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Mountain Geek

@mountaingeek76.bsky.social did:plc:7fa5m7hmpf6226plhjfy3zui

Professional: Principal Engineer Deep Learning Training CPU Design (Intel and Nvidia) Fun: Outdoors, Volleyball, Fishing, Mountain Climbing, Cycling Disclosure: I work at Nvidia, they don't speak for me and I don't speak for them.

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Mountain Geek (@mountaingeek76.bsky.social) est sur Bluesky depuis le 20 novembre 2024. Le compte a 81 abonnés, suit 295 comptes et a publié 93 posts.

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  • Diane Doyle@dianedoyle44.bsky.social

    I do NOT want to go back. The return of those diseases would also cause many women to exit the workforce since they'd be stuck home long term to care for their children with those diseases.

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  • pdhsu.bsky.social@pdhsu.bsky.social

    Great, but what can it do? Evo 2 is a generalist model that can predict the pathogenic effects of human genome variants across coding and noncoding mutations In other words, if you have a genetic mutation, Evo 2 has an opinion on whether or not it might cause disease

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  • pdhsu.bsky.social@pdhsu.bsky.social

    This was an insane team effort between Arc and Nvidia that convened machine learning and computational biology researchers across Stanford, UC Berkeley, and UCSF. Especially grateful to Jensen Huang for his belief and support of this vision and labor of love, and the entire Evo 2 team below

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  • George Takei@georgetakei.bsky.social

    Brave yourselves for more of the like.

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  • TechCrunch@techcrunch.com

    Jensen Huang says the performance of Nvidia's AI chips is advancing faster than historical rates set by Moore’s Law, the rubric that drove computing progress for decades. “Our systems are progressing way faster than Moore’s Law,” Huang told TechCrunch. Read more here: tcrn.ch/4fUmwnL

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