[ttcbj]

You might find the recent Verge/Decoder podcast with Cohere's CEO interesting:

https://www.theverge.com/24173858/ai-cohere-aidan-gomez-mone...

The host is clearly trying to push the CEO of Cohere on how all this is going to make money (or just be economic). The CEO is confident, but not in a very specific way. There is a great moment where he is like "we did some proof of concepts with 5 users, and they were pretty good, but when you tell CFOs about the running costs for a full user base, its not viable."

What fascinates me about AI right now is that it seems to have very different economics from traditional software/internet/SaaS businesses. Those business scale super-efficiently. They have some initial startup costs (but still relatively low, especially with cloud providers) and low running costs.

With AI, the initial capital costs to build the model are quite high. And, the running costs to handle queries are also quite high. These companies need to find use cases that generate value significantly in excess of those costs. If those use cases are out there, they must either involve really significant productivity improvements, or the costs have to come down a lot, or both.

All that said, I remember going to a talk by Adobe's founders, in which they pointed out that when they introduced Postscript, the first Apple printer that ran it was only viable because of a last minute drop in memory prices, and when they started building Photoshop, you could fit six (6!) digital images on a powerful computer.

So, I see why the investment is happening, but its a high risk investment right now hoping to identify both high-value use cases and significant cost savings simultaneously.

[aurareturn]

I think LLM foundational models are like the Cisco/Level3 of the dotcom hype. Cost is high.

It's the startups building on top of LLMs that will have much lower cost.