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Discussion (21 Comments)Read Original on HackerNews
The author also talks about advances like smartphones as though they arrived without significant challenges or trade-offs. Every major technological shift has come with some cost, e.g environmental, shortages, investments.
I'd argue most things are difficult to scale in the beginning. Just because today's LLMs are expensive and resource intensive doesn't mean the technology is fundamentally flawed, it may simply mean the current approach isn't the one we'll end up with. But naturally, someone working on another approach would have something to criticise about others.
Finally, I'm not convinced by the claim that we're "stuck" with LLMs just because they're heavily marketed. They create value for many people, which is why they've been adopted so quickly. As the author points out, investors care about economics. I'm sure people would listen if someone developed a cheaper/more sustainable technology that delivered the same value.
A lot of that adoption is completely useless crap tho. Like ai in vacuum cleaner that ads absolutely nothing useful to anything. AI buttons intentionally at places I randomly click at, so that I am forced to open it. Google search that defaults to ai, so that we have to use it after then nerfed real search.
There are useful usages of LLMs. But huge bulk of the adoption is companies realizing they wont get investors money if they dont add ai button, it does not have to be useful.
Wrote about this recently (from a vibe coding perspective) [1]. This applies to corporations, too, as they're betting their futures on fewer engineers, more AI.
[1] https://graybearding.bearblog.dev/they-got-something-on-the-...
It’s worth remembering that during the industrial revolution in Britain, the fastest growing country the world had ever seen, most people were in abject poverty. This tech revolution might end up being worse.
I shouldn't have to explain the benefits of productivity improvements and computer technology to people on Hacker News, but the place for some reason has been hijacked by neo luddites from Reddit that apparently have nothing better to do than troll about AI on a web site that is literally dedicated to an industry they don't like. Sam Altman literally used to run Y Combinator. Why not use that energy you're wasting to adopt emerging technology instead of bashing it?
There are places that recognized manufacturing was going to go away, transitioned a service economy, and did well economically, and places that ignored reality and are now in disrepair. Now's a great time to decide if you want to be Seattle or Cleveland. Don't fight the future. And don't think it's a billionaires fault when certain places are more successful then others because they didn't ban AI and datacenters while other places squandered the opportunity because they didn't confront the pitchfork mob driven into a frenzy by yellow journalism.
Wow, you just solved economics!
Your argument is so incredibly reductive as to be nonsensical. The understanding of the allocation of capital is seemingly below grade school level. Even moreso, your understanding of the business cycle and how it interacts with governments and banks seems to be even more immature.
"manufacturing" didn't "go away", it moved to China so investors could capitalize on lax environmental laws and cheap labor. This engineered trade off of wealth had devastating results to massive parts of the US. On top of that, not every city can become Seattle. There isn't enough 'service economy' to go around and do that, especially as technology tends to concentrate wealth.
Being concerned about how AI will concentrate power doesn’t mean I don’t think it’s extremely useful.
Why is the primary tech people impulse to disrupt, destroy and harm other industries? Maybe that is why we dont produce useful tech anymore. The primary impulse is always hostile, rarely something like "lets create and sell a useful thing for them".
> adopt emerging technology when it comes into play (like for example when the Internet came into play) and use it to start your own company, or make yourself more productive,
Funny, the strategy of creating a company entirely dependent on mercy of another company, vulnerable to destruction with any simple change in TOS has been criticized on HN previously.
yes, in traditional venture you want cost per marginal user to decrease and leverage your platform at scale
but improving llms shifts the frontier of their capability and unlocks entirely new use cases. so far, every mega training run has resulted in a model that has paid itself off profitably fully loaded. perhaps the TAM of intelligence has no ceiling?
not to say that we shouldnt be investing in efficient models, but the efficiency comes after we create another mega shoggoth that we can make more efficient
The alternative is that there will always be problems, and we could spend as much as possible trying to compute solutions, but they will not be found.