Project Silica introduces new techniques for encoding data in borosilicate glass, as described in the journal Nature. These advances lower media cost and simplify writing and reading systems while supporting 10,000-year data preservation.
By decoupling how agents work from how they’re trained, Agent Lightning turns each step an agent takes into data for reinforcement learning. This makes it easy for developers to improve agent performance with almost zero code changes.
Datacenter memory and network limits are restraining AI system performance. MOSAIC uses microLEDs and a wide-and-slow optical architecture to deliver faster, longer, more reliable, and energy efficient connections that could transform AI cluster designs.
In this issue: New research on compound AI systems and causal verification of the Confidential Consortium Framework; release of Phi-4-reasoning; enriching tabular data with semantic structure, and more.
In this issue, we examine a new conversation segmentation method that delivers more coherent and personalized agent conversation, and we review efforts to improve MLLMs’ understanding of geologic maps. Check out the latest research and other updates.
Metasurfaces explore engineered 2D materials that manipulate electromagnetic and mechanical waves, offering advances in wireless tech. They can power indoor GPS, extend 5G/6G coverage, and enable wireless sensing and imaging.
Advances in low-bit quantization techniques enable efficient operation of LLMs on resource-constrained edge devices. Discover how innovations like T-MAC, Ladder, and LUT Tensor Core improve computational efficiency and enhance hardware compatibility.
In this issue: A new approach to multimodal pretraining for remote sensing; Managed-retention memory for the AI era; Improving detection of macular telangiectasia type 2; Generalizing symbolic automata.
Can a new SOS-RMT protocol enable more efficient CL-MPC?; A fair-by-design, cloud-based algorithmic trading platform; LLM2CLIP unlocks richer visual representation; New technique enhances Low-Rank Adaptation’s expressiveness, generalization capabilities.
Holistic motion-capture calibration technique without calibration, manual intervention or custom hardware; Research on AI agents for autonomous clouds; Automating proof-oriented program construction; One-to-many testing for natural language code generation.
Sophisticated side-channel attacks present new security challenges for cloud providers. Learn how Microsoft is exploring defenses against emerging attacks with principled microarchitectural isolation:
Building resilient systems, scaling deep learning computation, and reproducing failures in production are just some of the ways Microsoft researchers are advancing the state of the art in computer systems research at SOSP 2024.
Meet our community of researchers, learn about exciting research topics, and grow your network
Ongoing conversations at the cutting edge of research
Join us for a continuous exchange of ideas about research in the era of general AI
