AI Tools & Frameworks Directory

Open interpretability tools for language models are now available across the entire Gemma 3 family with the release of Gemma Scope 2.

OpenAI introduces a real-world evaluation framework to measure how AI can accelerate biological research in the wet lab. Using GPT-5 to optimize a molecular cloning protocol, the work explores both the promise and risks of AI-assisted experimentation....

An AI-driven system lets users design and build simple, multicomponent objects by describing them with words.

The new ChatGPT Images is powered by our flagship image generation model, delivering more precise edits, consistent details, and image generation up to 4× faster. The upgraded model is rolling out to all ChatGPT users today and is also available in the API as GPT-Image-1.5....

Recent years have witnessed the rapid development of open-world image segmentation, including open-vocabulary segmentation and in-context segmentation. Nonetheless, existing methods are limited to a single modality prompt, which lacks the flexibility and accuracy needed for complex object-aware prom...

By Jacob Meyers and Rob ZienertTemporal is a Durable Execution platform which allows you to write code “as if failures don’t exist”. It’s become increasingly critical to Netflix since its initial adoption in 2021, with users ranging from the operators of our Open Connect global CDN to our Live relia...

Xiaomei Liu, Joseph Lynch, Chris NewtonIntroductionBehind the Streams: Building a Reliable Cloud Live Streaming Pipeline for Netflix introduced the architecture of the streaming pipeline. This blog post looks at the custom Origin Server we built for Live — the Netflix Live Origin. It sits at the dem...

NVIDIA today announced it has acquired SchedMD — the leading developer of Slurm, an open-source workload management system for high-performance computing (HPC) and AI — to help strengthen the open-source software ecosystem and drive AI innovation for researchers, developers and enterprises. NVIDIA w...

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The Model Context Protocol (MCP) is genuinely useful. It gives people who develop AI tools a standardized way to call functions and access data from external systems. Instead of building custom integrations for each data source, you can expose databases, APIs, and internal tools through a common pro...

Readers wanted to know if their therapy chatbot could be trusted, whether their boss was automating the wrong job, and if their private conversations were training tomorrow's models.

Most AI projects start with one annoying chore: cleaning messy files. PDFs, Word docs, PPTs, images, audio, and spreadsheets all need to be converted into clean text before they become useful. Microsoft’s MarkItDown finally fixes this problem. In this guide, I will show you how to install it, conver...

I’ve spent plenty of time building agentic systems. Our platform, Mentornaut, already runs on a multi-agent setup with vector stores, knowledge graphs, and user-memory features, so I thought I had the basics down. Out of curiosity, I checked out the whitepapers from Kaggle’s Agents Intensive, and th...

Ridge and Lasso regression are often perceived as more complex versions of linear regression. In reality, the prediction model remains exactly the same. What changes is the training objective. By adding a penalty on the coefficients, regularization forces the model to choose more stable solutions, e...

Building applications with LLMs through composability. LangChain is a framework for developing applications powered by language models.

A timeline of ChatGPT product updates and releases, starting with the latest, which we’ve been updating throughout the year....

Following the publication of his new book, Building Applications with AI Agents, I chatted with author Michael Albada about his experience writing the book and his thoughts on the field of AI agents. Michael’s a machine learning engineer with nine years of experience designing, building, and deployi...

In 2026, AI advantage will not come from tools but from focus. This piece outlines three concrete, disruptive moves businesses can make to turn AI into durable leverage, plus the contrarian and pessimistic views leaders should confront head-on.

By decoupling how agents work from how they’re trained, Agent Lightning turns each step an agent takes into data for reinforcement learning. This makes it easy for developers to improve agent performance with almost zero code changes. The post Agent Lightning: Adding reinforcement learning to AI age...

Han Wang | Machine Learning Engineer; Alex Whitworth | Staff Data Scientist; Pak Ming Cheung | Sr. Staff Machine Learning Engineer; Zhenjie Zhang | Sr. Staff Machine Learning EngineerIntroductionSearch relevance measures how well search results align with a user’s search query. For personalized sear...

Debugging is the process of finding and fixing errors. This is a critical step in software engineering, and even more critical in agent engineering. One of the key capabilities of LangSmith is tooling to debug LLM applications.Today we are doubling down on solving that problem for the new wave

Today, we're launching LangSmith Fetch, a CLI tool that brings the full power of LangSmith tracing directly into your terminal and IDE.If you're building agents with coding tools like Claude Code or Cursor, or if you simply prefer working in the command line, you'

Promptions helps developers add dynamic, context-aware controls to chat interfaces so users can guide generative AI responses. It lets users shape outputs quickly without writing long instructions. The post Promptions helps make AI prompting more precise with dynamic UI controls appeared first on Mi...