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Jensen Huang says Nvidia engineers should use AI tokens worth half their annual salary every year to be fully productive (www.tomshardware.com)
submitted 7 months ago by to c/technology@lemmy.world
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You're not productive if you don't use a lot of AI, says guy who makes all of his money selling AI hardware

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[–] 0 points 7 months ago

The database was an arbitrary example. A more relevant example would be tenserflow layers in a neural network. As I understand it, you can in some cases get a novel solution to a problem just by choosing a smart enough combination, with the right data.

ChatGPT absolutely knows how to help doing the grunt work setting up the tenserflow configuration, following your directions.

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  • [+] 3 points 7 months ago
    [removed by mod]
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  • [–] 0 points 7 months ago (-1 children)

    If used by an expect developer, then the combinations are not just random "lucky" choices.

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  • [–] 1 point 7 months ago*

    If you are capable of giving good directions...

    I'm probably not arguing with you, and I'm not trying to regardless. You seem like you have tried this, watched it happen, go "huh, neet!" And then get it to take the next step in whatever you were doing in the first place only to find out you didn't provide adequate requirements for your config.

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  • [–] 1 point 7 months ago* (last edited 7 months ago)

    Well, yes, that is a central point.

    I am a senior programmer. LLMs are amazing - I know exactly what I want, and I can ask for it and review it. My productivity has gone up at least 3-fold, with no decrease in quality, by using LLMs responsibly.

    But it seems to me that some people on social media just can't imagine using LLMs in this way. They just imagine that all LLM usage is vibe coding, using the output without understanding or review. Obviously you are very unlikely to create any fundamentally new solutions if you only use LLMs that way.

    only to find out you didn’t provide adequate requirements for your config.

    Senior programmer. I know exactly what I want. My requirement communicated to the LLM are precise and adequate.

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