Nvidia's Jensen Huang: 'China is going to win the AI race,'

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• colourlesspony@pawb.social ⁨1⁩ ⁨day⁩ ago

  He just wants to sell chips to china is what I got from that article.

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  • Makeitstop@lemmy.world ⁨1⁩ ⁨day⁩ ago

    What, do you expect him to settle for having a company that’s only worth 5 trillion dollars?

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  • rafoix@lemmy.zip ⁨1⁩ ⁨day⁩ ago

    Yeah, he’s desperate to have the US allow him to legally sell the high end GPUs directly to Chinese customers as opposed to the current system they use with lots of middlemen.

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• Assassassin@lemmy.dbzer0.com ⁨1⁩ ⁨day⁩ ago

  Despite funneling a huge chunk of the US GDP into it? Kinda feels like maybe AI is a scam, then.

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  • pennomi@lemmy.world ⁨1⁩ ⁨day⁩ ago

    Money doesn’t solve problems. Engineers solve problems. America is throwing too much money at hardware and not enough at people.

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• ninjabard@lemmy.world ⁨1⁩ ⁨day⁩ ago

  Let them? That way they’re holding the bag when it implodes.

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• Archangel1313@lemmy.ca ⁨1⁩ ⁨day⁩ ago

  How do you “win” a tech / investment bubble? Is it a race to see whose economy implodes first?

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  • AnarchistArtificer@slrpnk.net ⁨1⁩ ⁨day⁩ ago

    You win by acknowledging that AI/Machine Learning research has existed long before this bubble existed, and is continuing to happen outside of that bubble. Most of what we call AI nowadays is based on neural networks (that’s what Geoffrey Hinton and others got a recent nobel prize for), but that’s not the only way to go about the problem, and for years now, there have been researchers pointing out problems like hallucinations and diminishing returns from increasing the amount of data you feed to a model.

    An example of one such researcher is Song Chun-Zhu, who has recently moved back to China because he was finding it increasingly difficult to do research he wanted (i.e. outside of the current AI bubble) within the US. That linked article is a bit of a puff piece, in that it is a tad too mythologising of him, but I think he’s a good example of what productive AI research looks like — especially because he used to work on the “big data” kind of AI, before realising its inherent limits and readjusting his approach accordingly.

    He’s one of the names that’s on my watch list because even for people who aren’t directly building on his research, he comes up a lot in research that is also burnt out on neural nets

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• Casino2306@lemmy.zip ⁨1⁩ ⁨day⁩ ago

  One problem with this “race”. There is no finish line.

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  • onlinepersona@programming.dev ⁨1⁩ ⁨day⁩ ago

    AGI is the finish line, for them and humanity.

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