cross-posted from: https://fed.dyne.org/post/822710
Salesforces has entered a phase of public reckoning after senior executives publicly admitted that the company overestimated AI’s readiness
cross-posted from: https://fed.dyne.org/post/822710
Salesforces has entered a phase of public reckoning after senior executives publicly admitted that the company overestimated AI’s readiness
Exactly.
Are we about to witness a technological revolution on the scale of broadband access for the masses? Yes.
Are we in a financial bubble the size of the dotcom and subprime mortages combined? Also yes.
At least with dotcom and mortgages we had an assets bubble that didn’t have a shelf life of 5 years. It’s not like the capacity we are building now will be useful after the end of the decade
The answer to your first question is actually “no”.
I really don’t think AI is going to be anywhere near as influential as you think it will be.
We found a mathematical function which is good enough to be called universal estimator. Even better, our current computation technology is enough to implement these ideas algorithmically and compute in real-enough time. This will allow us to “do first, figure out later” rather than “hard work first, fruits later” approach.
It’s just not magic, so yea we have to find where it makes sense to deploy it and where it doesn’t.
Anecdote: I wasn’t really going for accuracy (we were looking at hidden layers more than the output layer) but the small model I was working with was able to predict cell state (sick with the thing I’m looking for?) from simple RNA assay data with 80-95% accuracy even with all the weird and bizarre regularization functions we were throwing at it.
For some things, it makes sense. For others, we need more research. For the remaining, this is an apple we need oranges.
I think a lot of the hype with AI comes from the sincere shock that throwing more compute at a really simple algorithm resulted in a program that kicked the Turing test’s ass. If we can’t recognize the significance of that, then we must truly have lost our sense of wonder and curiosity.
But the hype is focusing a little too much on the LLM side of things. The real gains are going to come from models that specialize on other kinds of data, especially data that humans are bad at working with.
We kicked the Turing Test’s ass? Ask an LLM for a joke and you’ll see it fail dismally.
lowest-level technical/call support is about the only thing i see, that area where your just waiting/trying to get the customer to shutup and tell you what their actual issue is.