Multimodal radiopathomics model predicts postoperative metachronous liver metastasis in gastric cancer
In locally advanced gastric cancer, a substantial number of patients relapse with liver metastasis months after an apparently curative operation, and standard tumor staging offers…
Benchmarking biomedical foundation models
A transparent evaluation and proof of reproducibility, generalization and replicability of algorithms are the bedrock of method development in computational biology. Many benchmar…
Embedding AI in biology — part 2
Artificial intelligence is rapidly changing the landscape of how biological data are acquired and analyzed. Almost no corner of biological research has been left untouched.
Assessment of the Japanese national examination for pharmacists using locally fine tuned large language models
Locally deployable large language models (LLMs) offer advantages in data security and customization, making them particularly useful in domains that handle sensitive information.…
Skin lipid chemistry influences host-microbiome-pathogen interactions in snake fungal disease (ophidiomycosis)
Within host-microbiome-pathogen systems, the host chemical microenvironment is often overlooked despite its inherent role in host physiology. We used a multifaceted experimental a…
NucleicBERT interprets RNA sequence space through self-supervised language modelling
Much of the human genome’s non-protein-coding fraction acts directly through RNA, yet the structural and functional roles encoded in these sequences remain poorly understood. Appl…
End-to-end deep learning methods for genetic risk prediction of schizophrenia
Schizophrenia is a highly heritable psychiatric disorder with a complex genetic basis. While recent GWAS and whole exome sequencing studies have identified numerous risk loci, exi…
Unsupervised discovery of functional sequence patterns from protein language model with MotifAE
Protein language models (pLMs) learn sequence patterns at evolutionary scale, but these patterns remain inaccessible within these “black box” models. To discover them, we develope…
What clinicians should know about how large language models reason
Large language models give a convincing impression of reasoning but can introduce meaningful errors into clinical notes, assessments and care plans, with potentially negative cons…
Human judgment in AI-assisted dermatology
Nature Sensors - Human judgment in AI-assisted dermatology
AI research papers and lab updates — page 1
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Transfer learning for genomic prediction in underrepresented populations
A connectomics milestone: Mapping the complete male fruit fly brain
Mapping global methane emissions from space with deep learning
TimesFM-3: A zero-shot foundation model for multivariate forecasting
Planetary prediction engine: Automating global models via Earth AI
GlucoFM: Foundation model for continuous glucose monitoring
Introducing WeatherNext 3, our most advanced and accurate global weather AI model
WeatherNext 3, our most advanced global weather AI model, is now in Search, Gemini, Maps, Google Maps Platform, and Cloud.
Proactive cyber defense for governments and enterprises
The Fairwind Program is a limited access program for governments and trusted partners to use our cyber defense tools.
Introducing Gemini 3.8 Flash and 3.8 Flash Cyber
Gemini 3.8 Flash and 3.8 Flash Cyber deliver next-generation intelligence for agentic workflows and cybersecurity.
Introducing agentic video understanding with Gemini
We’re launching agentic video understanding across our latest Gemini models for improved accuracy and lower costs and token usage.
Gemini Omni 1.1 Flash lets you build with more control
Gemini Omni 1.1 Flash brings a new suite of creative controls and generative video capabilities to developers.
Piloting the world's first double-blind AI evaluations
Building trust in proprietary model benchmarks using cryptographically secure environments
Intelligent transcription with Gemini 3.5 Transcribe
Now you can get more intelligent speech-to-text transcription with Gemini 3.5 Transcribe.
Live from ICM 2026: What Is Math For in the Age of AI?
In this special live recording from the International Congress of Mathematicians in Philadelphia, July 2026, the central question discussed was what do mathematicians really value…
In an Age of AI, a Physicist Seeks What Endures
Sarah Demers, chair of the physics department at Yale University, sees the potential for large language models to both help and harm her field.
Genome Duplication Is a Radical Evolutionary Gamble
By doubling their entire genome, organisms can evolve extremely rapidly — or they can lose it all. New studies reveal how to survive the high-risk, high-reward evolutionary event.
‘Stunning’ Percolation Proof Solves Decades-Old Puzzle About Phase Transitions
Mathematicians found that a broad class of networks will abruptly shift behavior past a critical point.
Does Computer Science Need Computers?
The theoretical side of the field doesn’t require computing machines. But many questions would never have been posed without them.
From MIT to IBM, expediting AI and quantum deployment
MIT affiliates engage with the MIT-IBM Computing Research Lab to bring rigorous theory to production systems in reinforcement learning and AI agents, quantum machine learning, and…
System helps humans predict when self-driving cars will make mistakes
The CW-Net technique explains the behavior of an autonomous vehicle, using concepts a human can easily understand. Researchers found these explanations helped drivers predict how…
Walter Torous named executive director of MIT Center for Real Estate
MIT Senior Lecturer Walter Torous has been appointed executive director of MIT Center for Real Estate. He will lead teaching, fundraising, and events while directing the MSRED pro…
Ila Kumar: Innovating with communities
MIT PhD student Ila Kumar works alongside young people who have gone through the child welfare system, to reimagine how technology can support healing, connection, and independenc…
MIT Quantum Initiative launches postdoctoral fellowship program
The MIT Quantum Initiative has launched a postdoctoral fellowship program supporting interdisciplinary research across quantum computing, sensing, materials, simulation, and netwo…
How an MIT research project became a global programming language
Julia, the programming language that originated as a research project at MIT, has gained a loyal following among scientists, engineers, mathematicians, and others. The free and op…
Looking beyond natural sequences
A machine-learning framework developed by MIT biologists aims to improve the success rate of computational protein design while moving away from results that reproduce sequences f…
AI helps design new materials that work in the real world
MIT researchers added a new component to AI models that design new materials, helping ensure the material will be stable and practical for real-world use. The “CrysVCD” approach c…
From MIT to IBM, expediting AI and quantum deployment
MIT affiliates engage with the MIT-IBM Computing Research Lab to bring rigorous theory to production systems in reinforcement learning and AI agents, quantum machine learning, and…
System helps humans predict when self-driving cars will make mistakes
The CW-Net technique explains the behavior of an autonomous vehicle, using concepts a human can easily understand. Researchers found these explanations helped drivers predict how…
Walter Torous named executive director of MIT Center for Real Estate
MIT Senior Lecturer Walter Torous has been appointed executive director of MIT Center for Real Estate. He will lead teaching, fundraising, and events while directing the MSRED pro…
Looking beyond natural sequences
A machine-learning framework developed by MIT biologists aims to improve the success rate of computational protein design while moving away from results that reproduce sequences f…
REFACTOR-VLA: Unsupervised Library Learning of Typed Motor Programs
Most current vision-language-action (VLA) models—such as OpenVLA, π0, RT-2, and RDT-1B—are “monolithic.” This means they generate raw motor…
Agent Seer: Synthesizing Scenarios from Specification Understanding
Evaluating AI agents that use external tools requires realistic test scenarios that capture how practitioners compose tools and iterate…
LLMs Are Not (Consistently) Bayesian: Quantifying Internal (In)consistencies of LLMs’ Probabilistic Beliefs
Modern AI systems are being deployed in complex domains such as medicine, science, and law, where there is often not a single correct answer…
From Preferences to Principles: Rubric-Based Alignment for Grounded Knowledge Answers
Designing effective reward signals for open-domain question answering is challenging because high-quality responses must simultaneously…
BenchMIRT: What are LLM benchmarks actually measuring?
BenchMIRT is a new method for auditing LLM benchmarks question by question, revealing which capabilities they actually measure and helping researchers build smaller, more focused,…
The hard parts of AI-assisted science
At an Ai2 event marking our expanded collaboration with Providence Swedish, researchers explored the hardest problems in AI-assisted science: keeping systems steerable, grounded i…
Ai2 and Providence Swedish Cancer Institute partner to advance AI-assisted scientific discovery
Ai2 and Providence Swedish Cancer Institute are expanding their collaboration after AutoDiscovery helped researchers uncover and validate a promising new immune signal in invasive…
Developing provably correct Rust code with Verus
Amazon uses the open-source Verus tool to mathematically prove the correctness of critical Rust code, including key components of the Nitro Isolation Engine.
When LLM judges agree, should we believe them?
Discounting the opinions of LLM judges with highly correlated outputs ensures that panels of judges reflect a true diversity of perspectives.
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