Cost per token is going to tank; it's a race to the bottom. The frontier model providers have no moat between each other and eventually even the open weight models will be "good enough" for almost every purpose.
Right now the market is expecting something a lot more than "sells a lot of tokens" out of these things to justify their valuation.
The future is in private data, private models, and private APIs, which can't be distilled as easily as public APIs.
Wouldn't that depend on how much data? I assume those who own the data would rather buy the hardware and create models from this data themselves, as opposed to sending their data off to someone else, or allowing it to be pirated.
For most of those Google is much better positioned.
I disagree, the moat will be of those holding rights for valuable problem domain specific training data. Examples I can think of:
Adobe sits on a treasure trove of:
- Copyrighted multimedia
- Years of telemetry on content creation
Zeiss sits on decades of data:
- Medical imaging, and surgical footage.
- Silicon waffer inspection.
These embody a training corpus that is de facto (lawfully) out of reach of the crawler scrapper approaches of Google/Meta/OpenAI/Anthropic (even if they pirate the seas for torrents like before).
Neither Adobe or Zeiss are an AI power house but the barrier to entry has also dropped with all the movement in the field.
Google owns Google Books and a myriad other data sub businesses beside the index of the entire web.
Excellent point, and one that’s not raised enough in these conversations.
Well openai and anthropic are sitting on absolute treasure troves of private data that is their users' interaction with their models.
personally thats why i think OAI is in a way better place with them targeting ads.