That's the benefit of making these models widely available: we now have many eyes and lots of experiences showing these tools aren't magic.

> The slowing pace of improvement at the bleeding edge of generative AI is one sign that LLMs are not living up to their hype. Arguably a more important indication is the rise of smaller, nimbler alternatives, which are finding favour in the corporate world.

This seems to be saying that SLM (Small Language Models) are a sign that improvement in LLM (Large Language Models) is slowing. I don't know that improvements in LLM are slowing, I really mean it, what is the data one way or the other. I've been trying to investigate this question and I don't have a clear answer. The rise of SLM doesn't seem like evidence either way.