MatterGen: Property-guided materials design
The central problem in materials science is to discover materials with desired properties. MatterGen enables broad property-guided materials design.
The central problem in materials science is to discover materials with desired properties. MatterGen enables broad property-guided materials design.
Advanced prompting technologies for LLMs can lead to excessively long prompts, causing issues. Learn how LLMLingua compresses prompts up to 20x, maintaining quality, reducing latency, and supporting improved UX.
Explore the latest AI innovations aiming to advance the software development lifecycle. AdaptivePaste adapts and refines pasted code snippets in an IDE. InferFix automates bug detection and repair. Discover how.
Research Focus: Using LLMs in a Rust-based formal verification framework; Rethinking network measurements with user feedback; 3D telemedicine using HoloportationTM communication technology could enhance overseas surgical visits.
Many patients in low- and middle-income countries rely on facilitated online health communities for information and support. Discover how large language models can assist the facilitators and boost outcomes.
ASL Citizen is the first crowdsourced sign language dataset, advancing the state of the art in sign recognition. The web-based project captured input from people in real-world settings, and from a diverse group of experts, including Deaf team members.
PwR uses domain-specific languages to bridge communication between developers and AI tools. Learn how it can help simplify code creation and enhance software reliability and customization, no matter your coding expertise.
Microsoft Chief Scientific Officer Eric Horvitz explains how new prompting strategies can enable generalist large language models like GPT-4 to achieve exceptional expertise in specific domains, such as medicine, and outperform fine-tuned specialist models.
This research paper is being presented at the 2023 Conference on Empirical Methods in Natural Language Processing (opens in new tab) (EMNLP 2023), the premier conference on natural language processing and artificial intelligence. In recent years, AI has been increasingly integrated into healthcare, bringing about…
A new deep-learning compiler for dynamic sparsity; Tongue Tap could make tongue gestures viable for VR/AR headsets; Ranking LLM-Generated Loop Invariants for Program Verification; Assessing the limits of zero-shot foundation models in single-cell biology.
At Microsoft, we’re expanding AI capabilities by training small language models to achieve the kind of enhanced reasoning and comprehension typically found only in much larger models.
Lifelong model editing fixes mistakes discovered after model deployment. This work could expand sequential editing to model properties like fairness and privacy and enable a new class of solutions for adapting LLMs over long deployment lifetimes.
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