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Doom scrolling and the next financial crash!
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Guys, for the love of God please take the technical chat here
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That's what I'm doing. Five years ago I was perfectly happy to be a retiree with 85% equities invested in US and International ex US equity index funds. Now that would have me with a very heavy tech bias. I've been in index funds for the past 40 years because they gave my portfolio some diversity, that strategy now leads to a tech concentration so I've made the active decision to bias towards value and up my cash allocation. I basically don't want to be all in on tech and also I'm out of the mid to long term bond markets too replacing them with MMF/ultrashort bonds.
And so we beat on, boats against the current, borne back ceaselessly into the past.0 -
There are many good uses for AI and I certainly think that LLMs deeply trained on specific subjects could be cheaper and more useful than the general ones. But hallucinations will always be a feature and too much reliance on AI could become an expensive cul-de-sac for many companies. What I worry about is the circular financing of OpenAI etc by the likes of Nvidia, Microsoft etc. The trillions in contracts for training and data centers are based on revenue projections that I'm not sure are that realistic and with interest rates on the way up servicing debt will get more expensive. If AI/tech was closer to 10% of US equity markets rather than 40% I'd be a lot more sanguine, but right now it all seems to be over hyped and over priced.
And so we beat on, boats against the current, borne back ceaselessly into the past.1 -
The hallucination problem has improved massively in the newer models. The consumer grade offerings are still not great, but I see that reasoning loops have had a positive effect there too and an LLM agent is much more likely to run a script to determine anything computable rather than rely on its next token prediction (e.g. "2" is most likely to follow "1 + 1 =")
I agree with you that the real value is in focused agentic products that put sophisticated tools and workflows into the hands of employees to save time and reduce headcount. That puts an upper limit on the amount of value the providers would be able to extract from a business. The earlier example from @Dead_keen of someone spending "$7500 on Claude Code this month" would be weighed against the cost of delivering the same work using human labour (taking into account the cost of the human directing and debugging Claude Code). Who knows what that $7500 would cost if it wasn't being subsidised, let alone based on the future earnings being attributed to the provider on current valuations. So for me, that is where things start to break down.
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Who knows what that $7500 would cost if it wasn't being subsidised,
I'm not convinced the Anthropic was subsidising this. I though that the margin on inference was very high (i.e. inference is very profitable).
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Why are you discussing your investments here? This is a tech board.
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It looks like that's an issue of contention. There is a margin on inference on the API tier, but it seems the price per token is still well below the true end to end operating cost.
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It's almost as if you're not enjoying us dissecting the AI companies' earning potential and valuations.
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It looks like that's an issue of contention.
You may be right, but the stuff I've read suggests inference may have a 70% to 80% gross margin at the moment.
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I've learned a lot. Until this thread i thought LLM was a Masters in Law.
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