As a brand-new market, large language models are likely still in the single-digit-billions range, not counting all the other markets that are, or can be, built on the use of LLM.
Just how big the core LLM model business might be remains a guess, but if one believes LLM is a general-purpose technology, then like other forms of enabling infrastructure, the market could be substantial.
What also remains unclear is where key revenue elements--especially fees for generating inferences--will be reaped. Use of an LLM includes both the license to use a model plus the recurring fees paid for deriving inferences.
As with any other form of “computing as a service,” some parameters will vary. License fees might be one-time payment, a recurring fee, or a fee based on usage.
Inference fees are variable. Support and maintenance fees might also often be charged, to cover bug fixes, security updates, and documentation updates.
The ultimate analogy might determine market size. Are LLMs most akin to servers, operating systems or end-user software? More generally, are LLMs going to be infrastructure somewhat similar in function to electricity networks, road systems, airports or seaports, as enablers of commerce?
Beyond all that, where is the incidence of payments? Is revenue generated by direct fees charged to business and consumer end users, directly by business partners or indirectly in the form of value for third parties and end users?
In many cases, AI is a capability that enhances the value of some product a buyer consumes, but might not be a distinct extra charge or involve a subscription for use of the product.
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