[apohn]

There might be a lesson from history on where an "AI" startup needs to focus if they want to succeed.

Starting around 2012, there was a huge hype around ML. Lots of startups on selling "ML." If you look today, the majority of the startups that just sold ML algorithms or ML in a box are pretty much gone, or were acquired for amounts where only the founders made enough money to pay off their car loan on a Toyota Camry. At least one of the most highly regarded Unicorns in 2014 now is in the "Wait, that company still exists?" category.

The companies that survived or got acquired for a decent amount were the companies that used ML to actually solve a tangible problem. They were not selling ML, but a solution to some problem that happened to use ML - even if their marketing focused on the ML part.

I wouldn't be surprised to see the same with AI companies.

A big company (e.g. Google) can quickly release a similar product for an LLM because that's an area where the big company was already doing work and a lot of the knowledge to build it is published or known. But if a startup is targeting a focused problem in a specific industry, a big company can't just wake up one day and get the information needed to solve that problem in a short amount of time.