AI agents often fail because their instructions, or skills, are manually modified with no guarantee of improvement. Learn how SkillOpt turns skill editing into a training process, making agent behavior more reliable without changing model weights. The post SkillOpt: Agent skills as trainable parameters appeared first on Microsoft Research.
AI agents can't remember past conversations. They must constantly reload or retrieve context, which grows less efficient as tasks get longer and more complex. Memora solves this with a scalable memory system separating what’s stored from how it's retrieved. The post Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity appeared first on Microsoft Research.
Researchers introduce generative causal testing, which translates black box models into clear hypotheses and verifies them in the scanner, revealing what specific brain regions respond to in language. The post Understanding the brain with AI-driven explanations and experiments appeared first on Microsoft Research.
Talos was built to help resolve a major bottleneck in genomic medicine: human review time. The open-source system recovered 90% of in-scope diagnoses while surfacing just 1.3 candidate variants per patient for expert review. The post Talos: Scaling rare disease diagnosis with automated, iterative genomic reanalysis appeared first on Microsoft Research.
Project Ire examined a timely malware sample and determined its intent through reverse engineering—identifying LOTUSLITE characteristics even as most major EDR tools did not detect it. The post Ire identifies another LOTUSLITE specimen appeared first on Microsoft Research.
—Introduction of various research papers on new models, including a neuro-symbolic framework for counterfactual explanations and discrete diffusion language models for interactive text generation.
—Development of Object Aligner for optimizing LLM prompts and enhancing JSON schema similarity scores.
Research
—Multiple papers addressing challenges in reinforcement learning, programming by example, and multi-agent systems for improved forecasting.
—Studies on multilingual TTS evaluation, Bayesian learning for hardware impairments, and the robustness of programming by example systems.
Tools
—New GitHub repositories like promptdiff for version control of LLM prompts and agent-replay for debugging AI agent execution.
—Agents-control-tower for monitoring multiple AI agents in a single terminal environment.
Discussion
—Japan's top court ruling that AI cannot be listed as an inventor on patent applications sparked significant online discussion.
—Ongoing debates about the implications of LLMs watching videos and the absence of LLM code in dependencies, highlighting concerns about AI safety and transparency.