This is a good summary of why the language we use to describe these tools matters[1].
It's important that the general public understands their capabilities, even if they don't grasp how they work on a technical level. This is an essential part of making them safe to use, which no disclaimer or PR puff piece about how deeply your company cares about safety will ever do.
But, of course, marketing them as "AI" that's capable of "reasoning", and showcasing how good they are at fabricated benchmarks, builds hype, which directly impacts valuations. Pattern recognition and data generation systems aren't nearly as sexy.
It's important that the general public understands their capabilities, even if they don't grasp how they work on a technical level. This is an essential part of making them safe to use, which no disclaimer or PR puff piece about how deeply your company cares about safety will ever do.
But, of course, marketing them as "AI" that's capable of "reasoning", and showcasing how good they are at fabricated benchmarks, builds hype, which directly impacts valuations. Pattern recognition and data generation systems aren't nearly as sexy.
[1]: https://news.ycombinator.com/item?id=44203562#44218251