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Sam Altman Desires $7 Trillion

Sam Altman Desires $7 Trillion

2024-02-13 19:13:33

[All numbers listed here are very tough and introduced in a sloppy method. For the extra rigorous variations of this, learn Tom Davidson, Yafah Edelman, and EpochAI)


Sam Altman wants $7 trillion.

In a single sense, this isn’t information. Everybody needs $7 trillion. I would like $7 trillion. I’m not going to get it, and Sam Altman in all probability received’t both.

Nonetheless, the media treats this as worthy of remark, and I agree. It’s a helpful reminder of what it’s going to take for AI to scale within the coming years.

The fundamental logic: GPT-1 value roughly nothing to coach. GPT-2 value $40,000. GPT-3 value $4 million. GPT-4 value $100 million. Particulars about GPT-5 are nonetheless secret, however one extremely unreliable estimate says $2.5 billion, and this appears the correct order of magnitude given the $8 billion that Microsoft gave OpenAI.

So every GPT prices between 25x and 100x the final one. Let’s say 30x on common. Which means we will anticipate GPT-6 to value $75 billion, and GPT-7 to value $2 trillion.

(Until they slap the title “GPT-6” on a mannequin that isn’t a full technology forward of GPT-5. Contemplate these numbers to signify fashions which might be eg as far forward of GPT-4 as GPT-4 was to GPT-3, no matter how they model them.)

Let’s attempt to break that value down. In a really summary sense, coaching an AI takes three issues:

  • Compute (ie computing energy, {hardware}, chips)

  • Electrical energy (to energy the compute)

  • Coaching information


Compute is measured in floating level operations (FLOPs). GPT-3 took 10^23 FLOPs to coach, and GPT-4 plausibly 10^25.

The capability of all of the computer systems on the earth is about 10^21 FLOP/second, so they may prepare GPT-4 in 10^4 seconds (ie two hours). Since OpenAI has fewer than all of the computer systems on the earth, it took them six months. This implies OpenAI was utilizing about 1/2000th of all of the computer systems on the earth throughout that point.

If we hold our 30x scaling issue, GPT-5 will take 1/seventieth of all of the computer systems on the earth, GPT-6 will take 1/2, and GPT-7 will take 15x as many computer systems as exist. The computing capability of the world grows shortly – this source says it doubles each 1.5 years, which implies it grows by an order of magnitude each 5 years, which implies these numbers are in all probability overestimates. If we think about 5 years between GPTs, then GPT-6 will truly solely want 1/tenth of the world’s computer systems, and GPT-7 will solely want 1/3. Nonetheless, 1/3 of the world’s computer systems is so much.

Most likely you possibly can’t get 1/3 of the world’s computer systems, particularly when all the opposite AI corporations need them too. You would want to vastly scale up chip manufacturing.


GPT-4 took about 50 gigawatt-hours of vitality to coach. Utilizing our scaling issue of 30x, we anticipate GPT-5 to wish 1,500, GPT-6 to wish 45,000, and GPT-7 to wish 1.3 million.

Let’s say the coaching run lasts six months, ie 4,320 hours. Which means GPT-6 will want 10 GW – about half the output of the Three Gorges Dam, the most important energy plant on the earth. GPT-7 will want fifteen Three Gorges Dams. This isn’t simply “the world might want to produce this a lot energy whole and you should buy it”. You want the ability fairly near your information middle. Your finest wager right here is both to get a whole pipeline like Nord Stream hooked as much as your information middle, or else a fusion reactor.

(Sam Altman is working on fusion power, however this appears to be a coincidence. No less than, he’s been inquisitive about fusion since at the very least 2016, which is method too early for him to have identified about any of this.)

Coaching Knowledge

That is the textual content or photos or no matter that the AI reads to grasp how its area works. GPT-3 used 300 billion tokens. GPT-4 used 13 trillion tokens (one other supply says 6 trillion). This type of appears to be like like our scaling issue of 30x nonetheless form of holds, however in principle coaching information is meant to scale because the sq. root of compute – so it’s best to anticipate a scaling issue of 5.5x. Which means GPT-5 will want someplace within the neighborhood of fifty trillion tokens, GPT-6 someplace within the three-digit trillions, and GPT-7 someplace within the quadrillions.

There isn’t that a lot textual content in the entire world. You would possibly be capable of get a number of trillion extra by combining all printed books, Fb messages, tweets, textual content messages, and emails. You might get some extra by including in all photos, movies, and films, as soon as the AIs be taught to grasp these. I nonetheless don’t suppose you’re attending to 100 trillion, not to mention a quadrillion.

You might attempt to make an AI that may be taught issues with much less coaching information. This must be doable, as a result of the human mind learns issues with out studying all of the textual content on the earth. However that is laborious and no one has an excellent thought learn how to do it but.

Extra promising is artificial information, the place the AI generates information for itself. This seems like a perpetual movement machine that received’t work, however there are tips to get round this. For instance, you possibly can prepare a chess AI on artificial information by making it play towards itself 1,000,000 occasions. You may prepare a math AI by having it randomly generate steps to a proof, finally stumbling throughout an accurate one by probability, mechanically detecting the proper proof, after which coaching on that one. You may prepare a online game enjoying AI by having it make random motions, then see which one will get the very best rating. Basically you need to use artificial information whenever you don’t know learn how to create good information, however you do know learn how to acknowledge it as soon as it exists (eg the chess AI received the sport towards itself, the maths AI acquired an accurate proof, the online game AI will get a very good rating). However no one is aware of how to do that effectively for written textual content but.

Possibly you possibly can create a wise AI by means of some mixture of textual content, chess, math, and video video games – some people pursue this curriculum, and it really works high-quality for them, type of.

That is form of the odd one out – compute and electrical energy may be solved with a lot of cash, however this one would possibly take extra of a breakthrough.

Algorithmic Progress

This implies “individuals make breakthroughs and change into higher at constructing AI”. It appears to be one other a kind of issues that provides an order of magnitude of progress per 5 years or so, so I’m revising the estimates above down by a little bit.

Placing It All Collectively

GPT-5 would possibly want about 1% the world’s computer systems, a small energy plant’s price of vitality, and loads of coaching information.

GPT-6 would possibly want about 10% of the world’s computer systems, a big energy plant’s price of vitality, and extra coaching information than exists. Most likely this appears to be like like a town-sized information middle connected to loads of photo voltaic panels or a nuclear reactor.

GPT-7 would possibly want the entire world’s computer systems, a gargantuan energy plant past any that at present exist, and method extra coaching information than exists. Most likely this appears to be like like a city-sized information middle connected to a fusion plant.

Constructing GPT-8 is at present unimaginable. Even if you happen to resolve artificial information and fusion energy, and you are taking over the entire semiconductor business, you wouldn’t come shut. Your solely hope is that GPT-7 is superintelligent and helps you with this, both by telling you learn how to construct AIs for affordable, or by rising the worldwide financial system a lot that it may fund currently-impossible issues.

Every part about GPTs >5 is a naive projection of present developments and possibly false. Order of magnitude estimates solely.

You would possibly name this “speculative” and “insane”. But when Sam Altman didn’t imagine one thing at the very least this speculative and insane, he wouldn’t be asking for $7 trillion.

See Also


Let’s again up.

GPT-6 will in all probability value $75 billion or extra. OpenAI can’t afford this. Microsoft or Google might afford it, however it might take a big fraction (perhaps half?) of firm assets.

If GPT-5 fails, or is simply an incremental enchancment, no one will wish to spend $75 billion making GPT-6, and all of this might be moot.

However, if GPT-5 is near human-level, and revolutionizes complete industries, and appears poised to start out an Industrial-Revolution-level change in human affairs, then $75 billion for the subsequent one will appear to be a discount.

Additionally, if you happen to’re beginning an Industrial Revolution degree change in human affairs, perhaps issues get cheaper. I don’t anticipate GPT-5 to be ok that it may deal with the planning for GPT-6. However you’ve acquired to think about this stepwise. Can it do sufficient stuff that giant initiatives (like GPT-6, or its related chip fabs, or its related energy vegetation) get 10% cheaper? Possibly.

The upshot of that is that we’re an exponential course of, like R for a pandemic. If the exponent is > 1, it will get very massive in a short time. If the exponent is < 1, it fizzles out.

On this case, if every new technology of AI is thrilling sufficient to encourage extra funding, and/or sensible sufficient to lower the price of the subsequent technology, then these two components mixed permit the creation of one other technology of AIs in a optimistic suggestions loop (R > 1).

But when every new technology of AI isn’t thrilling sufficient to encourage the huge funding required to create the subsequent one, and isn’t sensible sufficient to assist convey down the worth of the subsequent technology by itself, then sooner or later no one is keen to fund extra superior AIs, and the present AI growth fizzles out (R < 1). This doesn’t imply you by no means hear about AI – individuals will in all probability generate superb AI artwork and movies and androids and girlfriends and murderbots. It simply implies that uncooked intelligence of the most important fashions received’t enhance as shortly.

Even when R < 1, we nonetheless get the larger fashions finally. Chip factories can progressively churn out extra chips. Researchers can progressively churn out extra algorithmic breakthroughs. If nothing else, you possibly can spend ten years coaching GPT-7 very slowly. It simply means we get human or above-human degree AI within the mid-Twenty first century, as an alternative of the early half.


When Sam Altman asks for $7 trillion, I interpret him as wanting to do that course of in a centralized, fast, environment friendly method. One man builds the chip factories and energy vegetation and has all of them good and prepared by the point he wants to coach the subsequent massive mannequin.

Most likely he received’t get his $7 trillion. Then this identical course of will occur, however slower, extra piecemeal, and extra decentralized. They’ll come out with GPT-5. If it’s good, somebody will wish to construct GPT-6. Regular capitalism will trigger individuals to progressively enhance chip capability. Folks will make loads of GPT-5.1s and GPT-5.2s till lastly somebody takes the plunge and builds the large energy plant someplace. All of this can take a long time, occur fairly naturally, and nobody individual or company could have a monopoly.

I’d be happier with the second state of affairs: the safety perspective right here is that we would like as a lot time as we will get to arrange for disruptive AI.

Sam Altman beforehand endorsed this place! He mentioned that OpenAI’s efforts have been good for security, since you wish to keep away from compute overhang. That’s, you need AI progress to be as gradual as doable, to not progress in sudden jerks. And a technique you possibly can hold issues gradual is to max out the extent of AI you possibly can construct along with your present chips, after which AI can develop (at worst) as quick because the chip provide, which naturally grows fairly slowly.

except you ask for $7 trillion {dollars} to extend the chip provide in an enormous leap as shortly as doable! Individuals who trusted OpenAI’s good nature based mostly on the compute overhang argument are feeling betrayed right now.

My present impression of OpenAI’s multiple contradictory perspectives here is that they’re genuinely inquisitive about security – however solely insofar as that’s appropriate with scaling up AI as quick as doable. That is removed from the worst method that an AI firm might be. But it surely’s not reassuring both.

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