AI Briefing#microsoft-research
The latest AI and developer news about #microsoft-research, with the original source and a short summary.
The latest AI and developer news about #microsoft-research, with the original source and a short summary.
The edition highlights a proof of the KLS conjecture and a new method, APEC, that reduces coding agent processing costs by up to 25.4%.
The ~50-person research group is ending operations after being reorganized into Microsoft AI, which prioritizes scaling over fundamental research.
A research prototype from Microsoft Research and GitHub Next that shifts review from line-by-line code to plain-language intent, using formal proofs to ensure agent-written Rust code matches specifications.
Walker argues that the 2013-2016 Cyber Grand Challenge relied on expert systems rather than machine learning, and that current AI capabilities have disrupted the traditional balance of offensive scarcity.
BioEmu2, a foundation model for biomolecular structure, is now available in public preview, while new frameworks improve coding agents and weather forecasts.
The system uses a high-level language and compiler to reduce the cost and complexity of creating interactive visualizations with AI agents.
Researchers proved the 1995 Kannan-Lovász-Simonovits conjecture, establishing a dimension-free geometric principle for log-concave distributions.
Magnetar proves RISC-V execution at 7.2 to 8.7 million instructions per second on a laptop using only standard hash functions.
Microsoft Research has released StudentSim, a simulator that mimics individual students' learning patterns, and demonstrated how to use it to validate the instructional quality of AI tutors.
StudentSim outperforms baselines like GPT-5.4 and Maia2 in chess, writing, and math simulations, achieving 90.5% tutor accuracy in reinforcement learning tests.
Microsoft Research scientists Jennifer Neville and Chad Atalla discuss how AI models degrade in multi-turn interactions despite high single-turn benchmark scores, highlighting the need for new evaluation methods and user strategies.
The system provides 30 to 60 minutes of advance warning and detected nearly 80% of major space-weather events during evaluation.
Quine combines a multimodal world model with an interactive harness to prioritize therapeutic compounds, validated in collaboration with the Broad Institute.
MS unveiled Physical AI Toolchain features that offload robotics inference to the edge or cloud, extending battery life by up to 160% and improving performance.
Chris White leads AI security and infrastructure innovation at Microsoft Catalyst Lab after developing dark web search tools at DARPA.
Microsoft Research released Skala 1.1 with improved accuracy and expanded integration with major simulation codes.
CARE-X is presented as a chest X-ray VLM that combines generation and structured prediction.
Microsoft Research unveiled Flint, a chart-generation language for AI agents.
EvoLib is a framework that lets AI agents teach themselves by converting past experiences into reusable skills and insights.
Microsoft Research Asia has unveiled the PIKE-RAG framework to handle complex industrial-site data.
Microsoft Research has released Fara1.5-27B, a multimodal web browser automation agent based on Qwen3.5-27B, on Hugging Face.
Microsoft has unveiled a technique that leverages Rust, Aeneas, and Lean to verify the mathematical integrity of SymCrypt's cryptographic algorithms.
Flint, an open-source visualization language that helps AI agents generate expressive charts, has been released.
SkillOpt optimizes an agent's skills as learnable parameters without modifying model weights, increasing the reliability of its behavior.