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The NAIRR pilot program, powered by NVIDIA AI infrastructure, has supported over 700 research projects, including the development of the Walrus foundation model for fluid simulations and the MIST molecular foundation models for energy storage.
At CERN, the ALICE collaboration uses open source code on GitHub to analyze massive amounts of physics data, demonstrating how shared code and peer review enable global teamwork in scientific breakthroughs.
This tweet highlights a scientific paper that provides a simplified, step-by-step guide for beginners on writing and publishing research, from initial idea to journal selection and peer review.
A paper introducing Arbor, an AI framework that enables autonomous scientific research by combining strategic coordination, isolated hypothesis testing, and a persistent knowledge tree to iteratively improve research outcomes across multiple domains.
ResearchClawBench is a benchmark for evaluating end-to-end autonomous scientific research across 40 tasks from 10 domains, using expert-curated rubrics. Current systems score poorly, highlighting challenges in achieving reliable autonomous scientific discovery.
Anthropic's science blog argues that AI progress in biology lags behind coding because biological data infrastructure is not designed for agents. A case study shows that adding a deterministic retrieval layer (gget virus) boosts accuracy to nearly 100%.
A report on an AI-assisted research tool that connects the entire research workflow through three Skills (scientific-toolkit, research-writing, office-academic), from data computation to paper writing to PPT creation. It supports one-click installation in Claude Code and Codex, with Chinese-first priority.
Debug is a project using sterile male mosquitoes with Wolbachia bacteria to reduce populations of disease-carrying mosquitoes like Aedes aegypti.
AutoSci is a memory-centric agentic system designed to automate the full scientific research lifecycle, from literature understanding to rebuttal, using LLM-based agents with persistent memory and self-evolution capabilities.
ResearchClawBench is a benchmark for evaluating end-to-end autonomous scientific research across 40 tasks from 10 domains, revealing that current AI agents and LLMs achieve low re-discovery accuracy, with Claude Code averaging 21.5 and Claude-Opus-4.7 averaging 20.7 out of a possible score.
SciAtlas is a large-scale, multi-disciplinary academic knowledge graph containing over 43 million papers and 3 billion triplets, designed to provide structured knowledge for AI-driven automated scientific research with a neuro-symbolic retrieval algorithm.
A GitHub repository called scientific-agent-skills contains 138 Agent Skills for scientific research tools, covering bioinformatics, drug discovery, clinical databases, and more. It supports one-line integration into AI agents, providing precise API calling methods.
A roundup of 12 AI co-scientist systems in 2026, including DeepMind's Co-Scientist finding a fibrosis drug candidate and OpenAI's reasoning model solving an 80-year-old geometry problem, highlighting open-source tools for biology, fluid simulation, and automated research.
Cosmic voids, vast empty regions of space, may help solve mysteries about dark energy, gravity, and the Hubble tension. New telescopes and simulations are enabling detailed study of these voids.
A comprehensive open-source collection of 138 scientific agent skills that transform AI coding assistants like Claude Code and Codex into AI scientists, covering biology, chemistry, medicine, and more, with integration of over 100 scientific databases and specialized Python packages.
AI systems using teams of agents, like Google's Co-Scientist and FutureHouse's Robin, can accelerate drug repurposing research by developing hypotheses, proposing experiments, and analyzing data in hours instead of months.
Google DeepMind announces Gemini for Science, a suite of experimental AI tools to help scientists explore hypotheses, validate work, and unpack literature.
GPT-5.5 autonomously spent over 150 hours improving protein folding models, showcasing advanced AI-driven scientific research.
Google introduces Gemini for Science, a collection of AI-powered experimental tools for scientific research, including hypothesis generation, computational discovery, and literature insights, aimed at accelerating discovery across fields.
This GitHub repository provides 135 ready-to-use scientific AI skills covering biology, chemistry, medicine, and other fields. They can be integrated into AI agents with one click to accelerate research workflows.