

LLMs have proven time and time again to be a cognitohazard. It just sucks people in like a drug.


LLMs have proven time and time again to be a cognitohazard. It just sucks people in like a drug.


I doubt there will be plentiful fresh water either, in the former situation.


As someone with plans to work in the software dev sector, it’s just bad news no matter what. AI turns out to be magic, no jobs. Industry crashes because of the bubble, no jobs.


Companies have been very forthcoming with their AI use and development, actually.
And you can tell when it starts getting used. Suddenly the UI will be replaced with the ubiquitous Clod™ look. Then the bugs and awful performance start rearing their head. If you use programs, it’s plainly obvious that the quality of software over the last year has plummeted.


That last part isn’t even far off the horizon. The bureaucracy and legal framework already exists — banks and all manner of institutions will unperson you if you get associated with a “terrorist” organization; so all needs is to classify some domestic nonprofit as a terrorist organization, and bam, all involved or who’ve donated become unpersoned.


China has 1 billion more people than the US. And they’re graduating PhDs in STEM at twice the rate.
Frankly, if you don’t expect them to surpass the US in the coming decades, you’d have to be delusional, the numbers bare it out. A billion more people.


We’ve basically got to wait for Anthropic and OpenAI to actually IPO before any of this can get started properly. Once there’s a public expectation for profit from the two biggest AI labs, then the market will start acting against them. We can hope, at least.


Is this substantiated?
At this point for many projects it’s now depressingly, a matter of degree.
As far as public education, yeah Kagi doesn’t have the legal and compliance framework to even attempt. You’d also need to provide an alternative to the whole docs/drive/etc ecosystem.
For like colleges though, I think there’s a more viable path — I can’t see their purely per-seat pricing model working though; and is also the problem I see with their “teams” plan. The better way there is to either provide a hybrid and/or totally ala carte pricing model, one where you pay per seat and also get a number of searches added to the whole plan ($3/seat + 250 searches); and another where you don’t have seats and instead just accumulate searches and pay at the end of the month based on your search volume. Otherwise the upfront $10/user seat costs in their current billing are hard to justify.