AI profitability is mathematically impossible
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AI profitability is mathematically impossible
1–10 of 31 posts
Re: AI profitability is mathematically impossible
#2Not convinced. That is a very static view. You would think that the output of AI will be better AI, better energy sources and that will make AI way cheaper in the long run...
It will end up a cheap commodity that is basically free to produce.
Over the long run it is absolutely one of the best investments in projections.
Re: AI profitability is mathematically impossible
#3Not convinced. That is a very static view. You would think that the output of AI will be better AI, better energy sources and that will make AI way cheaper in the long run... It will end up a cheap commodity that is basically free to produce. Over the long run it is absolutely one of the best investments in projections.
"It will end up a cheap commodity that is basically free to produce."
Wouldn't this just mean that hardware manufacturers capture the profits, not hyperscalers?
Re: AI profitability is mathematically impossible
#4Not convinced. That is a very static view. You would think that the output of AI will be better AI, better energy sources and that will make AI way cheaper in the long run... It will end up a cheap commodity that is basically free to produce. Over the long run it is absolutely one of the best investments in projections.
The idea that a GPU being useful for 3 years is insane. There is little to no data to support that
Re: AI profitability is mathematically impossible
#5Not convinced. That is a very static view. You would think that the output of AI will be better AI, better energy sources and that will make AI way cheaper in the long run... It will end up a cheap commodity that is basically free to produce. Over the long run it is absolutely one of the best investments in projections.
Classic story tellers vs people who can quantify.
Story tellers: Full self driving was commonplace already in 2020.
Re: AI profitability is mathematically impossible
#6Why is no one talking about open source models being burned direct to chip and running inference at 10k-15k a second?
OS models close the gap (via distillation) with frontier models, then get burned to chip, then offer commoditized inference via data farms or local plugins.
With thought loops this fast even if the models are less smart they can be self correcting to level them selves up.
Re: AI profitability is mathematically impossible
#7Why is no one talking about open source models being burned direct to chip and running inference at 10k-15k a second? OS models close the gap (via distillation) with frontier models, then get burned to chip, then offer commoditized inference via data farms or local plugins. With thought loops this fast even if the models are less smart they can be self correcting to level them selves up.
> With thought loops this fast even if the models are less smart they can be self correcting to level them selves up.
You can't self-correct a model that's been burned to a chip. That seems like it'd be the main problem with ASIC AI, when everything's changing on a monthly basis, do you want to spend $x00 on a substandard model that'll be obsolete in 3 months, or wait 3 months?
Re: AI profitability is mathematically impossible
#8Why is no one talking about open source models being burned direct to chip and running inference at 10k-15k a second? OS models close the gap (via distillation) with frontier models, then get burned to chip, then offer commoditized inference via data farms or local plugins. With thought loops this fast even if the models are less smart they can be self correcting to level them selves up.
If you burn a model to a chip what happens if there's a better model?
Re: AI profitability is mathematically impossible
#9Why is no one talking about open source models being burned direct to chip and running inference at 10k-15k a second? OS models close the gap (via distillation) with frontier models, then get burned to chip, then offer commoditized inference via data farms or local plugins. With thought loops this fast even if the models are less smart they can be self correcting to level them selves up.
If you burn a model to a chip what happens if there's a better model?
You have a slightly less great model. Depending on your thesis on how fast AI will advance, that might be minimal, or it might be huge. However, "AI is advancing too fast for people to make obvious efficiency improvements economically worth doing" is rather hard to square with "AI is a lie and will never generate profits."
Re: AI profitability is mathematically impossible
#10Why is no one talking about open source models being burned direct to chip and running inference at 10k-15k a second? OS models close the gap (via distillation) with frontier models, then get burned to chip, then offer commoditized inference via data farms or local plugins. With thought loops this fast even if the models are less smart they can be self correcting to level them selves up.
If you burn a model to a chip what happens if there's a better model?
I had the same question.
I wondered if it'd be possible to use a rewritable chip or a socketed chip...