DeepMind CEO Demis Hassabis proposed a concrete AGI benchmark: train an AI with a knowledge cutoff of 1911, then see if it can independently derive general relativity as Einstein did in 1915. This test targets genuine scientific discovery rather than pattern matching.
Google DeepMind spin-off Isomorphic Labs published a technical report on IsoDDE, a proprietary drug discovery AI that scientists are comparing to a hypothetical AlphaFold 4. The model excels at predicting protein-drug binding and has secured billion-dollar deals with J&J, Eli Lilly, and Novartis.
Google.org announced a new $30 million global open call for AI-for-science projects on February 18, 2026. Applications are open through April 17, 2026, with focus areas in health and life sciences, crisis resilience, and environmental science.
A Hacker News post highlighted the SkillsBench paper, which evaluates agent skills across 86 tasks and 11 domains. Curated skills improved average pass rate substantially, while self-generated skills showed no average gain.
Anthropic announced on February 2, 2026 that it is partnering with the Allen Institute and Howard Hughes Medical Institute (HHMI) on AI-enabled life-science workflows. The stated goal is to reduce analysis bottlenecks and improve transparent, interpretable scientific reasoning.
Technical summary of "OpenAI Says Internal Model May Have Solved 6 Frontier Research Problems.", a high-signal post from Reddit r/singularity. Based on visible community indicators (score 536, comments 100), this article highlights practical checks before adoption.
Microsoft AI Safety team discovered GRP-Obliteration, an attack that disables safety alignment across 15 major LLMs with a single prompt. GPT-OSS-20B's attack success rate jumped from 13% to 93%.
EPFL researchers have developed a method that essentially eliminates drift in generative video, enabling stable, high-quality videos lasting several minutes without increased computational demands. To be presented at ICLR 2026.
Leading mathematicians launched 'First Proof,' an exam testing AI on unpublished problems. It's academia's skeptical response to AI companies' inflated claims about mathematical breakthroughs.