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Sam Altman Says AI Using Too Much Energy Will Require Breakthrough Energy Source
- dexwiz 3y agoThis is my concern with AI in general. Cost, both real and monetary. Right now Microsoft and VCs are dumping money into AI operation to help with growth and adoption. What happens when AI's business focus moves from cost to grow to cost to serve? Will all these business who integrated in AI suddenly be saddled with huge bills? What if your product depends on AI, and suddenly is not profitable to operate? Anecdotally I have already seen people pull back AI features, because it turned out to be too expensive to serve in the long run. I already pay for a GPT subscription, and its reliability is one of the worst of any product I pay for. The novelty keeps me paying, but I can't imagine building a business on it.
- gmerc 3y agoThey will charge the salary of the worker they are replacing with an EC2 style AI simulacrum. Employers will save health, logistics, HR, etc. Governments will have to pay for unemployment Just the same as always - privatize the gains
- riscy 3y agoIn other words, if the people providing the AI demand the same money as the workers it replaces, it doesn't seem like society actually benefits.
- JumpCrisscross 3y ago> if the people providing the AI demand the same money as the workers it replaces, it doesn't seem like society actually benefits Those people no longer have jobs. That sounds bad, but consider they can now do something else. (Ad infinitum this is obviously a problem. But the history of technological development provides cause for optimism in the long run.)
- gmerc 3y agoThe average american has 6 months of savings for unemployment. I don’t think there’s any cause for optimism on that timeline
- JumpCrisscross 3y ago> average american has 6 months of savings for unemployment. I don’t think there’s any cause for optimism on that timeline That's 6 months more than during the agricultural and industrial revolutions. The world isn't great, but it's getting better in the long run.
- s1artibartfast 3y agoI see lots of help wanted signs. 6 days should be be enough.
- dexwiz 3y agoThe majority of Americans live paycheck to paycheck. On average, American's may have sixth months of savings, but that is due to the long tail of wealth distribution. Only about 1 out of 4 of them actually have six months or more of savings.
- jacquesm 3y ago> the history of technological development provides cause for optimism in the long run I think it actually provides cause for pessimism: in the past those people had other kinds of jobs to move to. But this AI revolution makes it much harder to move to another job other than a menial one because a lot of the lower level office jobs are affected all at once. This creates a lot of downward pressure on fields that were already paying peanuts and where employers have realized they can now squeeze even further, either by cutting wages directly or by having more desperate entrants in the race to the bottom. Going from agricultural work into technology was an improvement, going from office work to unskilled labor is a regression. Upward mobility is limited because there is less room there anyway and there too there will be more competition for fewer jobs. So for the moment I don't really see the upside on a societal scale, even if for some individuals there are upsides.
- dathinab 3y agoIt can help if there are simply not enough workers available and it's used to boost productivity of the existing workers. through in most cases it probably will still not work/help society I.e. from what I heard public defendants in the US are notoriously overworked, if an AI could help them auto prepare all the simple straight forward cases they could do a better job. But then this is also a good example for why it probably still will not work out well. As no one will pay for that tool or they will pay for it but then expect so many more cases to be handled that it might get worse instead of better.
- jacquesm 3y agoIndeed it doesn't, and likely it won't. But they'll start off subsidizing it to get the employers hooked. It's always the same pattern.
- cyanydeez 3y agofirst evidence that OpenAI is seriously lowballing it's tech bills and unless there's serious GPU efficiency gains, they're doing ye olde uber dances trying to get their consumers locked in before the price hikes start.
- Dopameaner 3y agoHence, using OpenAI/perplexity everyday, as I am afraid they might start increasing subscriptions after the VC funds dry out.
- BobaFloutist 3y agoAh we've now reached the "We're ready to go except for the magical development in another domain that's already resisted decades of concerted research and is absolutely necessary for what we do to actually make sense" stage. Good to know.
- EA-3167 3y agoThe AI winter is coming, and it's going to be bad. So many promises have been made, to the extent that the average person thinks that AGI is just around the corner.
- hnu234 3y ago[flagged]
- favorited 3y agoEnergy from nuclear fusion is available today – you just need solar panels to capture it.
- ogogmad 3y agoIsn't storage still a problem? I suppose there's batteries and pumped-storage hydro.
- midasuni 3y agoOnly at night. Build 3 data centra and you can provide full solar power to at least one of them at any time, just shift the workload to the resource with the power Or base your DC in a location with lots of other renewable energy
- nuodag 3y agoJust run your AGI during the day and suspend it at night? Also makes it easier to fight when it turns evil
- fulladder 3y agoYes, and there's also a stealth way to capture it if your planet has any type of gaseous atmosphere: take advantage of air currents that arise from the repeated heating and cooling of your atmosphere using a wind turbine.
- JumpCrisscross 3y ago> Energy from nuclear fusion is available today – you just need solar panels to capture it Nitpick: stellar fusion is fundamentally different from thermonuclear fusion. Proton-proton fusion is mediated by the weak force [1][2]. A lump of the Sun radiates less power than your body. It works because there is a lot of Sun. Thermonuclear fusion is far more energetic because it's mediated by the strong force. [1] https://en.wikipedia.org/wiki/Proton–proton_chain https://en.wikipedia.org/wiki/Proton–proton_chain [2] https://en.wikipedia.org/wiki/Beta_plus_decay https://en.wikipedia.org/wiki/Beta_plus_decay
- ogogmad 3y agoHow's analogue computing progressing as a more energy-efficient alternative?
- jacquesm 3y agoNot. Noise would kill it. Your answers would essentially be nonsense.
- ogogmad 3y agoIsn't ML moving towards low-precision floating point anyways?
- jacquesm 3y agoYes, but the whole reason that works is because a chain of such devices is still stable. A chain of analog components will just output random noise if it gets long enough. That's the main reason why digital won out over analog: repeatability even with long chains of computation.
- kuahyeow 3y agoSo AGI will invent fusion, but we need fusion for AGI. Chicken-egg :)
- Zacharias030 3y agoRemember that the chicken and egg problem was eventually solved ;) (Don’t you ask how)
- rightbyte 3y agoIf there is a first chicken, there has to have been an egg with it inside it?
- somewhereoutth 3y agoThis is blockchain all over again isn't it.
- Dopameaner 3y agothis is just not true.
- somewhereoutth 3y ago- lots of hype - technically complex - use cases uncertain - except for crime/spam/other unpleasantness - Nvidia is smiling - cooking the planet seems like it to me!
- Dopameaner 3y agoNot everything that has hype is blockchain. I have some legit usecases for Generative AI, it advanced my productivity across multiple learning areas by at least 2x. Blockchain on the other hand, a pile of wannabe numbers in the air.
- it_citizen 3y agoI have found some legit use cases for generative AI at least.
- nekoashide 3y agoWe have companies like Google and Microsoft who have the ability to build or create power generation for things like this. I just think it's interesting that Microsoft could be energy self sufficient by building generation next to a datacenter.
- cwbrandsma 3y agoat least out west they build near power generation already (usually next to hydro dams). At least that is what I remember them doing, I could be a few years out of date.
- dexwiz 3y agoAmazon is a huge investor in green energy, both solar and wind. Google also buys solar. Colocated energy is great in theory, but doesn't always scale. That is why most companies take an offset approach. https://www.aboutamazon.com/news/sustainability/amazon-renewable-energy-portfolio-january-2024-update https://www.aboutamazon.com/news/sustainability/amazon-renew...
- Dirak 3y agoOne should be suspicious of ulterior motives when the CEO of an AI company makes a claim like this. On one hand, LLMs do require significant amounts of compute to train. But the other hand, if you amortize training costs across all user sessions, is it really that big a deal? And that’s not even factoring in Moore’s law and incremental improvements to model training efficiency.
- pclmulqdq 3y agoThe inference cost is also huge in energy terms, not just the training. Remember that Altman's company builds gigantic models.
- anonylizard 3y agoData centers cost 2% of electricity (Statistics from a few years ago). AI inference is so costly at scale, one can easily see data centers start using 4% of total electricity, and in the next decade 8%. That will start to have severe effects on the power grid, basically require planning many years in advance to setup new power plants and such. "Moore's law and incremental improvements' are irrelevant in the face of scaling laws. Since we aren't at AGI yet, every extra bit of compute will be dumped back into scaling the models and improving performance.
- dathinab 3y ago> is it really that big a deal yes, at least as long as you constantly develop new AI models and you still need to run the models, and e.g. for GPT4 that is alone already non trivial (energy cost/compute wise) through for small LLMs if they are not run too much it might be not that bad --- Generally I would always look for ulterior motives for any "relevant" public statement Sam Altman makes. As history has shown there often seems to be some (through in that usage "ulterior" has a bit too much of a "bad"/"evil" undertone). To cut it short he seem to be invested in some Nuclear Fusion company, which is one of the potential ways to "solve" that problem. Another potential way is to use smaller LLMs but smaller LLMs can also be potentially a way how OpenAI loses their dominant position, as there is a much smaller barrier for training them.
- _sword 3y agoIs this because of actual energy needs? Or because Sam is trying to drive investments into the fusion energy company he's backing?
- _sword 3y agoHe's probably trying to build out a vertically integrated AI conglomerate spanning power, chip fabs, software, etc. And he's great at marketing in the meantime
- jacquesm 3y agoI think both the OpenAI and the Sam Altman brand sustained some damage. He may be great at marketing but now that the gun is on the table and the cloth is withdrawn we'll see how much success he has in the future with trying to wrap people around his fingers.
- dathinab 3y agoprobably both The size some of the large language models have is just insane. To put it into context GPT3 is a Large Language Model (LLM) but GPT4 has like (handwaveing) 5+ times as many parameters. This means the energy cost is also at least that much larger for inference. And if we look at training instead of inference it's a quite a bit more complicated (each iteration is more costly, more parameter can also require more iterations, but at the same time you might need to spend less time in an area of increasingly diminishing returns per iteration), but if we go with GPT3 vs. GPT4 the 5x+ increase of parameters lead to a 10x+ increase in training cost (of which a huge part is energy cost, through also amortized hardware cost; ~10M$ to >100M$). Additionally there are various analysis steps you might do when creating new models which can be hugely (energy) costly. And that is with GPT4 and with OpenAI any major increase in version seem to come with a major increase in parameter size so with that trend we are looking at energy bills in the (potential many) hundreds of million US dollar for training alone. Another thing wrt. inference cost is that with my limited understanding currently the best way to reach AGI and also a lot of other tasks is to run multiple models in tandem. Through this model might be domain adoptions of the same model, so not twice the training cost. --- Domain Adaption == take a trained model and then train it a bit more to "specialize" it on a specific task, potentially adding additional knowledge etc. While you can try to do so just with prompt engineering there a larger prompt comes at a larger cost and a higher chance for unexpected failure, so by in a certain way "burning in" some additional behavior, knowledge etc. you can get nice benefit.
- jacquesm 3y agoWell, if the AI is good enough then ask it to design one. Joking aside: the options are to turn it off or to charge what it should cost and given that no matter what it costs and no matter what the source if it uses too much energy the better solution would be to make it use less energy rather than to look for a breakthrough energy source because that also reduces the climate impact.
- julienchastang 3y agoWell actually: "In a twist, Microsoft is experimenting with generative artificial intelligence to see if AI could help streamline the [nuclear power] approval process, according to Microsoft executives." [0] [0] https://www.wsj.com/tech/ai/microsoft-targets-nuclear-to-power-ai-operations-e10ff798 https://www.wsj.com/tech/ai/microsoft-targets-nuclear-to-pow...
- jacquesm 3y agoThat's edging closer and closer to Douglas Adams 'Reason' software application.
- dathinab 3y agocan't read the article but if it's roughly about what I would expect (and have seen in other fields) the idea is roughly: The final proof reading and decision still is done by humans, but before that automatic feedback AI is used to find things which need to be changed during planing, certification and highlight potential problem. I.e. eliminate as many rounds of back and force between agency and plant builder and in turn save a lot of time. Through if the final proof reading is also done by AI or relies to much on AI this is a huge issue. LLMs fundamentally to their design sometimes (in the future maybe rarely) make mistakes in forms which for humans seem arbitrary, random and absurd (in turn they tend to also not do some of the mistakes humans tend to do). The problem is even if this mistakes become rare they always can be fundamental safety issues.
- boulos 3y agoIt's unfortunate that no math is ever done in these stories. If you take the "350,000" H100s that Facebook wants by EOY, each of those can do 700W, which gives you almost 250 MW for just the GPUs. That sounds like a lot, until you realize that a single large power plant is measured in Gigawatts. All of Google's data centers combined are O(10 GW) which are matched with renewable power offsets [1]. Importantly, the world installed >500 Gigawatts of renewable energy in 2023 [2], mostly driven by PV Solar in China. The amount of potential solar and wind and other renewable-ish (hydro) outstrips even a 10x'ing of a lot of these numbers. But even for a single site, dams like Three Gorges are >20 GW. There are real efficiency and scale challenges in doing AI in a single, large site. But existing power generation systems deliver plenty of power. [1] https://www.gstatic.com/gumdrop/sustainability/google-2023-environmental-report-executive-summary.pdf https://www.gstatic.com/gumdrop/sustainability/google-2023-e... [2] https://www.iea.org/reports/renewables-2023/executive-summary https://www.iea.org/reports/renewables-2023/executive-summar...
- jacquesm 3y agoThe big point of course is that there is massive asymmetry between training and inference and that even inference at scale is going to require massive amounts of energy and that likely OpenAI's business model isn't viable at scale. It works right now because they have capital to burn but when the music stops it may well turn out that their model isn't sustainable at all. Efficiency gains should come first, long before they start looking at alternative energy sources.
- deleted 3y ago[deleted]
- nateglims 3y agoEnergy production capacity in the US is relatively flat for the last couple of decades. The renewable installation is offsetting the decommission of coal. The capacity installed in China is not really accessible to Open AI due to recent security competition (both export restrictions on AI and a desire to import less energy). The capital costs of power are also quite high so I think he is pretty accurate considering the expectations of a startup to hockey stick.
- j45 3y agoMore energy... or differently designed chips? Maybe Apple will have some ideas with the power/performance ratio of their chips compared to what's used in graphic cards.
- bearjaws 3y agoThis is why we need to focus on smaller, more efficient models. A lot of the 13 and 30bn parameter models are actually quite good, maybe not GPT4 but it can run on my M1 MBP without an issue, and a bit faster than GPT4 anyway. I don't need a chat interface that is amazing at all things at once, I need it to be great at 1 subject at a time.
- Alex3917 3y ago> we need better ways to store energy from solar power. Why? I understand that for a normal website you always want to use the closest server possible, but for queries that take 30 seconds on average anyway, why does it matter if you're adding an extra 250ms to get it from the opposite side of the world? If AI can legitimately replace human labor, why would anyone care if it takes an extra few milliseconds?
- JumpCrisscross 3y agoIs this the new PR playbook? Claim to be building something big and dangerous and ready to ruin everything if everyone doesn't drop everything and pay attention to me?
- Animats 3y agoExpect price increases for OpenAI, then. Maybe OpenAI's business model of cheap AI for banal purposes won't work.
- brianolson 3y agoBitcoin is still wasting gigawatts every year, but later blockchains are literally a million times more efficient. If the current generations of AI turn out to be useful, maybe someone will figure it out an efficiency optimization.
- hackermatic 3y agoPeople and governments really need to start asking if the results of the current generation of FAANG-size LLMs are worth the costs, in additional chips, power, and cooling water -- especially in locations that are constrained for any of those resources. Are we getting ten times better Google results for ten times more energy? I don't think so.
- s1artibartfast 3y agoThat question is for the investors to worry about, as long as the public and government aren't the ones footing the bill for compute.
- karim79 3y agoWhat kind of 'AI' is he talking about? The AGI kind? The Superintelligence kind? The chatbot which can't easily be ridiculed using esoteric word incantations kind? I want one which can instantly calculate numberwang[0] and get it right every time [0] https://www.youtube.com/watch?v=6ofnDdi-vfw https://www.youtube.com/watch?v=6ofnDdi-vfw
- iteratethis 3y agoThat's the Big Tech playbook: go towards technology so expensive to run that competition is impossible. Tech that cannot be replicated. And of course the main fuel is our work, our content.
- slowmovintarget 3y ago"Make the pie higher" ~ Sam Altman
- singularity2001 3y agoForemost it will require a nvidia substitute using photonics for matrix multiplications