Earlier quoted context omitted.
How can research predict this wave is coming to an end, when research also didn't think this wave would happen either. It seems like there are always people saying 'it can't be done'. Then it happens. If there was a way to predict the future, then wouldn't that research need to know how something would be implemented, in order to know it can't be?
For the first time with GPT4, OpenAI as been able to predict model progress with accuracy: > A large focus of the GPT-4 project has been building a deep learning stack that scales predictably. The primary reason is that, for very large training runs like GPT-4, it is not feasible to do extensive model-specific tuning. We developed infrastructure and optimization that have very predictable behavior across multiple sca…
"just trying to temper investor enthusiasm"
"trying to downplay AI threats to calm down regulators"
etc....
etc....
But it is not some 'Proof', that LLM's have reached a limit.
It is a self reported note along the lines of : "nothing to see here, we're at our limit, it's all good, stop probing us".