The current stage is now productionizing what we have; finding product fits for it, and making it cheaper. Even GPT-4 isn't necessary to push forward what is po

The current stage is now productionizing what we have; finding product fits for it, and making it cheaper. Even GPT-4 isn't necessary to push forward what is possible with AI; if you think about something dumb like "load all of my emails into a language model in real time, give me digests, automatically write responses for ones which classify with characteristics X/Y/Z, allow me to query the model to answer questions, etc": This does not really exist yet, this would be really valuable, and this does not need GPT-4. Another good example is in the coding landscape, which feels closer to existing. Ingest all of a company's code into a model like this, then start thinking about what you can do with it. A chatbot is one thing, the most obvious thing, but there's higher order product use-cases that could be interesting (e.g. you get an error in Sentry, stack trace points Sentry to where the error happened, language model automatically PRs a fix, stuff like that). This shit excites me WAY WAY more than GPT-5. We've unlocked like 0.002% of the value that GPT-3/llama/etc could be capable of delivering. Given the context of broad concern about cost of training, accidentally inventing an AGI, intentionally inventing an AGI; If I were the BDFL of the world, I think we've got at least a decade of latent value just to capture out of GPT-3/4 (and other models). Let's hit pause. Let's actually build on these things. Let's find a level of efficiency that is still valuable without spending $5B in a dick measuring contest [1] to suss out another 50 points on the SAT. Let's work on making edge/local inference more possible. Most of all, let's work on safety, education, and privacy. [1] https://techcrunch.com/2023/04/06/anthropics-5b-4-year-plan-to-take-on-openai/?guccounter=1 https://techcrunch.com/2023/04/06/anthropics-5b-4-year-plan-...