a 7B-parameter end-to-end Large Audio Language Model (LALM). The model is designed to unify speech processing and language intelligence by directly processing continuous audio inputs and generating audio outputs within a single architecture. System Architecture The Covo-Audio framework consists of four primary components designed for seamless cross-modal interaction: Hierarchical […] The post Tencent AI Open Sources Covo-Audio: A 7B Speech Language M
In this tutorial, we explore MolmoWeb, Ai2âs open multimodal web agent that understands and interacts with websites directly from screenshots, without relying on HTML or DOM parsing. We set up the full environment in Colab, load the MolmoWeb-4B model with efficient 4-bit quantization, and build the exact prompting workflow that lets the model reason about […] The post How to Build a Vision-Guided Web AI Agent with MolmoWeb-4B Using Multimodal Reasoning and Action Prediction appeared first
Post-training Large Language Models (LLMs) for long-horizon agentic tasksâsuch as software engineering, web browsing, and complex tool useâpresents a persistent trade-off between computational efficiency and model generalization. While Supervised Fine-Tuning (SFT) is computationally inexpensive, it frequently suffers from out-of-domain (OOD) performance degradation and struggles to generalize beyond its training distribution. Conversely, end-to-end reinforcement learning (E2E […] The post
The scaling of Large Language Models (LLMs) is increasingly constrained by memory communication overhead between High-Bandwidth Memory (HBM) and SRAM. Specifically, the Key-Value (KV) cache size scales with both model dimensions and context length, creating a significant bottleneck for long-context inference. Google research team has proposed TurboQuant, a data-oblivious quantization framework designed to achieve near-optimal […] The post Google Introduces TurboQuant: A New Compression Alg
When running LLMs at scale, the real limitation is GPU memory rather than compute, mainly because each request requires a KV cache to store token-level data. In traditional setups, a large fixed memory block is reserved per request based on the maximum sequence length, which leads to significant unused space and limits concurrency. Paged Attention […] The post Paged Attention in Large Language Models LLMs appeared first on MarkTechPost.
In this tutorial, we explore OpenSpace, a self-evolving skill engine developed by HKUDS that makes AI agents smarter, more cost-efficient, and capable of learning from every task they perform. We walk through the complete lifecycle of OpenSpace: from installing and configuring an OpenAI model, to executing cold-start tasks where no prior skills exist, watching the […] The post A Coding Implementation to Design Self-Evolving Skill Engine with OpenSpace for Skill Learning, Token Efficiency,
Researchers from FAIR at Meta, Cornell University, and Carnegie Mellon University have demonstrated that large language models (LLMs) can learn to reason using a remarkably small number of trained parameters. The research team introduces TinyLoRA, a parameterization that can scale down to a single trainable parameter under extreme sharing settings. Using this method on a […] The post This AI Paper Introduces TinyLoRA, A 13-Parameter Fine-Tuning Method That Reaches 91.8 Percent GSM8K on Qwe
World Models (WMs) are a central framework for developing agents that reason and plan in a compact latent space. However, training these models directly from pixel data often leads to ‘representation collapse,’ where the model produces redundant embeddings to trivially satisfy prediction objectives. Current approaches attempt to prevent this by relying on complex heuristics: they […] The post Yann LeCunâs New LeWorldModel (LeWM) Research Targets JEPA Collapse in Pixel-Based Pre
The dream of recursive self-improvement in AIâwhere a system doesnât just get better at a task, but gets better at learningâhas long been the ‘holy grail’ of the field. While theoretical models like the Gödel Machine have existed for decades, they remained largely impractical in real-world settings. That changed with the Darwin Gödel Machine (DGM), […] The post Meta AIâs New Hyperagents Donât Just Solve TasksâThey Rewrite the Rules of How They Learn appeared first on MarkTechPo
In the field of generative AI media, the industry is transitioning from purely probabilistic pixel synthesis toward models capable of structural reasoning. Luma Labs has just released Uni-1, a foundational image model designed to address the ‘intent gap” inherent in standard diffusion pipelines. By implementing a reasoning phase prior to generation, Uni-1 shifts the workflow […] The post Luma Labs Launches Uni-1: The Autoregressive Transformer Model that Reasons through Intenti
In this tutorial, we build an advanced, hands-on tutorial around Google’s newly released colab-mcp, an open-source MCP (Model Context Protocol) server that lets any AI agent programmatically control Google Colab notebooks and runtimes. Across five self-contained snippets, we go from first principles to production-ready patterns. We start by constructing a minimal MCP tool registry from […] The post How to Design a Production-Ready AI Agent That Automates Google Colab Workflows Using
When you type a query into a search engine, something has to decide which documents are actually relevant â and how to rank them. BM25 (Best Matching 25), the algorithm powering search engines like Elasticsearch and Lucene, has been the dominant answer to that question for decades.  It scores documents by looking at three things: […] The post How BM25 and RAG Retrieve Information Differently? appeared first on MarkTechPost.
In this tutorial, we implement a reinforcement learning agent using RLax, a research-oriented library developed by Google DeepMind for building reinforcement learning algorithms with JAX. We combine RLax with JAX, Haiku, and Optax to construct a Deep Q-Learning (DQN) agent that learns to solve the CartPole environment. Instead of using a fully packaged RL framework, […] The post Implementing Deep Q-Learning (DQN) from Scratch Using RLax JAX Haiku and Optax to Train a CartPole Reinforcement
The current state of AI agent development is characterized by significant architectural fragmentation. Software devs building autonomous systems must generally commit to one of several competing ecosystems: LangChain, AutoGen, CrewAI, OpenAI Assistants, or the more recent Claude Code. Each of these ‘Five Frameworks’ utilizes a proprietary method for defining agent logic, memory persistence, and tool […] The post Meet GitAgent: The Docker for AI Agents that is Finally Solving th
In this tutorial, we explore the capabilities of the pymatgen library for computational materials science using Python. We begin by constructing crystal structures such as silicon, sodium chloride, and a LiFePOâ-like material, and then investigate their lattice properties, densities, and compositions. Also, we analyze symmetry using space-group detection, examine atomic coordination environments, and apply oxidation-state […] The post A Coding Implementation for Building and Analyzing Crys
Deploying a new machine learning model to production is one of the most critical stages of the ML lifecycle. Even if a model performs well on validation and test datasets, directly replacing the existing production model can be risky. Offline evaluation rarely captures the full complexity of real-world environmentsâdata distributions may shift, user behavior can […] The post Safely Deploying ML Models to Production: Four Controlled Strategies (A/B, Canary, Interleaved, Shadow Testing) appe
In this tutorial, we build an uncertainty-aware large language model system that not only generates answers but also estimates the confidence in those answers. We implement a three-stage reasoning pipeline in which the model first produces an answer along with a self-reported confidence score and a justification. We then introduce a self-evaluation step that allows […] The post A Coding Implementation to Build an Uncertainty-Aware LLM System with Confidence Estimation, Self-Evaluation, and
NVIDIA has announced the release of Nemotron-Cascade 2, an open-weight 30B Mixture-of-Experts (MoE) model with 3B activated parameters. The model focuses on maximizing ‘intelligence density,’ delivering advanced reasoning capabilities at a fraction of the parameter scale used by frontier models. Nemotron-Cascade 2 is the second open-weight LLM to achieve Gold Medal-level performance in the 2025 […] The post NVIDIA Releases Nemotron-Cascade 2: An Open 30B MoE with 3B Active Para
In this comprehensive tutorial, we present the core architecture of ClawTeam, an open-source Agent Swarm Intelligence framework developed by HKUDS. We implement the fundamental concepts that make ClawTeam powerful: a leader agent that decomposes complex goals into sub-tasks, specialized worker agents that execute those tasks autonomously, a shared task board with automatic dependency resolution, and […] The post A Coding Implementation Showcasing ClawTeam’s Multi-Agent Swarm Orchestr
In the current landscape of Retrieval-Augmented Generation (RAG), the primary bottleneck for developers is no longer the large language model (LLM) itself, but the data ingestion pipeline. For software developers, converting complex PDFs into a format that an LLM can reason over remains a high-latency, often expensive task. LlamaIndex has recently introduced LiteParse, an open-source, […] The post LlamaIndex Releases LiteParse: A CLI and TypeScript-Native Library for Spatial PDF Parsing in
Google has officially released the Colab MCP Server, an implementation of the Model Context Protocol (MCP) that enables AI agents to interact directly with the Google Colab environment. This integration moves beyond simple code generation by providing agents with programmatic access to create, modify, and execute Python code within cloud-hosted Jupyter notebooks. This represents a […] The post Google Colab Now Has an Open-Source MCP (Model Context Protocol) Server: Use Colab Runtimes with
In this tutorial, we explore how to solve differential equations and build neural differential equation models using the Diffrax library. We begin by setting up a clean computational environment and installing the required scientific computing libraries such as JAX, Diffrax, Equinox, and Optax. We then demonstrate how to solve ordinary differential equations using adaptive solvers […] The post A Coding Guide to Implement Advanced Differential Equation Solvers, Stochastic Simulations, and N
The scaling of inference-time compute has become a primary driver for Large Language Model (LLM) performance, shifting architectural focus toward inference efficiency alongside model quality. While Transformer-based architectures remain the standard, their quadratic computational complexity and linear memory requirements create significant deployment bottlenecks. A team of researchers from Carnegie Mellon University (CMU), Princeton University, Together […] The post Meet Mamba-3: A New Sta
Autonomous LLM agents like OpenClaw are shifting the paradigm from passive assistants to proactive entities capable of executing complex, long-horizon tasks through high-privilege system access. However, a security analysis research report from Tsinghua University and Ant Group reveals that OpenClawâs âkernel-pluginâ architectureâanchored by a pi-coding-agent serving as the Minimal Trusted Computing Base (TCB)âis vulnerable to […] The post Tsinghua and Ant Group Researchers Unveil a Five-L