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I agree with this take. One interesting open question is: what fraction of the wealth created will the big labs be able to capture? Right now the differences between the big LLMs are relatively small, so it seems plausible to me that the LLM provider becomes a low-margin coke vs pepsi kind of market. However there could easily be some winner-takes-all dynamics or services bundling dynamics that might favor e.g. Google since they might be able to integrate across services better. Am curious for your thoughts.
Speculative:
Most of the economic value of LLMs will come from enterprise, not consumers. For that, there's a variety of factors beyond cost-to-serve that will drive centralization to a few large providers. See the move to cloud in the 2010s. E.g. HIPAA, privacy, "no one ever got fired for buying IBM," reliability, access to large and growing proprietary data sets, custom hardware for specialized workloads, complex data residency requirements.
Google is much better positioned for this than many people give it credit for. OAI will have to learn to deal with a bunch of stupid shit ("what, the government of Saudi Arabia is demanding we set up a data center in the country if we want to operate there? And integrate with a bespoke IAM system to allow the government to view user data?"), and they're just starting to run into these issues. Their saving grace is their relationship with MSFT, which has solved all of these problems; otherwise they'd be dead in the water.
As for the wealth captured: more than they do now, but not everything.
Since the internet became a thing an easy way of making money has been to create CRUD apps (create, read, update and delete). Essentially make a program that takes some info, stores it in a database, retrieves it, updates it and deletes it. People have made fortunes making programs for hotels, programs for hairdressers, programs for libraries etc. Making a program for gyms isn't that hard. It is just a bunch of forms that are filled out and stored in a database. Get a thousand gyms paying 99 dollars a month for your software package and you are now a rich man.
AI will open up similar markets. Take a opensource model, hire a bunch of people in India to read through tens of thousands of home inspection protocols and use it to create home inspection report AI. Sell it to a thousand home inspectors for 99 dollars a month and have a million-dollar business. Do the same with everything from an AI that can tell if bread is baked or if a tooth needs extracting based on a xray.
The base models will do it. There isn’t a separate word processor for accountants, one for lawyers, one for bankers, and one for doctors. Everyone uses Microsoft Word. A handful of foundational models which are largely interchangeable will eventually be tuned on all common scenarios and available as part of your (or your employer’s) $20 a month per person MS/Google/Apple subscription.
The only reason a lot of the current SaaS market exists is that the 90s made conglomerates unfashionable and big techs didn’t want to hire 500,000 engineers to make software for every business when they were already facing antitrust scrutiny. But LLMs offer the ability to build more general products capable of fulfilling business needs without major workforce expansion or other costs.
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Reminiscent of Dr. Evil: "Here's the plan, we use AI to write home inspection reports, and we hold the market captive for... ONE MILLION DOLLARS."
Sure, do that a thousand times and you get to a billion. But this is all chump change. And when you're LoRA-ing your Llama, whose GPUs are you training on? Do you have a cluster in your basement, or are you calling some API hosted by a big provider? And when you're generating the home inspection reports, where are they actually coming from? Even if you're able to do that all yourself, can you do it faster than someone who takes some VC money and writes a big check to a big provider to GTM faster?
None of that is to say that there's not money to be made; there is. But a substantial chunk of it will accrue to centralized providers.
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