Browsing: Framework

Generative AI is reshaping how organizations approach productivity, customer experiences, and operational capabilities. Across industries, teams are experimenting with generative AI to unlock new ways of…

Retrieval-Augmented Generation (RAG) has become a standard technique for grounding large language models in external knowledge — but the moment you move beyond plain text and…

Training AI agents that can actually use a computer — opening apps, clicking buttons, browsing the web, writing code — is one of the hardest infrastructure…

Writing a research paper is brutal. Even after the experiments are done, a researcher still faces weeks of translating messy lab notes, scattered results tables, and…

Writing fast GPU code is one of the most grueling specializations in machine learning engineering. Researchers from RightNow AI want to automate it entirely. The RightNow…

Post-training Large Language Models (LLMs) for long-horizon agentic tasks—such as software engineering, web browsing, and complex tool use—presents a persistent trade-off between computational efficiency and model…

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,…

Stanford researchers have introduced OpenJarvis, an open-source framework for building personal AI agents that run entirely on-device. The project comes from Stanford’s Scaling Intelligence Lab and…

In this tutorial, we implement a Colab-ready version of the AutoResearch framework originally proposed by Andrej Karpathy. We build an automated experimentation pipeline that clones the…

Claude Flow is an open-source orchestration framework designed to run multiple Claude agents in coordinated workflows. Instead of relying on a single LLM prompt chain, it…