- Code interpreter, function calling were already possible on any sufficiently advanced LLM that could follow instructions well enough to output tokens in a rigidly parseable format, which could then be fed into a parser, and its output fed back to the LLM. It was clunky to do with online APIs like ChatGPT, but still eminently possible.
- Custom chatbots were easy to build before, and services to build them (like Poe.com) existed before.
- Likewise outputting JSON just requires a good instruction following AI, that can output token probabilities, along with a schema validator that always picks a token that results in schema-conforming JSON
- GPT4-128k seems to be revolutionary, but Claude-100k already existed, and considering LLM evaluation is quadratic wrt context size, they are probably using some tricks to extend the context, they are not 'full' tokens (I'd be happy to be proven wrong). While having a huge context is useful, for coding, a 8k context can be enough with some elbow grease (like filling the context with a 2-3 deep recursive 'Go To Definition' for a given symbol), so that the AI receives the right context.
- Dall-E 3 seems to be the most revolutionary, but after playing with it, it has much improved compositional ability over SD, but it's still prone to breakdowns
Overall I feel like todays announcements were polish and refinement over last year's bombshell breakthroughs.