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A decline in search interest outside of academia makes sense. The groups who can get by on APIs don't care so much how the sausage is made and just want to see prices come down. Interested parties have likely already found tools that work for them.
There's definitely some academic interest outside of CS in producing tools using LLMs. I know plenty of astro folks working to build domain specific tools with open models as their backbone. They're typically not interested in more operational work, I guess because they operate under the assumption that relevant optimizations will eventually make their way into public inference engines.
And CS interest in these models will probably sustain for at least 5-10 more years, even if performance plateaus, as work continues into how LLMs function.
All that to say, maybe we're just seeing the trend die for laypeople?
I am only half kidding.
Eg tap water is really, really useful and widely deployed. Approximately every household is a user, and that's unlikely to change. But I doubt you'll find much evidence of that in Google Search trends.
but maybe statistical learning from pretraining is near its limit. not enough data or not enough juice to squeeze more performance out of averages.
though with all the narrow ais it does seem plausible you might be able to cram all what these narrow ais can do in on big goliath model. wonder if reinforcement learning and reasoning can manage to keep the exponential curve of ai going if there are still hiccups in the short term.
the difficulty in just shoehorning llms as they are in any and every day task without a hitch might be behind the temporary hype-dying down trend.
ChatGPT is at it's peak, and something like Claude is still rising.
I think organizing and structuring data from unorganized data from the past is a massive use case that seems heavily underrated by so many right now. People spend a lot of time on figuring out where to find some data, internally in companies, etc.
Finance is a big industry, and they are doing lots of different things.
And I'm not quite sure why you mention determinism in the grandfather comment? Finance people have been using Monte Carlo simulations for ages. (And removing non-determinism from LLMs by fixing the seed of any pseudo-random number generator used wouldn't really change anything, would it?)
There's a lot more to finance outside of that.
I know every segment of finance loves to pretend that's not the case, because their jobs (and high salaries) frequently rely on that not being true (see the subprime mortgage crisis).
You are forgetting all about regulations and taxation (and how to work with / around them). And how to cleverly read documents, and exploit loop holes in contracts.
There's so much more to finance.
(And for eg stocks or commodities, there's not even any notion of defaulting. Defaulting only really makes sense when you have fixed obligations. 'Fixed income' is only one part of finance.)
> (see the subprime mortgage crisis)
That's actually a more nuanced topic than you think. See eg https://kevinerdmann.substack.com/p/subprime-bank-runs-and-t... and other posts by Kevin Erdmann on the topic.