Comment by mparis | Hacker News Reader

Comment by mparis | Hacker News Reader

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There will of course be high-flyers whose wings will melt and that will fall back to earth, but don't be so quick to dismiss the teams that are bringing real value to industries that have historically been tricky to make more productive. For every red-hot AI demo that drops promising to change the world, there is some other team using AI to do something that may sound boring, yet is important..

For example, I work in healthcare and its difficult to over-exaggerate how much time it can take to do the most basic things. The people that are tasked with doing those basic things are often highly-educated, highly-skilled, and highly-paid; and it still takes a long time.

I suspect there is an unreasonable amount of cost to shed from doing simple things. Things like:

1. Reading, reasoning over, and copying structured data from lightly-structured, highly variable documents like PDFs.

2. Reducing the amount of time a human sits on hold on the phone. I'm of the opinion the AI doesn't even need to do the talking to deliver huge amounts of value. Just help me help my highly-skilled employees move from high-value task to high-value task without the tedium in the middle.

3. Login and copy basic details from any of the 1000s of healthcare specific websites, each of which does more or less the same thing, slightly differently. RPA has always been so costly to build and maintain. The high variation fan-out just got a lot easier.

In the short term, I'm most bullish on AI to solve these low-value, highly-variable, highly-annoying tasks. I'm also reasonably confident that the AI we have today is already good enough to do it.

Give it time and we'll start to see companies operate at margins that were previously impossible in industries that we thought were near-impossible to make more productive.

It's not that it's not useful at all, it's that the mismatch between the reality (what you described) and hype ("build full-stack AI companies to outcompete human-first ones") is wilder than anything I have seen in my lifetime. It's reminiscent of stories about the dot-com bubble era, which I am not old enough to have seen first hand.

(Maybe a bit less than what you described. It's something I tried and I don't think LLMs can deal with most unstructured data at scale very well.)

The problem with AI isn't that it isn't useful.

Its that, as an industry or business at macro level, it is OBSCENELY overvalued.

Generative AI may be a 50bn business. Or a 25bn, or 75bn.

What it definitely isn't, is a multi-trillion doller game changer thats going to revolutionize the world in ways unheard of; and yet, that seems to be how it is being presented and, more importantly, pitched to VCs and hyperscalers.

That's fair. I don't know what the generative AI industry will end up being worth. Maybe you're right it's only worth 25bn or 75bn. But.. also.. maybe you're missing something. I certainly don't know, but I try to hold a spectrum of possible futures in mind.

I acknowledge your bear case and hear the possibility that it's all hype and the aggregate value of all generative AI (measured in dollars) will be worth less than e.g. the market capitalization of a single company like Uber.

BUT, hear me out. Forgive me, as I fallback to healthcare... The US spent ~$4.9 trillion on healthcare in 2023 alone (according to CMS). That cost is spread out across a lot of things, some of which is work that things like AI can help make more productive, some of which is not applicable to AI. When we are spending nearly ~$5 trillion dollars a year, it does not take a lot on a percentage basis to start seeing really significant dollar values in savings.

It's a story of death by 1000 cuts. I suspect it won't be a big magical fix all at once where AI magically solves healthcare. But we will optimize 1% here and 1% there using focused solutions that actually solve pain points. If someone improves productivity in healthcare by even just 1%, one-time, then we are talking about savings of ~50bn per year.

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