Microsoft Research Lab – Asia
뉴스 & 기능
Jiang Bian discusses how generative AI transforms industries by bridging gaps between AI capabilities and sector needs. He will showcase domain-specific foundation models and versatile AI agents, setting new industry standards.
| Jiang Bian, Adam Fourney, Tanuja Ganu, Daniela Massiceti, Jacki O'Neill, Sunayana Sitaram, 그리고 Tian Xie
In this forum episode, researchers dive into the importance of globally inclusive and equitable AI, share updates on AutoGen and MatterGen, explore novel use cases for AI, and more.
뉴스에서 | IEEE Spectrum
1-bit LLMs Could Solve AI’s Energy Demands
“Imprecise” language models are smaller, speedier—and nearly as accurate. Large language models, the AI systems that power chatbots like ChatGPT, are getting better and better—but they’re also getting bigger and bigger, demanding more energy and computational power. For LLMs that…
“If life is a marathon, then health is the key to its duration.” Health is not only the foundation of happiness and societal progress but also a pivotal aspect of the intelligent era. AI’s integration into healthcare represents a transformative…
Deciding between fundamental and applied research is a dilemma that confronts many in the scientific community. Dongqi Han, on the cusp of graduation, ambitiously aspired to bridge this divide by pursuing both avenues of research in his future endeavors. After…
뉴스에서 | Business Wire
PKSHA harnesses RetNet to develop the first Japanese-English LLM
PKSHA Technology Inc. has developed one of the first Japanese-English Large Language Models (LLM) using Retentive Network (RetNet) in collaboration with Microsoft Japan Co., Ltd. Through this LLM development, PKSHA will further enhance the practicality of generative AI in the…
뉴스에서 | PIM-DL: Expanding the Applicability of Commodity DRAM-PIMs for Deep Learning via Algorithm-System Co-Optimization
Microsoft at ASPLOS 2024: Advancing hardware and software for high-scale, secure, and efficient modern applications
PIM-DL is the first deep learning framework specifically designed for off-the-shelf processing-in-memory (PIM) systems, capable of offloading most computations in neural networks. Its goal is to surmount the computational limitations of PIM hardware by replacing traditional compute-heavy matrix multiplication operations…
