Most of the high volume enterprise use cases use their cloud providers (e.g., azure)

What we have here is mostly from smaller players. Good data but obviously a subset of the inference universe.

With better imaging, tooling, and archaeological funding, I'm sure we'll find much more evidence like this

So many countries bronze and ancient ages are underexplored

Anthropomorphism of LLMs is obviously flawed but remains the best way to actually build good Agents.

I do think this is one thing that will hold enterprise adoption back: can you really trust systems like these in production where the best control you can offer is that you're pleading with it to not do something?

Of course good engineering will build deterministic verification and scaffolds into prevent issues but it is a fundamental limitation of LLMs

The more prevalent automation is, the worse humans do when that automation is taken away. This will be true for learning now .

Ultimately the education system is stuck in a bind. Companies want AI-native workers, students want to work with AI, parents want their kids to be employable. Even if the system wants to ensure that students are taught how to learn and not just a specific curriculum, their stakeholders have to be on board.

I think we're shifting to a world where not only will elite status markers like working at places like McKinsey and Google be more valuable but also interview processes will be significantly lengthened because companies will be doing assessments themselves and not trusting credentials from an education system that's suffering from great inflation and automation