I have a lot of thoughts unrelated to the game experiment but more about how these opus/ultra size models can possibly be a financially viable product at scale when it costs $3000 to play 30 simple games. It just seems much much higher than what it would cost to get a human to play 30 rounds
There are plenty of tasks where $100/task is reasonable.
The value of tasks also doesn't correlate to tokens, and as can be seen here you can light a lot of tokens on fire doing nothing useful.
You mean almost like it was super short sighted to do a ton of layoffs when the AI tech is going to cost almost as much, if not more, than the humans it replaced?
Yeah, you don't need Opus level for everything, and sonnet has gotten fairly decent I'm using it more and more, but still for most tasks I'm working with, Opus is the only one that still regularly succeeds.
So if the tech is only useful on the most expensive tier, that's not going to be sustainable for long unless costs and dramatically come down, and fast.
So maybe our CEOs are responding with a lot of foresight and inside information and know that that level of quality is going to be cheap really soon. But barring that, they're going to experience either sticker shock or a slowdown.
I think the real endgame is probably more accurate "models of models" (model routers) that know exactly how to split prompts between expensive frontier and cheap/free local models.
No, why? It was perhaps a bit too long-sighted, because AI is still improving and often not quite there yet.
Though looking at overall unemployment numbers (which are fairly low across the board), the AI layoffs are more of an anecdote than anything else.
(???)
Overall employment is limited by how many people of working age there are in the economy. When tech employment grows faster than that population, the 'non-tech' sector employment shrinks, and that's not a catastrophe either. Vice versa for 'non-tech' growing faster than tech.
The overall unemployment rate in the US has been basically flat-ish since Covid at around ~4%-ish. With some minor wobbles above and below that, but nothing to write home about. (Eg compared to the peak of 2010 at ~10%.)
Other countries have also not seen any AI impact on overall employment numbers. Apart from maybe a data centre building boom, and Taiwan firing on all cylinders to satisfy chip demand.
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Though in any case, my point was that '[doing] a ton of layoffs' isn't necessarily short-sighted.
In other words, if I were a CEO that needed to do layoffs, I'd blame them on AI. Because why the fuck wouldn't I? It's practically a get out of jail free card right now. The big bad AI is the villain, not me!
I suspect $482 was the total cost for all the models, so more like 11 humans.
But still true.
When your model plays, the learnings are captured forever, and enable smaller/cheaper/faster models.
It’s the same principle that makes “invest in research and production” the dominant strategy in most 4X games: compounded interest, but for knowledge and productivity.