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date: '2023-01-22T11:07:18'
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hypothesis-meta:
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created: '2023-01-22T11:07:18.838647+00:00'
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document:
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title:
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- Who Owns the Generative AI Platform? | Andreessen Horowitz
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id: 771i6ppEEe2RxNtz0udwZw
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links:
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html: https://hypothes.is/a/771i6ppEEe2RxNtz0udwZw
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incontext: https://hyp.is/771i6ppEEe2RxNtz0udwZw/a16z.com/2023/01/19/who-owns-the-generative-ai-platform/
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json: https://hypothes.is/api/annotations/771i6ppEEe2RxNtz0udwZw
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permissions:
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admin:
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- acct:ravenscroftj@hypothes.is
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- group:__world__
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update:
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- acct:ravenscroftj@hypothes.is
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tags:
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- ai
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- generative ai
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- gpu
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target:
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- exact: Other hardware options do exist, including Google Tensor Processing Units
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(TPUs); AMD Instinct GPUs; AWS Inferentia and Trainium chips; and AI accelerators
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from startups like Cerebras, Sambanova, and Graphcore. Intel, late to the
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game, is also entering the market with their high-end Habana chips and Ponte
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Vecchio GPUs. But so far, few of these new chips have taken significant market
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share. The two exceptions to watch are Google, whose TPUs have gained traction
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in the Stable Diffusion community and in some large GCP deals, and TSMC, who
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is believed to manufacture all of the chips listed here, including Nvidia
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GPUs (Intel uses a mix of its own fabs and TSMC to make its chips).
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prefix: ' top AI chip startups combined.
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'
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Infrastructure is, in other wor'
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source: https://a16z.com/2023/01/19/who-owns-the-generative-ai-platform/
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text: Look at market share for tensorflow and pytorch which both offer first-class
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nvidia support and likely spells out the story. If you are getting in to AI you
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go learn one of those frameworks and they tell you to install CUDA
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updated: '2023-01-22T11:07:18.838647+00:00'
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uri: https://a16z.com/2023/01/19/who-owns-the-generative-ai-platform/
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user: acct:ravenscroftj@hypothes.is
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user_info:
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display_name: James Ravenscroft
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in-reply-to: https://a16z.com/2023/01/19/who-owns-the-generative-ai-platform/
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tags:
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- ai
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- generative ai
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- gpu
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- hypothesis
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type: annotation
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url: /annotations/2023/01/22/1674385638
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---
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<blockquote>Other hardware options do exist, including Google Tensor Processing Units (TPUs); AMD Instinct GPUs; AWS Inferentia and Trainium chips; and AI accelerators from startups like Cerebras, Sambanova, and Graphcore. Intel, late to the game, is also entering the market with their high-end Habana chips and Ponte Vecchio GPUs. But so far, few of these new chips have taken significant market share. The two exceptions to watch are Google, whose TPUs have gained traction in the Stable Diffusion community and in some large GCP deals, and TSMC, who is believed to manufacture all of the chips listed here, including Nvidia GPUs (Intel uses a mix of its own fabs and TSMC to make its chips).</blockquote>Look at market share for tensorflow and pytorch which both offer first-class nvidia support and likely spells out the story. If you are getting in to AI you go learn one of those frameworks and they tell you to install CUDA
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