Can someone a successful (not necessarily profitable) concrete application of these things, other than "gpt-3 wrote an article in Guardian and said it wouldn't kill us".
I used largish (GPT-2 and similar) models to build an app discovering Category Entry Points (a marketing thing around the things people are thinking about when they decide they need to buy a particular product) for specific product categories.
We use specifically prompted gpt-3 to generate synthetic training examples (eg paraphrases, summaries, etc). We fine tune other (much smaller than gpt3 but still large-ish) language models for controllable language generation (often augmented with synthetic data from gpt3). As a comparison point, we did try GPT Neo and it did not provide sufficiently high quality synthetic data.
Transformers in general have lots of applications (machine translation, information retrieval/reranking, ner, etc).
In the narrow access window I was allowed to Philosopher AI, I found it incredibly helpful in brainstorming and bouncing ideas off. It helped me organize my project, and I even included the conversations in the repo.
Can someone a successful (not necessarily profitable) concrete application of these things, other than "gpt-3 wrote an article in Guardian and said it wouldn't kill us".