Yeah that was disapointing given the title. ChatGPT didn't spring full-formed out of nowhere. It's progress upon an existing body of work that is totally opaque to the uninitiated but a reasonable facsimile can be approximated given enough time on http://huggingfaces.co, colab, and finding the right discord to help you out. ML shouldn't be limited to an Ivory tower of arvix papers.

No, because there is no (public) chatGPT api. This is using the GPT-3 API to build something that behaves similarly to chatGPT.

I wonder if one of the open models would work the same

I tried them all, and continue trying when new things come out. No open model is capable of even remotely approaching the capabilities of GPT-3 or ChatGPT. Even if you had an equivalent trained model, running it would require enormous hardware.

While Stable Diffusion is pretty comparable to DALL-E 2 even on small hardware (such as M1 MacBook Air), this doesn't hold true for large language models. These need much, much more VRAM.

text-davinci-003 is extremely close, or code-davinci-002

None of that model available to run on your hardware

thats a real shame. Any idea why GPT-3 generations differ so much? Maybe eleuther/whatever could look at refining their model in a similar way.

It's most likely because of the actual runtime size of the model. All the open models are sized for consumer-grade devices, and thus 10x-100x smaller than whatever OpenAI runs (probably around 100+ GB in VRAM, maybe even some multiples more). This is one of the main reasons why their API makes business sense - it's not practical at all to run models like GPT-3 yourself, and training them costs incredible amount of money too.

FYI ChatGPT does not have an API and the article references GPT-3 general availability release.

ChatGPT runs on a heavily modified version of GPT3 nicknamed “GPT3.5” that is also not available via API.