AI for Science
Scientific discovery, drug design, materials science, and AI-driven research acceleration. Accelerating humanity's understanding of the world.
Key Benchmarks
Recent Papers
Neuro-Symbolic Activation Discovery: Transferring Mathematical Structures from Physics to Ecology for Parameter-Efficient Neural Networks
Anas Hajbi
Naiad: Novel Agentic Intelligent Autonomous System for Inland Water Monitoring
Eirini Baltzi, Tilemachos Moumouris, Athena Psalta +2 more
The Persona Paradox: Medical Personas as Behavioral Priors in Clinical Language Models
Tassallah Abdullahi, Shrestha Ghosh, Hamish S Fraser +5 more
WildSci: Advancing Scientific Reasoning from In-the-Wild Literature
Tengxiao Liu, Deepak Nathani, Zekun Li +2 more
MedInsightBench: Evaluating Medical Analytics Agents Through Multi-Step Insight Discovery in Multimodal Medical Data
Zhenghao Zhu, Chuxue Cao, Sirui Han +4 more
From Macro to Micro: Benchmarking Microscopic Spatial Intelligence on Molecules via Vision-Language Models
Zongzhao Li, Xiangzhe Kong, Jiahui Su +8 more
Recent Milestones
Insilico Opens ‘Science Gym’ for Frontier LLMs
On January 22, 2026, Insilico Medicine announced a new ‘Science MMAI gym’ service designed to train general‑purpose LLMs such as GPT and Qwen to perform better on biology and chemistry tasks. The Hong Kong‑listed biotech says its pipeline can boost model performance by up to 10x on key scientific benchmarks using domain datasets, reward models and reinforcement learning.
GPT‑5.2 helps solve long‑standing Erdős problem
On January 18, 2026, Eclipse founder Neel Somani said he used OpenAI’s GPT‑5.2 Pro to solve Erdős Problem #281, a number theory problem open since 1980. Fields Medalist Terence Tao and other mathematicians reviewed and accepted the proof, and OpenAI president Greg Brockman highlighted the result as a major milestone for AI-assisted science.
Merge Labs raises $250M for brain–AI links
Brain‑computer interface startup Merge Labs emerged from stealth with a reported $252 million seed round, led by OpenAI and other investors. Coverage on January 16 highlights the lab’s plan to build high‑bandwidth, largely noninvasive BCIs that integrate tightly with advanced AI systems.
KAIST AI maps B‑ and T‑cell targets for cancer vaccines
A joint team from KAIST and biotech firm Neogenlogic announced an AI model that predicts which tumor neoantigens will trigger robust B-cell and T-cell responses, enabling personalized cancer vaccine design. The model, validated on large genomic and clinical datasets, is described as the first AI framework to jointly model B-cell immunogenicity and T-cell responses, with clinical trials targeted for 2027.
AI Designs Personalized Cancer Vaccines by 2027
On January 2, 2026, a joint team from KAIST and Korean biotech firm Neogenlogic disclosed an AI platform that predicts both B cell and T cell responses to tumor neoantigens to design personalized cancer vaccines. The group says the framework, detailed in a December 3 Science Advances paper, is the first to jointly model B cell immunogenicity for vaccine design and is being readied for an IND filing with the U.S. FDA targeting clinical trials in 2027.
Nobel Prize for AlphaFold
Demis Hassabis and John Jumper awarded Nobel Prize in Chemistry for AlphaFold.
Nobel Prize for Neural Networks
Geoffrey Hinton and John Hopfield awarded Nobel Prize in Physics for foundational neural network work.
AlphaFold 3 Released
DeepMind releases AlphaFold 3, predicting structures of proteins, DNA, RNA, and small molecules.
AlphaGeometry Solves IMO Problems
DeepMind AlphaGeometry solves International Mathematical Olympiad problems at silver medalist level.
Isomorphic Labs Drug Discovery Partnership
Isomorphic Labs announces major pharmaceutical partnerships worth over $3B.