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- Hacker News
- Honestly, this is just the inverse of them all getting hyped on AI replacing all the jobs. Between both of these positions, RTO, crypto, VR, it's really shown just how much they're trend chasers.
Only a Tech CEO speaks in absolutes, it seems.
by Macha - Text-only, no Javascript, no ads/tracking:
curl http://assets.msn.com/content/view/v2/Detail/en-in/AA27hbnR \ |grep -o "<p>.*</p>" \ |tr -d '\134' \ |sed '1s/^/<meta charset=utf-8>/' > 1.htm firefox ./1.htm #links 1.htm - In case anyone else read the "flipped on" as "flipped the switch on" rather than "reversed course on", no, it's the latter.by kerblang
- I kind of wish there was a way to flip the script on the companies that gave up on humans and tried to switch to AI. Make them suffer for their idiocy in the same way that workers suffered or continue to suffer.
If that makes me a bad person, fine. If a few CEO's wind up working at 7-11 to make rent money, all the better.
- My read has been that a lot of leaders were trying to drive “being early” as the catalyst for future success. At the complexity scale of big orgs you’re mostly fiddling with the incentives that the system self-aligns toward. Firing a bunch of people does create an incentive to use AI, if you think it’ll help.
The more pernicious effect I’ve been seeing is that we’re living in the golden age of LLMs, but eventually that’ll fade. Tokens are subsidized and cheap, model capabilities leap forward regularly, and there’s competition driving it all. But even now there’s stories about frontier models suddenly becoming less capable, or providers switching to usage-based billing, and new model releases feel a bit more sluggish and less dramatic. (Fable/Mythos notwithstanding.)
Eventually the models are going to settle into a rut of being just “good enough” to earn a living rather than all this hoopla. A lot of people will be re-hired. And we’ll do it all again for the next wave.
by cgearhart - by openquery
- This is all noise. The leaders of these companies are flip-flopping to whatever sounds best for their current agenda - hiring, fundraising, pre-IPO, etc.
The only thing that matters is if LLMs with sufficient scaling can become frontier AI researchers kicking off the exponential. Everything else is transient noise.
by openquery - > The only thing that matters is if LLMs with sufficient scaling can become frontier AI researchers kicking off the exponential. Everything else is transient
As long as the term “AI” means by-and-large LLMs with additional features sprinkled on top, the answer is no. More likely (without careful vetting by the folks aggregating these models) is that the quality will go down as more and more AI-generated output gets subsumed into these models.
Even without that particular problem, LLMs-as-AI can only give us probabilistic outputs based on inputs; and by definition they’re reliant on humans to provide the training data for their model. Without specialized knowledge or training on that knowledge (And even with it, viz. Meta’s engineering), we don’t have to worry about AI itself. We do have to worry what investors who are looking for outsized returns will do to get those returns, job market be damned.
The problem for us isn’t that AI will take our jobs; it’s that snake-oil salesmen can sell the idea that AI will take our jobs, investors buy into it, companies try it, fire their folks, the snake-oil salesmen IPOs, the companies that bought into this idea implode in some form or fashion, and the salesmen have already taken the money and ran. Of course, we still lose our jobs, but maybe (!) we get them back when this all fails?
by gortok