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[–] 3 points 4 hours ago (3 children)

and has fuck all to do with charity

That's what I said?

you absolutely can inspect the weights

Current techniques cannot give you anything close to the level of inspection you can with software. Worse still, techniques of frontier AI labs are moving in the opposite direction with it getting harder to understand over time and less going into things like chain of thought

There also projects like petals for doing distributed training

You always be at a massive disadvantage because of the severally more limited compute available. Additionally, distributed computing not inside the same data center adds massively increased latency

Training a model also does nothing for the environmental side of things and just makes things worse

instead of whinging endlessly as if OpenAI or Anthropic give a flying fuck that some brave lib made yet another ‘AI slop’ comment on a niche social media platform.

That's 100% missing the point. The point is to not encourage more people to use the tool that gives control to Anthropic, OpenAI, etc. Social stigma and pushback is the point. People use things less when it's seen as uncool. Normalizing AI use just means it's going to be used more against your interests

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  • [–] [S] 5 points 4 hours ago* (2 children)

    That’s what I said?

    No, I'm countering what you said by pointing out that there are rational reasons for companies to put models out in the open.

    Current techniques cannot give you anything close to the level of inspection you can with software.

    So, that just means people need to put the work into improving the techniques. That's how problems are solved. Last I looked, models like Qwen are actually becoming easier to understand as the article I linked explains.

    You always be at a massive disadvantage because of the severally more limited compute available.

    Not really because you'd be leveraging a global compute cluster and amortizing the work. But the thing is that it's not even a competition. Local models just need to be good enough to use. The same way my I don't need to have a supercomputer at home for my needs, I don't need a frontier model either. A model like Qwen is already plenty useful, and they will only get better.

    raining a model also does nothing for the environmental side of things and just makes things worse

    That's going to continue to happen regardless of how much whinging you do. The question is whether models will be owned by corps or by the public.

    The point is to not encourage more people to use the tool that gives control to Anthropic, OpenAI, etc.

    You already lost this battle. And on top of that, as you so glibly pointed out in your other reply, an insane amount of money is going into these companies. So these models will obviously continue to be trained and operated. This is the reality:

    What do our findings say about democracy in America? They certainly constitute troubling news for advocates of “populistic” democracy, who want governments to respond primarily or exclusively to the policy preferences of their citizens. In the United States, our findings indicate, the majority does not rule—at least not in the causal sense of actually determining policy outcomes. When a majority of citizens disagrees with economic elites or with organized interests, they generally lose. Moreover, because of the strong status quo bias built into the U.S. political system, even when fairly large majorities of Americans favor policy change, they generally do not get it.

    Normalizing whinging about AI without doing anything productive just means that people who share none of your concerns will be the ones developing it.

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  • [–] 2 points 4 hours ago (1 child)

    I don't think this is a good faith conversation if we are going to continue to call it being massively used against workers and our overall society just "whining". I was going to respond with all the other negative effects on human cognition from AI which do not go away no matter who makes it, but I see little point to continuing this

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