Anthropic's IPO prospectus shows AI vision, surging costs
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Unofficial Hacker News client; not affiliated with Y Combinator.
Anthropic's IPO prospectus shows AI vision, surging costs
Unofficial Hacker News client; not affiliated with Y Combinator.
2ss · · focus · HN ↗
-LLMs profoundly change society -The LLM business is mangled in terms of ROIC vs CoC
Such a business already exists - airlines.
This nuance is what many here refuse/find difficult to understand.
CoolestBeans · · focus · HN ↗
runarberg · · focus · HN ↗
The two things being true may as well be: LLM will not be transformative and the LLM business is mangled in terms of ROIC vs CoC.
In fact given the behavior of AI companies, I actually consider it more likely then not that the effects of the technology is severely over-hyped. I for one do not trust the words of the people who mangle their business in terms of ROIC and CoC. Why should I?
CookieCrisp · · focus · HN ↗
runarberg · · focus · HN ↗
If this the criteria we are using form something being transformative, then being transformative is truly unremarkable in this context, to the point of being a distraction.
CookieCrisp · · focus · HN ↗
archagon · · focus · HN ↗
ben_w · · focus · HN ↗
If LLMs are "transformative" in the same sense as counting "alchemy because of the scientific funding that went into various attempts led into many vital discoveries", what's going to be our version of "actually we can turn lead into gold now, we just have better things to do with the capability"?
<a href="https://en.wikipedia.org/wiki/Nuclear_transmutation" rel="nofollow">https://en.wikipedia.org/wiki/Nuclear_transmutation
owebmaster · · focus · HN ↗
Isn't it vibecoding? Turn out it's not really gold
ben_w · · focus · HN ↗
We do have the means today to turn literal lead into literal gold.
The energy is better spent on almost anything else and the gold is radioactive afterwards, but we can do it.
The closest analogy I'd have for vibecoding is combustion engines. Historical antecedent was a toy, early industrial ones took a lot of fuel and were only useful to pump water out of the coal mines that supplied that fuel, but kept getting improved until they made a critical quality leap that took them from "slightly worse than a horse" to "marginally better than a horse" and then there were suddenly a lot of unemployed farriers.
But literal-lead-to-gold took a while longer than that, and a different set of inventions behind it.
ambrozk · · focus · HN ↗
archagon · · focus · HN ↗
goolz · · focus · HN ↗
vineyardmike · · focus · HN ↗
The world looks pretty different today. Even if the model maker companies go out of business (I’m skeptical), the model weights would stick around (many are open freeware already).
I know many software engineers who haven’t written code this year. AI chatbots are regularly used as alternatives to searching manually by many people. Agents are becoming a valuable new enterprise tool, and now consumers tech consumers are hopping on board.
hajile · · focus · HN ↗
Even if you eliminate 100% of the people involved in creating software, that's still not enough money (and of course, that's not going to happen because someone has to know what to build).
Everyone is adding agents to enterprise stuff, but an overwhelming majority of the general population now hate AI for most things -- especially the "AI support" these companies are using. I think most people would rather suffer through overseas call centers with absolutely terrible representatives than deal with AI support (studies seem to indicate 80+% prefer a human to AI for support in general).
AI as a search engine is useful, but a very different animal. Proficient users want a way to check the AI like Google's AI search does (though the links sometimes don't agree with the summary), but these run very small models (8b or so) with the RAG backend doing the real work.
How many competitors does this space need? Companies can build their own proprietary RAG search engines, but users would almost always prefer the company make that public data available to Google and just use one well-optimized search engine instead of dozens of bad copies.
What about profitability? Google enshittified their search to increase retention and ad time, but AI search should reduce retention/ad time AND costs a lot more money to run too meaning it should lower their bottom line. If that weren't enough, their RAG system is almost certainly more replaceable by users with alternatives than their traditional search system. This seems like all downside for Google.
TeMPOraL · · focus · HN ↗
The currently well-served market for AI is not software engineering, it's approximately all of white-collar work, ranging from accounting and law, through medicine, general office work, to school administration, education, NGOs and governance.
Not everyone is going to just publicly brag about their AI use, but it's an open secret everyone is either using LLMs for half their work, or - if for some reason they're not busy enough to arrive at this idea on their own - under pressure to start using them.
CoolestBeans · · focus · HN ↗