Whatever you think of AI for your own work, the fact that the entire economy is betting everything on it is really concerning. It’s not just the fact that it may not work well economically speaking and would end up with a market crash, or all the negative externalities from AI development, it’s also the opportunity cost we are paying. With so much human capital and resources dedicated to developing and running LLMs all the other business, research opportunities aren’t being explored and invested in

I prefer that scenario to the one we had before where too many smart people were building out social networks and similar services trying to maximize ad impressions. We are still dealing with the consequences…

> With so much human capital and resources dedicated to developing and running LLMs all the other business, research opportunities aren’t being explored and invested in

It probably feels this way if you only see headlines like this, but the LLM companies and even extending into their data center buildouts are still only a part of the economy. Investment dollars get spread around far and wide. Investors can’t even get allocations in these companies if they want to because they’re so oversubscribed.

This headline and website are a good example. If you think being a YC founder is rare and reserved for the truly elite, you may not have seen the size of YC batches lately. The number of YC founders is in the tens of thousands. Showing a list of 100 of them who joined a couple big tech companies doesn’t mean anything by itself.

It’s on the order of 1% of YC founders. YC startups don’t work out all the time and their employees and founders go work for other startups. Barely worth noting, if not for a website making it look like a big deal.

I fear another related possibility. With *so* much money on the table, if this new industry shrinks or collapses, it is hard to believe that it will collapse same way dot-com did, and instead investors will seek to protect their capital who knows at what cost. Given the influence they have it is not hard to imagine the impact on policies, etc. I fear that tax payers are not the winners in either case, whether this industry grows or not.

I don’t really buy the opportunity cost argument. The bets we are placing look EV-positive to me.

The 90th percentile upside is way, way higher than is priced into the current stocks, the 10th percentile looks to me like 2000 where a bunch of investors loose their shirts and then for the next few decades new companies boom on all the infrastructure that was built.

The “failure mode” for this tech is that we don’t advance much beyond Sol/Fable and the existing models just get cheaper. If there is an AI bust in hindsight it likely will look like the dotcom bust did, which is a small blip on the decades-scale GDP curve.

> Whatever you think of AI for your own work, the fact that the entire economy is betting everything on it is really concerning. It’s not just the fact that it may not work well economically speaking and would end up with a market crash, or all the negative externalities from AI development, it’s also the opportunity cost we are paying.

It's worth pointing out that "entire economy is betting everything on [AI]" you're talking about here is in the economy in the "numbers go up sense" (e.g. the stock market). It's not the economy in the providing for the general well being sense (e.g. gives people jobs so they can get housing and food).

at the current pace, LLMs are the researchers

the end goal isnt to serve a chatbot to replace google or a coding agent to build crud

Tech != the entire economy

Moonshots are concerning until you consider the alternative.

AI is the one and only possibility for saving millions (likely billions) of lives from “old age”, cancers, Alzheimer’s, ALS… you name it.

It’s a big bet. The alternative is we all die anyway: sadly after a gradual decline at best or horribly after long undignified suffering at worst.

I’ll take the economic risk.

Researchers are increasingly using LLMs and other transformer based AI. My friend at a well known research institution asked Anthropic for access to their biology model (not sure if it's Mythos or some other sort of uncensored model) and recently made breakthroughs with it and other AI.

I also think this is a huge problem in government. A lot of government services could be digitized via simple CRUD API/UIs and instead politicians talk about AI...

I know Ed Zitron is a dirty word on HN most days but having recently read some of his (highly editorialized) work… it seems like he’s right and the numbers just aren’t making sense.

Combine that with the fact that “good enough” is a real thing and cheap Chinese models are either there or close depending on your use case and it’s hard to see how this ends well.

Sunk cost fallacy is already too established for anything else.