World Models (WMs) are a central framework for developing agents that reason and plan in a compact latent space. However, training these models directly ...

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, ...

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 ...

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 ...

The deployment of autonomous AI agents—systems capable of using tools and executing code—presents a unique security challenge. While standard LLM applications are restricted to text-based interactions ...

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.

In this tutorial, we explore how to use NVIDIA Warp to build high-performance GPU and CPU simulations directly from Python. We begin by setting up a Colab-compatible environment and initializing Warp ...

Mistral AI Releases Mistral Small 4: A 119B-Parameter MoE Model that Unifies Instruct, Reasoning, and Multimodal Workloads ...

In this tutorial, we build an enterprise-grade AI governance system using OpenClaw and Python. We start by setting up the OpenClaw runtime and launching the OpenClaw Gateway so that our Python ...

Garry Tan Releases gstack, an open-source toolkit that redefines AI-assisted coding with structured workflow skills for developers.

The gap between proprietary frontier models and highly transparent open-source models is closing faster than ever. NVIDIA has officially pulled the curtain back on Nemotron 3 Super, a staggering 120 ...

In the high-stakes world of AI infrastructure, the industry has operated under a singular assumption: flexibility is king. We build general-purpose GPUs because AI models change every week, and we ...