AI Tools & Frameworks Directory

This release introduces the built-in MCP Server, Extensible Tokenizers, Diversity Search (MMR), and Query Profiling as previews, along with Incremental Backups, Gemini audio support for multi2vec-google, and the new BlobHash property type.

Our most capable voice agent is now available via API.

Cursor was on track to close a $2 billion funding round this week but chose to halt discussions after SpaceX offered a $10 billion "collaboration fee" and a path to a $60 billion acquisition.

Alibaba’s Qwen Team has released Qwen3.6-27B, the first dense open-weight model in the Qwen3.6 family — and arguably the most capable 27-billion-parameter model available today for coding agents. It brings substantial improvements in agentic coding, a novel Thinking Preservation mechanism, and a hyb...

A new training method improves the reliability of AI confidence estimates without sacrificing performance, addressing a root cause of hallucination in reasoning models.

In this tutorial, we explore Equinox, a lightweight and elegant neural network library built on JAX, and show how to use it. We begin by understanding how eqx.Module treats models as PyTrees, which makes parameter handling, transformation, and serialization feel simple and explicit. As we move forwa...

Turning free-to-use data into a hypothesis-ready dataset The post Using Causal Inference to Estimate the Impact of Tube Strikes on Cycling Usage in London appeared first on Towards Data Science.

Gemini Enterprise Agent Platform takes an interesting approach: it is geared for IT and technical users.

How to make multiple agents work together like an elite team — autonomously dividing tasks, communicating efficiently, and collaborating seamlessly? The openJiuwen community released the latest version of JiuwenClaw, which adds support for AgentTeam — a multi-agent collaborative capability. It propo...

Deploying large language models (LLMs) in real-world, high-stakes settings is harder than it should be. In high-stakes settings like law, medicine, and cloud incident response, performance and reliability can quickly break down because adapting models to domain-specific requirements is a slow and ma...

How I turned LLM persona interviews into a repeatable customer research workflow The post From Ad Hoc Prompting to Repeatable AI Workflows with Claude Code Skills appeared first on Towards Data Science.

Infosys said the integration will be used to help its clients modernize software development, automate workflows and deploy AI systems, initially focusing software engineering, legacy modernization, and DevOps.

Design has traditionally required multiple roles working in sequence: a strategist to define the problem, a designer to shape the solution, and a developer to build it. This means coordinating timelines, aligning opinions, and going through rounds of iteration before anything tangible is created. Cl...

Across climate, conservation, disaster monitoring and recycling, NVIDIA AI is enabling applications protecting the planet.

Learn faster, build smarter, and unlock the full power of Claude Code through real examples, reusable templates, prompts, workflows, subagents, and system design.

NVIDIA and Google Cloud have collaborated for more than a decade, co‑engineering a full‑stack AI platform that spans every technology layer — from performance‑optimized libraries and frameworks to enterprise‑grade cloud services.  This foundation enables developers, startups and enterprises to push ...

FastAPI has become one of the most popular ways to serve machine learning models because it is lightweight, fast, and easy to use.

The eighth generation of Google’s TPU includes two specialized chips that will power the future of AI.

The following article originally appeared on the Asimov’s Addendum Substack and is being republished here with the author’s permission. Are LLMs reliable? LLMs have built up a reputation for being unreliable. Small changes in the input can lead to massive changes in the output. The same prompt run t...

Artificial intelligence is moving quickly in the enterprise, from experimentation to everyday use. Organizations are deploying copilots, agents, and predictive systems across finance, supply chains, human resources, and customer operations. By the end of 2025, half of companies used AI in at least t...

Learn how to build, use, and scale workspace agents in ChatGPT to automate repeatable workflows, connect tools, and streamline team operations.

Workspace agents in ChatGPT are Codex-powered agents that automate complex workflows, run in the cloud, and help teams scale work across tools securely.

A deep dive into the Codex agent loop, showing how WebSockets and connection-scoped caching reduced API overhead and improved model latency.

For all the progress made in AI agent development over the past few years, one fundamental problem has remained largely unsolved: most people never actually interact with agents. They live behind developer dashboards, inside specialized apps that users are asked to download, and within chat interfac...