I’m almost shocked this spooked the market as much as it did, as if the market was so blind to past technological innovation to not see this coming.
Innovation ALWAYS follows this path. Something is invented in a research capacity. Someone implements it for the ultra rich. The price comes down and it becomes commoditized. It was inevitable that “good enough” models became ultra cheap to run as they were refined and made efficient. Anybody looking at LLMs could see they were a brute forced result wasting untold power because they “worked” despite how much overkill they were to get to the end result. Them becoming lean was the obvious next step, now that they had gotten pretty good to the point of some diminishing returns.
sure, but what nobody expected how QUICKLY the efficiency progress has been - aviation took about 30 years to progress from "the rich" to "everybody", personal computers about 20 years (from 1980s to 2000s), I think the market expected to have at least 10 years of "rich premium" - not 2 years and get taken to the cleaners by the economic archenemy, China
The Google transformer paper was 2017. ChatGPT was the “we can give a version away of this for free.” Llama was “we can afford to give away the whole product for free to even the playing field.” Every tech giant comes out with a comparable product simultaneously. And now a hedge fund, not even a megacap company, can churn out a clone by hiring a small or medium size engineering team.
Really this should be an indictment of corporate bloat, having hundreds of thousand headcount companies distracted by performance reviews, shareholders, marketing, rebuilding the same product they launched two years ago under a new name.
>Really this should be an indictment of corporate bloat, having hundreds of thousand headcount companies distracted by performance reviews, shareholders, marketing, rebuilding the same product they launched two years ago under a new name.
Yeah.
There are some shorter words or acronyms for it though, roughly equivalent to your about 30-word paragraph above:
IBM
DEC
Novell
Oracle
MS
Sun
HP
...
MBA
, all in their worse days or incarnations or ...
The notion I now believe more fully is that the money people - managers, executives, investors and shareholders - like to hear about things in units they understand (so money). They don't understand the science, or the maths and in so much as they might acknowledge it exists it's an ambient concern: those things happen anyway (as far as they can tell), and so they don't know how to value them (or don't value them).
Because we saw, what a week ago the leading indicator that the money people were now feeling happy they were in charge which was that weird not-government US$500 billion investment in AI announcement. And we saw the same being breathlessly reported when Elon Musk founded xAI and had "built the largest AI computer cluster!"...as though that statement actually meant anything?
There was a whole heavily implied analogy going on of "more money (via GPUs) === more powerful AIs!" - ignoring any reality of how those systems worked, their scaling rules or the fact that inferrence tended to run on exactly 1 GPU.
Even the internet activist types bought into this, because people complaining about image generators just could not be convinced that the Stable Diffusion models ran locally on extremely limited hardware (the number of arguments where people would discuss this and imply a gate while I'm sitting their with the web GUI in another window on my 4 year old PC).
I would generally agree, but the market isn't rational about the future prospects of a company. It's rational about "can I make money off this stock" and nothing else matters in the slightest.
Riding hype, and dumping at the first sign of issues, follows that perfectly well.
Innovation ALWAYS follows this path. Something is invented in a research capacity. Someone implements it for the ultra rich. The price comes down and it becomes commoditized. It was inevitable that “good enough” models became ultra cheap to run as they were refined and made efficient. Anybody looking at LLMs could see they were a brute forced result wasting untold power because they “worked” despite how much overkill they were to get to the end result. Them becoming lean was the obvious next step, now that they had gotten pretty good to the point of some diminishing returns.