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Microsoft Research Forum: New series explores bold ideas in technology research in the era of AI
Microsoft Research Forum (opens in new tab) is a new series of conversations that explore recent advances, bold new ideas, and important discussions within the global research community. Leading Microsoft researchers will share insights into their work, followed by live…
In the news | The Verge
Microsoft LASERs away LLM inaccuracies
During the January Microsoft Research Forum, Dipendra Misra, a senior researcher at Microsoft Research Lab NYC and AI Frontiers, explained how Layer-Selective Rank Reduction (or LASER) can make large language models more accurate.
Besmira Nushi summarizes timely challenges and ongoing work on evaluating and in-depth understanding of large foundation models as well as agent platforms built upon such models at the Microsoft Research Forum.
Dipendra Misra, Senior Researcher at Microsoft Research New York City and AI Frontiers lightning talk presentation at the Microsoft Research Forum.
Panel Discussion: AI Frontiers
Hosted by Ashley Llorens, VP and Distinguished Scientist, Microsoft AI researchers, Sébastien Bubeck, Ahmed Awadallah, and Ece Kamar discuss frontiers in small language models and where AI research and capabilities are headed next.
Abstracts: January 25, 2024
| Gretchen Huizinga, Jordan Ash, and Dipendra Misra
On “Abstracts,” Jordan Ash & Dipendra Misra discuss the parameter reduction method LASER. Tune in to learn how selective removal of stored data alone can boost LLM performance, then sign up for Microsoft Research Forum for more on LASER &…
HoloAssist: A multimodal dataset for next-gen AI copilots for the physical world
| Xin Wang and Neel Joshi
HoloAssist is a new multimodal dataset consisting of 166 hours of interactive task executions with 222 participants. Discover how it offers invaluable data to advance the capabilities of next-gen AI copilots for real-world tasks.
AI Frontiers: The future of scale with Ahmed Awadallah and Ashley Llorens
| Ahmed Awadallah and Ashley Llorens
What’s the driving force behind AI’s recent, rapid progress? Research manager Ahmed Awadallah shares his insights on this, the two-stage approach to training large-scale models, and the need for better model evaluation in this episode of the #MSRPodcast.
Understanding social biases through the text-to-image generation lens
| Ranjita Naik and Besmira Nushi
Gender, race, and age disparities in AI-generated images persist. This AIES 2023 study on text-to-image models shows that even basic prompts can lead to underrepresentation, calling for responsible bias mitigation strategies.