Technology

The answer is that it's all about "growth". The fetishization of shareholders has reached its logical conclusion, and now the only value companies have is in growth. Not profit, not stability, not a reliable customer base or a product people will want. The only thing that matters is if you can make your share price increase faster than the interest on a bond (which is pretty high right now).

To make share price go up like that, you have to do one of two things; show that you're bringing in new customers, or show that you can make your existing customers pay more.

For the big tech companies, there are no new customers left. The whole planet is online. Everyone who wants to use their services is using their services. So they have to find new things to sell instead.

And that's what "AI" looked like it was going to be. LLMs burst onto the scene promising to replace entire industries, entire workforces. Huge new opportunities for growth. Lacking anything else, big tech went in HARD on this, throwing untold billions at partnerships, acquisitions, and infrastructure.

And now they have to show investors that it was worth it. Which means they have to produce metrics that show people are paying for, or might pay for, AI flavoured products. That's why they're shoving it into everything they can. If they put AI in notepad then they can claim that every time you open notepad you're "engaging" with one of their AI products. If they put Recall on your PC, every Windows user becomes an AI user. Google can now claim that every search is an AI interaction because of the bad summary that no one reads. The point is to show "engagement", "interest", which they can then use to promise that down the line huge piles of money will fall out of this pinata.

The hype is all artificial. They need to hype these products so that people will pay attention to them, because they need to keep pretending that their massive investments got them in on the ground floor of a trillion dollar industry, and weren't just them setting huge piles of money on fire.

I've ran some college hw through 4o just to see and it's remarkably good at generating proofs for math and algorithms. Sometimes it's not quite right but usually on the right track to get started.

In some of the busier classes I'm almost certain students do this because my hw grades would be lower than the mean and my exam grades would be well above the mean.

The part that is over hyped is companies trying to jump the gun and wholesale replace workers with unproven AI substitutes. And of course the companies who try to shove AI where it doesn't really fit, like AI enabled fridges and toasters.

This is literally the hype. This is the hype that is dying and needs to die. Because generative AI is a tool with fairly specific uses. But it is being marketed by literally everyone who has it as General AI that can "DO ALL THE THINGS!" which it's not and never will be.

Even if they plateaued in place where they are right now it would lead to major shakeups in humanity's current workflow

Like which one? Because it's now 2 years we have chatGPT and already quite a lot of (good?) models. Which shakeup do you think is happening or going to happen?

Computers have always been good at pattern recognition. This isn't new. LLM are not a type of actual AI. They are programs capable of recognizing patterns and Loosely reproducing them in semi randomized ways. The reason these so-called generative AI Solutions have trouble generating the right number of fingers. Is not only because they have no idea how many fingers a person is supposed to have. They have no idea what a finger is.

The same goes for code completion. They will just generate something that fills the pattern they're told to look for. It doesn't matter if it's right or wrong. Because they have no concept of what is right or wrong Beyond fitting the pattern. Not to mention that we've had code completion software for over a decade at this point. Llms do it less efficiently and less reliably. The only upside of them is that sometimes they can recognize and suggest a pattern that those programming the other coding helpers might have missed. Outside of that. Such as generating act like whole blocks of code or even entire programs. You can't even get an llm to reliably spit out a hello world program.

This is easy to say about the output of AIs.... if you don't check their work.

Alas, checking for accuracy these days seems to be considered old fogey stuff.

Goldman Sachs, quote from the article:

“AI technology is exceptionally expensive, and to justify those costs, the technology must be able to solve complex problems, which it isn’t designed to do.”

Generative AI can indeed do impressive things from a technical standpoint, but not enough revenue has been generated so far to offset the enormous costs. Like for other technologies, It might just take time (remember how many billions Amazon burned before turning into a cash-generating machine? And Uber has also just started turning some profit) + a great deal of enshittification once more people and companies are dependent. Or it might just be a bubble.

As humans we're not great at predicting these things including of course me. My personal prediction? A few companies will make money, especially the ones that start selling AI as a service at increasingly high costs, many others will fail and both AI enthusiasts and detractors will claim they were right all along.

Eh, my best coworker is an LLM. Full of shit, like the rest of them, but always available and willing to help out.

Though the image generators are actually good. The visual arts will never be the same after this

"Confidently incorrect" I think describes a lot of AI aficionados.

Some people can only hear "AI means I can pay people less/get rid of them entirely" and stop listening.

I've noticed that the people most vocal about wanting to use AI get very coy when you ask them what it should actually do.

Quantum! don't forget quantum, you filthy peasant.