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AI profitability is mathematically impossible
- aatd86 3mo agoNot 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.
- bwestergard 3mo ago"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?
- RetroTechie 3mo agoProbably. Selling gear to shovel gpus into datacenters is gonna be profitable for a while, no matter how this pans out.
- vablings 3mo agoThe idea that a GPU being useful for 3 years is insane. There is little to no data to support that
- u1hcw9nx 3mo agoClassic story tellers vs people who can quantify. Story tellers: Full self driving was commonplace already in 2020.
- aatd86 3mo agoNo one claimed that. Besides negativity is a self-fulfilling prediction. And investing is not accounting...
- Tryk 3mo ago"I think we will be feature complete — full self-driving — this year,” Musk said. “Meaning the car will be able to find you in a parking lot, pick you up and take you all the way to your destination without an intervention, this year. I would say I am of certain of that. That is not a question mark.” -Elon Musk (2019) https://www.cnbc.com/2019/02/19/elon-musk-tesla-will-have-all-its-self-driving-car-features-by-the-end-of-the-year.html https://www.cnbc.com/2019/02/19/elon-musk-tesla-will-have-al... https://en.wikipedia.org/wiki/List_of_predictions_for_autonomous_Tesla_vehicles_by_Elon_Musk https://en.wikipedia.org/wiki/List_of_predictions_for_autono...
- aatd86 3mo agoThat is not my claim. And to be fair the claim about fsd wasn't completely wrong. It is still has failure modes but you can't argue that the tech works. Mercedes even had demos. That is still irrelevant to my initial point.
- jv22222 3mo agoWhy 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.
- saulpw 3mo ago> 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?
- jv22222 3mo agoJust talking about longer deep thought loops. You can do a LOT of deep thought at 15k a second and it still feels super fast. Side note: I really believe in this technology if anyone building this happens to be reading this and is looking for help give me a shout.
- david_shi 3mo agoIf you burn a model to a chip what happens if there's a better model?
- scarmig 3mo agoYou 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."
- nosioptar 3mo agoI had the same question. I wondered if it'd be possible to use a rewritable chip or a socketed chip...
- aesthesia 3mo agoThere are some glaring local errors that make this analysis less than trustworthy. For instance, an assumption that corporate income tax applies directly to revenue, or a supposedly generous assumption that GPUs will fully depreciate after 3 years (6-year-old A100s are still in very high demand!). I would love to read a really well thought through investigation of inference costs and how they relate to token pricing, but I have low confidence that this is it.
- aesthesia 3mo agoOh, just noticed one other very significant error: they evaluate revenue using input token pricing while counting capacity using generated tokens per second. There's a big gap between input and output token pricing, and between prefill TPS and generation TPS.
- anamax 3mo ago> GPUs will fully depreciate after 3 years (6-year-old A100s are still in very high demand!) Depreciation is a tax thing. While it is supposed to track useful life, it almost never does. For example, houses are depreciated on a 28-year schedule. I'm typing this from a house built in 1902.... Google has yet to decommission any of its Trilliums, and the V1s shipped in 2015. The prices to rent V2 (2017) and later are on https://cloud.google.com/tpu/pricing https://cloud.google.com/tpu/pricing .
- aesthesia 3mo agoYep, in their analysis depreciation meant "get no useful work out of the GPU after this point," though.
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- tim333 3mo agoThe analysis seems iffy. As with most industries it's like: Cost of producing service X Revenue coming Y Whether X>Y or not is mostly down to how much competition drives the price down. At the moment prices are down due to an investment fueled land grab but that could change.
- itskamran 3mo ago100 percent....i agree on it.....its more difficult for businesses using AI...