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Ivan Tashev receives IEEE SPS 2022 Industrial Innovation Award

Awards | Ivan Tashev receives 2022 IEEE SPS Industrial Innovation Award

Ivan Tashev receives 2023 IEEE SPS Industrial Innovation Award 

May 9, 2023

Dr. Ivan Tashev named recipient of the IEEE Signal Processing society “Industrial Innovation Award” for 2022 with citation “For outstanding contributions to microphone array and speech enhancement systems.”

Awards | MIT

2022-23 Morison Prize and Lecture with danah boyd, PhD – “Made, Not Found: Grappling with the Vulnerabilities of Data” 

May 8, 2023

MIT announced danah boyd is the recipient of the 2022-23 Morison Prize in Science, Technology, and Society (STS). The Morison Prize recognizes an outstanding individual who combines humanistic values with effectiveness in practical affairs, particularly in science and technology. danah…

In the news | Microsoft FLAML on GitHub

Surpassing 1 Million Downloads – A Retrospective and a Look into the Future 

May 7, 2023

This week, FLAML has reached a significant milestone: 1 million downloads. Originating as an intern research project within Microsoft Research, FLAML has grown into an open-source library used widely across the industry and supported by an active community. As we…

diagram
Microsoft Research Blog

Using generative AI to imitate human behavior 

May 4, 2023 | Tim Pearce, Tabish Rashid, Anssi Kanervisto, Dave Bignell, Mingfei Sun, Raluca Stevenson, Sergio Valcarcel Macua, Shanzheng Tan, Ida Momennejad, Katja Hofmann, and Sam Devlin

Diffusion models have been used to generate photorealistic images and short videos, compose music, and synthesize speech. In a new paper, Microsoft Researchers explore how they can be used to imitate human behavior in interactive environments.

A diagram in which five newspaper icons are lined up in the middle, the first of which is labeled a. An arrow points from the newspaper to an icon of a person above it. The person is labeled x and has a mouse click icon next to it and a thought bubble with the words “I like this!” that’s labeled r. An arrow points from the mouse click icon to a box labeled “recommender system” under the newspapers.
Microsoft Research Blog

Inferring rewards through interaction 

May 4, 2023 | Jessica Maghakian, Akanksha Saran, Cheng Tan, and Paul Mineiro

In reinforcement learning, handcrafting reward functions is difficult and can yield algorithms that don’t generalize well. IGL-P, an interaction-grounded learning strategy, learns personalized rewards for different people in recommender system scenarios.

Awards | Institute of Mathematical Statistics (IMS)

Lester Mackey named IMS Fellow 

May 4, 2023

Lester Mackey, Principal Researcher, Microsoft Research, has been named Fellow of the Institute of Mathematical Statistics (IMS). Dr. Mackey received the award for deep theoretical work in statistical machine learning with impactful applications.

In the news | The Times of Israel

Microsoft partners with Start-Up Nation Central to tap Israeli agrifood tech 

May 4, 2023

US tech giant Microsoft has partnered with Start-Up Nation Central to help Israeli agrifood tech startups augment their AI-powered models for sustainable farming solutions and get exposure to global markets. Microsoft and Start-Up Nation Central are working together to identify…

GitHub Product Manager Kasia Sitkiewicz and Protocol Labs Research Scientist Petar Maymounkov discuss their collaboration on Gov4git on the Microsoft Research Podcast
Microsoft Research Podcast

Collaborators: Gov4git with Petar Maymounkov and Kasia Sitkiewicz 

May 3, 2023 | Gretchen Huizinga, Petar Maymounkov, and Kasia Sitkiewicz

Collaboration is key to bringing ideas from lab to life. In the first episode of the #MSRPodcast series “Collaborators,” learn how GitHub’s Kasia Sitkiewicz and Protocol Labs’ Petar Maymounkov are teaming up to make open-source collaborative work better.

A flow chart demonstrating the five steps in a self-play pipeline for a language model to improve itself automatically.A self-play pipeline for a language model (LM) to improve itself in a fully automatic manner. First, the LM generates novel puzzles based on a training set of handwritten puzzles. Then, the LM attempts to solve each of these puzzles 100 times. In Step 3, the computer (specifically a Python interpreter) filters the candidate solutions for correctness. Finally, the LM is improved by further training on these verified correct solutions to synthetic puzzles, and the process repeats. This process leads to significant improvements as measured on held-out test puzzles that were also handwritten.
Microsoft Research Blog

AI self-play for algorithm design 

May 2, 2023 | Adam Tauman Kalai and Patrick Haluptzok

Self-play has helped AI systems succeed in games like chess and Go. Can the same method help improve AI programming abilities? Using easy-to-check, hard-to-solve programming problems, researchers show AI can create, solve, and train on its own puzzles.

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