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Google
@GoogleResearch
Impossible? Let’s see. From algorithms to neuroscience to AI, Google Research strives to progress science, advance society & improve billions of people’s lives.
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Joined May 2017
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    Google Research
    Google
    @GoogleResearch
    12h
    Today we present Mobility-Embedded POIs (ME-POIs), a novel mobility-informed framework that improves text-based place representations derived by language models, allowing AI models to understand the aggregate activity rhythms of places over time. More →goo.gle/4xMeO8O
    A conceptual map illustrating human mobility patterns to a specific point of interest. Several colorful figures converge from different directions toward a central blue building marked with a red map pin. Text bubbles next to each figure indicate varying times.
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    Google Research
    Google
    @GoogleResearch
    15h
    Finding clinical signals in large-scale health sensing data streams is quite challenging. We introduce a biomarker discovery framework that pairs hypothesis generation with adversarial validation to discover rigorous digital biomarkers alongside human experts. Read more:
    Overview of the Biomarker Discovery Framework. (a) The system ingests time series data from consumer wearables and clinical labs. (b) A closed-loop architecture orchestrates six phases mirroring the human biomarker prioritization lifecycle. (c) An Orchestrator agent decomposes natural-language research directives into execution plans.
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    Google Research
    Google
    @GoogleResearch
    Aug 18
    We've launched Operation Blue Skies, in partnership with the UK government and aviation leaders, to continue our work addressing the climate challenge of contrails. Learn more in 🧵 from @ymatias, VP, Google & GM, Google Research ⬇️
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    Yossi Matias
    @ymatias
    Aug 18
    Contrails account for roughly one-third of aviation's total climate impact. We are making a major step in our work on mitigating aviation's climate impact with the launch of Operation Blue Skies — the world’s first state-backed trial to avoid contrails at the scale of an entire
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    Google Research
    Google
    @GoogleResearch
    Aug 17
    Today on the blog, we demonstrate the feasibility of a deep learning approach estimating body composition from smartphone photos, to predict insulin resistance with accuracy comparable to DXA scans in a clinical research setting. Read more →goo.gle/4xIGxHj
    Overview of the body composition pipeline and insulin resistance classification. Body composition metrics are first estimated from the pre-trained PhotoScan model, and the body composition features, combined with user demographics are used for insulin resistance classification.
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    Google Research
    Google
    @GoogleResearch
    Aug 12
    Today we discuss knowledge profiling, a behavioral framework that measures both encoding and recall, and use it to examine the underlying bottlenecks of factuality in frontier LLMs. Read more →goo.gle/4wXia92
    Five knowledge profiles that characterize facts.