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Is There Real Anti-Trust Risk From A Coordinated AI Lab Pause?
In AI-pause discussions it is increasingly common to hear the "anti-trust" objection. The idea is that if the labs were to coordinate a pause in frontier AI development, this would be a "conspiracy in restraint of trade" and therefore illegal.
Putting aside the question of whether it is ethical to risk a double-digit chance of destroying the world in order to avoid getting sued (it isn't), is this even a realistic possibility? My impression is that anti-trust law in the United States is legitimately quite fuzzy (as the NCAA is currently discovering).
Putting my cards on the table, I think this argument is cope. The labs want to pretend that they want to pause, but they don't actually want to pause. "If she wanted to, she would," etc. Just today, Anthropic put out a new statement containing the following sentence:
It seems like every time I read a statement from them, they've added more and more qualifications. Are they going to keep racing until congress passes a specific anti-trust exemption? That arguably seems like what the word "lawful" is implying.
Perhaps I am too cynical but the call for government coordination seems like an obvious attempt to build themselves a moat in a largely moatless space. My own experience has been the cost of model switching is near 0. Approximately all the agents, skills, whatever I've used in my job work pretty seamlessly for any of the underlying models. Some have their quirks but essentially all of them are good enough.
"We the current frontier mousetrap makers think it should be ILLEGAL for anyone to build a better mousetrap faster than we can, for the good of humanity."
The moat is the trillion or so that's already been spent on a technology that can't turn a profit. VC is getting close to tapped out, and it's unlikely that some upstart company is going to get access to the compute necessary to make any kind of impact at this stage of the game. The only possible exception would be a company that can demonstrate that the huge compute requirements can be made more reasonable by more efficient coding algorithms, but as long as the focus is on building more impressive shit there isn't going to be much call for that. It's kind of like the auto industry in the late 60s, when gas was cheap enough that automakers cared more about increasing horsepower or the size of a luxury land yacht than fuel efficiency. They could theoretically build more efficient cars and indeed had at the start of the decade, but there wasn't much call for something like the Ford Falcon by the end of the decade.
The difference here is that the bigger, more powerful models had higher profit margins than the more basic models, and the basic models still made money through volume. AI is in a situation where most people are getting it for free, and the few paying customers are getting steep discounts. And those customers screamed earlier this year when the companies started charging the true cost and sent them a bill at the end of the month. So now you're in the double predicament of needing to ask VC for money so that you can build a more efficient model that does essentially the same thing as the current models, which also aren't profitable. It's not like they can make the money back by charging less, because the prices people are paying are completely untethered from the cost of providing the service.
My own cynical view is that they want a pause because they require tens of billions per year just to stay solvent, and the investors who are putting up this money are getting to the point where they are going to start expecting some kind of return on their investment, not more tin cup rattling because the 60 billion that they needed last year has turned into 100 billion they'll need this year. One gets the sense that VC is completely held hostage to AI companies because they're in so deep that throwing good money after bad at least has the possibility of returning a profit, whereas cutting their losses now would obliterate their entire investment. It's like the old bromide about how if you owe the bank $100,000 the bank owns you, but if you owe them $100,000,000 you own them.
You are almost entirely right but you are missing the connection: there is one possible way to make huge profits - just stop the R&D. Right now a majority of resources (compute + engineers) are actually being spent on R&D for the next big model in the AI race. If they can just pause model development instead of burning it on competing in the race, they'll be profitable immediately. Obviously this cannot be a unilateral decision, if you are the only frontier lab ceasing R&D, then no one will be using your model after six months and you'll make no more money.
Yeah. Each model comes close to making back its investment in a few months. Then a newer model gets released before it can actually "break even", it lasts a few months, and the cycle repeats.
Also, the more efficient models already exist: The Sonnet/Mini/Flash tier is cheaper and only months behind the Opus/[non-specified]/Pro tier. It only seems like a lot because AI progress speeds are wild.
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