7 Comments

Super helpful read, thanks for another awesome writeup!

I'd love to hear your thoughts on the "lower cost of ownership" angle played forward. Running these models is expensive (Ex. ChatGPT is likely ~$100k/day https://twitter.com/tomgoldsteincs/status/1600196995389366274?s=20) so it seems plausible that the providers will need to turn the pricing dial up soon (even as the cost of compute continues to fall, it'd be a multi-year timeline before it makes LLMs super cheap).

How do you think the companies built on these FMs should plan for those increases? Is it a case of creating enough value for a vertical where your customers are ok paying up down the line?

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Hey Aqil - appreciate the feedback and helpful thoughts! Yes, there is a scenario in which costs can turn upside down for companies building intelligent apps, and there will be multiple paths for these companies to explore wrt passing costs to end users, finding economies of scale on COGS, leveraging (and negotiating between) multiple FMs, etc. Keep an eye out for a future post here :)

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Very insightful content. As an entrepreneur in the same space, this article was really helpful in understanding the current rapid progress and trends across industries in generative AI space. Looking forward to more such content. Cheers.

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Hey Rishabh - thanks so much for reading and the kind feedback. So much going on right now in this space, there won't be any shortage of content to write about :)

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where'd you source $100B in saas spend?

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Allied Market Research is quoted here (https://www.prnewswire.com/news-releases/global-software-as-a-service-saas-market-size-is-projected-to-reach-700-billion-by-2030-301618870.html) sizing the global SaaS market at $121B in 2020. We saw estimates as high as $200-$300B but believed that included infrastructure/platform spend, so felt $100B+ was the appropriate sizing for application SaaS. Salesforce alone will do $30B+ of rev this year!

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Thank you Vivek! Very helpful.

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