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TaskWeaver: A code-first agent framework for efficient data analytics and domain adaptation

Garnet: an open-source, next-generation, faster cache-store for accelerating applications and services

GenAI for Industry - AI-generated image compilation of industrial blueprints from renewable energy to transporation and manufacturing

Injecting New Knowledge into Large Language Models via Supervised Fine-Tuning

Enhanced autoscaling with VASIM: Vertical Autoscaling Simulator Toolkit

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Published Date

Podcast

NeurIPS 2024: The co-evolution of AI and systems with Lidong Zhou

December 17, 2024

Just after his NeurIPS 2024 keynote on the co-evolution of systems and AI, Microsoft CVP Lidong Zhou joins the podcast to discuss how rapidly advancing AI impacts the systems supporting it and the opportunities to…

Illustrated headshots of Lidong Zhou and Eliza Strickland

Microsoft Research Blog

Moving to GraphRAG 1.0 – Streamlining ergonomics for developers and users

December 16, 2024 | Nathan Evans, Alonso Guevara Fernández, Joshua Bradley

GraphRAG helps advance AI use in complex domains like science. Thanks to enthusiastic adoption and community engagement, we’ve upgraded the pre-release version. Check out the major ergonomic and structural updates in GraphRAG 1.0.

GraphRAG blog hero - cluster of small circular nodes on a blue/green gradient background

Publication

Extensible Query Optimizers in Practice

Bailu Ding, Vivek Narasayya, Surajit Chaudhuri

Published by Foundations and Trends® in Databases | December 2024, Vol 14

Publication

REDSTONE: Curating General, Code, Math, and QA Data for Large Language Models

Yaoyao Chang, Lei Cui, Li Dong, Shaohan Huang, Yangyu Huang, Yupan Huang, Scarlett Li, Tengchao Lv, Shuming Ma, Qinzheng Sun, Wenhui Wang, Furu Wei, Ying Xin, Mao Yang, Qiufeng Yin, Xingxing Zhang

December 2024

Publication

Microsoft New Future of Work Report 2024

Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le

MSR-TR-2024-56 | December 2024

Published by Microsoft

Project Project

Publication

Balance Reward and Safety Optimization for Safe Reinforcement Learning: A Perspective of Gradient Manipulation

Shangding Gu, Hong Cheng, Hang Dong, Bo Qiao, Si Qin, Qingwei Lin 林庆维

December 2024

Project

Extensible Query Optimizers in Practice: Errata and Updates

This page contains errata and updates to the Foundations and Trends in Databases article titled: “Extensible Query Optimizers in Practice” by Bailu Ding, Vivek Narasayya, Surajit Chaudhuri.

Publication