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Only the AI labs are really interested in closed models. Google, Facebook, Microsoft, ... they'd rather go back to doing stock buybacks and being ridiculously p
by cataphract 2mo ago
Only the AI labs are really interested in closed models. Google, Facebook, Microsoft, ... they'd rather go back to doing stock buybacks and being ridiculously profitable rather than raising capital for all this research and datacenters. They only do it because they think they have to.
- mcmcmc 2mo agoThe alternative is ceding the leading edge to China and being dependent on them to continue releasing advances
- skohan 2mo agoIsn't this meta release kind of a counterexample to that?
- chrsw 2mo agoWe did this with manufacturing and industrial build outs over the last 4 decades or so. It worked out very well for capital, not well for labor. One could make the argument we can do the same for AI. Let China build the models and we capture the value somewhere in the layers above. I think that’s a terrible idea but financially it makes just as much sense as offshoring labor and manufacturing, if not more.
- TheOtherHobbes 2mo agoManufacturing was never strategic. (That was irony, by the way.)
- ignoramous 2mo ago> That was irony Sarcasm or irony?
- DrewADesign 2mo agoSo, if they got ahead of us by whatever arbitrary measure someone pretends is objective, then suddenly our stuff… what… stops working? Does it say somewhere in the big book of AI rules that the first entity to beat the US AI companies would be in charge now, and we’d have to stop doing our own research and development and start using their shit exclusively? I don’t get the argument.
- mrDmrTmrJ 2mo agoIf the leading model companies aren't profitable long-term, how do we get the money to continually spend on more research and more compute? I get that plenty of people don't like big corporations or stock buybacks or certain CEOs, which is fine. But as someone who wants to see AGI happen FASTER, I really want to see a clear financial reason for maximal AGI investment. If the model labs aren't clearly profitable, or open source models eat all the 'model layer' profit - what financial force will push forward very expensive experiments/scaling, etc.?
- munk-a 2mo ago> If the model labs aren't clearly profitable, or open source models eat all the 'model layer' profit - what financial force will push forward very expensive experiments/scaling, etc.? It's hype - when the hype dies the great push will slow. My hypothesis is that we'll end up with something like Seti@Home where continued model training gets outsourced to a benevolent appearing product (something like what OpenAI started out as). If I were to bet - Europe and Canada seem best poised (especially the latter) to produce an AGI initiative with a strong ethical focus.
- makingstuffs 2mo agoOut of curiosity why do you want AGI to ‘happen FASTER’?
- failbuffer 2mo agoWhy do you think your life will be better with AGI?
- sanderjd 2mo agoWhat I think is that something the "exponential scaling to AGI" thesis pays too little attention to is resource constraints, and that this is the answer to your question. What will happen if it becomes difficult to sustain the investment of resources necessary to continuously train newer and better models is that the s-curve will start to inflect toward plateau, just like any other technology.
- nradov 2mo agoThat's a non sequitur. While the frontier LLMs are quite useful for many tasks there's no reliable evidence that scaling them up will ever produce a true AGI. More likely some other fundamental research breakthroughs will be needed, and those breakthroughs won't necessarily come from the current leading companies. I doubt that more money would be necessary or even helpful in that.