Aside from dumping a very large amount of compute and human-supervised learning into existing technology, what major progress has been made in the past six months?
Read it again, but this time turn off your preconception. I asked a question I wanted to hear a legitimate answer for. I am very interested to hear where this is headed (to the best of our ability to predict). The results we can get with sufficient computing power is quite interesting, but is it reaching the point of rapidly diminishing returns? What's the next step in this evolution, beyond making the training faster or adding more parameters to the model?
It's not like when the first theoretical models that make up the basis for GPT came out, people were instantly sure where we'd end up in 5 years.
I'm sure people within OpenAI or other AI companies would be able to tell you of very interesting advances, but they won't do so on HN until the things are public.