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    Daniel Salz

    Research Engineer at Google Deepmind

    Daniel Salz is a Research Engineer at Google DeepMind with a background in software engineering and machine learning. He joined Google in September 2021 as a Software Engineer in the Perception Team and has since transitioned to a research role at DeepMind.12

    Prior to his current position, Salz worked as a Data Scientist at C3.ai from September 2020 to August 2021. He also held internships at Credit Suisse, Texas Instruments, and Cohere Technologies.1

    Salz completed his education at Stanford University, where he earned both his undergraduate and master's degrees. He received his MS from 2018 to 2020 and his undergraduate degree from 2015 to 2019.2

    In his research career, Salz has contributed to publications in the field of computer vision and language models. He was one of the authors of a paper titled "Scaling Pre-training to One Hundred Billion Data for Vision Language Models," which investigated the potential of pre-training vision-language models on an unprecedented scale of 100 billion examples.34

    Salz's expertise includes image representation learning, which he has been focusing on since 2019.2 His work at Google DeepMind likely involves advanced research in artificial intelligence, particularly in the areas of computer vision and multimodal learning.

    Highlights

    Feb 11 · arxiv.org
    Scaling Pre-training to One Hundred Billion Data for Vision ... - arXiv
    Feb 11 · deepmind.google
    Scaling Pre-training to One Hundred Billion Data for Vision ...
    Jan 1 · research.google
    PaLI: A Jointly-Scaled Multilingual Language-Image Model
    Jan 1 · openreview.net
    Daniel Salz | OpenReview

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    Daniel Salz
    Daniel Salz, photo 1
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    New York, New York, United States