Blaise Aguera y Arcas

Blaise Aguera y Arcas

Blaise leads Cerebra, a Google Research organization working on both basic research and new products. Among the team’s public contributions are MobileNets, Federated Learning, Coral, and many Android and Pixel AI features; they also founded the Artists and Machine Intelligence program. Until 2014 Blaise was a Distinguished Engineer at Microsoft, where he worked in a variety of roles, from inventor to strategist, and led teams with strengths in experience design, pro­to­typ­ing, machine vision, augmented reality, wearable com­put­ing and mapping. Blaise has given TED talks on Sead­ragon and Pho­to­synth (2007, 2012), Bing Maps (2010), and machine creativity (2016). In 2008, he was awarded MIT’s TR35 prize.
Authored Publications
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    Towards Generalist Biomedical AI
    Danny Driess
    Andrew Carroll
    Chuck Lau
    Ryutaro Tanno
    Ira Ktena
    Anil Palepu
    Basil Mustafa
    Aakanksha Chowdhery
    Simon Kornblith
    Philip Mansfield
    Sushant Prakash
    Renee Wong
    Sunny Virmani
    Sara Mahdavi
    Bradley Green
    Ewa Dominowska
    Joelle Barral
    Karan Singhal
    Pete Florence
    NEJM AI (2024)
    Large Language Models Encode Clinical Knowledge
    Karan Singhal
    Sara Mahdavi
    Jason Wei
    Hyung Won Chung
    Nathan Scales
    Ajay Tanwani
    Heather Cole-Lewis
    Perry Payne
    Martin Seneviratne
    Paul Gamble
    Christopher Kelly
    Abubakr Abdelrazig Hassan Babiker
    Nathanael Schaerli
    Aakanksha Chowdhery
    Philip Mansfield
    Dina Demner-Fushman
    Katherine Chou
    Juraj Gottweis
    Nenad Tomašev
    Alvin Rajkomar
    Joelle Barral
    Nature (2023)
    LaMDA: Language Models for Dialog Applications
    Aaron Daniel Cohen
    Alena Butryna
    Alicia Jin
    Apoorv Kulshreshtha
    Ben Zevenbergen
    Chung-ching Chang
    Cosmo Du
    Daniel De Freitas Adiwardana
    Dehao Chen
    Dmitry (Dima) Lepikhin
    Erin Hoffman-John
    Igor Krivokon
    James Qin
    Jamie Hall
    Joe Fenton
    Johnny Soraker
    Kathy Meier-Hellstern
    Maarten Paul Bosma
    Marc Joseph Pickett
    Marcelo Amorim Menegali
    Marian Croak
    Maxim Krikun
    Noam Shazeer
    Rachel Bernstein
    Ravi Rajakumar
    Ray Kurzweil
    Romal Thoppilan
    Steven Zheng
    Taylor Bos
    Toju Duke
    Tulsee Doshi
    Vincent Y. Zhao
    Will Rusch
    Yuanzhong Xu
    arXiv (2022)
    A Field Guide to Federated Optimization
    Jianyu Wang
    Gauri Joshi
    Maruan Al-Shedivat
    Galen Andrew
    A. Salman Avestimehr
    Katharine Daly
    Deepesh Data
    Suhas Diggavi
    Hubert Eichner
    Advait Gadhikar
    Antonious M. Girgis
    Filip Hanzely
    Chaoyang He
    Samuel Horvath
    Martin Jaggi
    Tara Javidi
    Satyen Chandrakant Kale
    Sai Praneeth Karimireddy
    Jakub Konečný
    Sanmi Koyejo
    Tian Li
    Peter Richtarik
    Karan Singhal
    Virginia Smith
    Mahdi Soltanolkotabi
    Weikang Song
    Sebastian Stich
    Ameet Talwalkar
    Hongyi Wang
    Blake Woodworth
    Honglin Yuan
    Manzil Zaheer
    Mi Zhang
    Tong Zhang
    Chunxiang (Jake) Zheng
    Chen Zhu
    arxiv (2021)
    Privacy-first Health Research with Federated Learning
    Adam Sadilek
    Dung Nguyen
    Methun Kamruzzaman
    Benjamin Rader
    Stefan Mellem
    Elaine O. Nsoesie
    Jamie MacFarlane
    Anil Vullikanti
    Madhav Marathe
    Paul C. Eastham
    John S. Brownstein
    npj Digital Medicine (2021)
    UIBert: Learning Generic Multimodal Representations for UI Understanding
    Chongyang Bai
    Srinivas Kumar Sunkara
    Xiaoxue Zang
    Ying Xu
    the 30th International Joint Conference on Artificial Intelligence (IJCAI-21) (2021)
    ActionBert: Leveraging User Actions for Semantic Understanding of User Interfaces
    Zecheng He
    Srinivas Sunkara
    Xiaoxue Zang
    Ying Xu
    Lijuan Liu
    Gabriel Schubiner
    Ruby Lee
    AAAI-21 (2020)