This weekly roundup thread is intended for all culture war posts. 'Culture war' is vaguely defined, but it basically means controversial issues that fall along set tribal lines. Arguments over culture war issues generate a lot of heat and little light, and few deeply entrenched people ever change their minds. This thread is for voicing opinions and analyzing the state of the discussion while trying to optimize for light over heat.
Optimistically, we think that engaging with people you disagree with is worth your time, and so is being nice! Pessimistically, there are many dynamics that can lead discussions on Culture War topics to become unproductive. There's a human tendency to divide along tribal lines, praising your ingroup and vilifying your outgroup - and if you think you find it easy to criticize your ingroup, then it may be that your outgroup is not who you think it is. Extremists with opposing positions can feed off each other, highlighting each other's worst points to justify their own angry rhetoric, which becomes in turn a new example of bad behavior for the other side to highlight.
We would like to avoid these negative dynamics. Accordingly, we ask that you do not use this thread for waging the Culture War. Examples of waging the Culture War:
-
Shaming.
-
Attempting to 'build consensus' or enforce ideological conformity.
-
Making sweeping generalizations to vilify a group you dislike.
-
Recruiting for a cause.
-
Posting links that could be summarized as 'Boo outgroup!' Basically, if your content is 'Can you believe what Those People did this week?' then you should either refrain from posting, or do some very patient work to contextualize and/or steel-man the relevant viewpoint.
In general, you should argue to understand, not to win. This thread is not territory to be claimed by one group or another; indeed, the aim is to have many different viewpoints represented here. Thus, we also ask that you follow some guidelines:
-
Speak plainly. Avoid sarcasm and mockery. When disagreeing with someone, state your objections explicitly.
-
Be as precise and charitable as you can. Don't paraphrase unflatteringly.
-
Don't imply that someone said something they did not say, even if you think it follows from what they said.
-
Write like everyone is reading and you want them to be included in the discussion.
On an ad hoc basis, the mods will try to compile a list of the best posts/comments from the previous week, posted in Quality Contribution threads and archived at /r/TheThread. You may nominate a comment for this list by clicking on 'report' at the bottom of the post and typing 'Actually a quality contribution' as the report reason.
Jump in the discussion.
No email address required.
Notes -
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.
Compute also complicates the picture a lot. Nvidia has around 80% margins; something like 40% of the LLM serving TCO is paying the Nvidia tax. In a world where compute isn't as speculatively valuable as it is now, that cost decreases a lot; cut Nvidia's margins to a more reasonable 30-40%, and everything becomes much more economic.
A lot of the expense of the AI build out is just speculative bidding by AI labs to get more, faster. And the biggest bag holder from a bubble popping is probably Nvidia itself (with Oracle and SoftBank also having starring roles).
More options
Context Copy link
It also seems a lot more palatable to both current and future investors to say "our product is so cool that THE GOVERNMENT shut us down, so we're still working on it, just more slowly" than to cry uncle first and say "you know what, we can't afford this, we're going to let Sam/Dario take the lead."
More options
Context Copy link
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.
More options
Context Copy link
More options
Context Copy link
More options
Context Copy link