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[–] 12 points 11 months ago (12 children)

This is peak bubble type news. AI is becoming rapidly more energy efficient. These events will be looked back on like pets.com reaching hundreds of millions and then dying.

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  • [–] 15 points 11 months ago (10 children)
  • [–] 4 points 11 months ago*

    Sometimes. As a tool, not an outsourced human, oracle, or some transcendent companion con artists like Altman are trying to sell.

    See how grounded this interview is, from a company with a model trained on peanuts compared to ChatGPT, and that takes even less to run:

    …In 2025, with the launch of Manus and Claude Code, we realized that coding and agentic functions are more useful. They contribute more economically and significantly improve people’s efficiency. We are no longer putting simple chat at the top of our priorities. Instead, we are exploring more on the coding side and the agent side. We observe the trend and do many experiments on it.

    https://www.chinatalk.media/p/the-zai-playbook

    They talk about how the next release will be very small/lightweight, and more task focused. How important gaining efficiency through architecture (not scaling up) is now. They even touch on how their own models are starting to be useful utilities in their workflows, and specifically not miraculous worker replacements.

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  • [+] -1 points 11 months ago (5 children)
  • [–] 2 points 11 months ago

    One example is it reviews code a lot better than human beings. It’s not just finding obvious errors but it catches logical error that no human would have caught.

    No, it does not.

    Source: Open-source contributor who's constantly annoyed by the useless CodeRabbit AI that some open source projects have chosen to use.

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  • [–] 2 points 11 months ago (2 children)

    It’s not just finding obvious errors but it catches logical error that no human would have caught.

    I'm not having the same experience.

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  • [–] -1 points 11 months ago (1 child)

    Maybe reconsider which model you're using?

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  • [–] 1 point 11 months ago* (last edited 11 months ago)

    And how many errors is it creating that we don't know about? You're using AI to review code but then someone has to review what the AI did because they fuck up.

    If humans code something, then humans can troubleshoot and fix it. It's on our level. But how are you going to fix a gigantic complicated tangle of vibe code that AI makes and only AI understands? Make a better AI to fix it? Again and again? Just get the AI to code another system from scratch every month? This shit is not sustainable.

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  • [–] -2 points 11 months ago (2 children)

    Yes, as far as scalability, cheaper more efficient models can be used in applications which require thousands of uses a day.

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