[Planktonne]

> You ask it to show you a color picker, it generates HTML code for a color picker, you copy that into your browser and you can pick your color, which you can then copy&paste back into the LLM for further processing.

This is slower, more awkward, and less efficient than just picking a colour from an existing colour picker.

[grumbel]

The point is that nobody had to program this. Nobody had think up front "Will the user need a color picker?". Nobody had to find a spot in the UI to place it. You can just will it into existing as a user with nothing but the power of the LLM. No classic app has anywhere near that amount of expressiveness.

Future versions of chatbots will of course have support for <iframe> or similar to display this kind of stuff inline, that should be obvious.

[gtirloni]

> The point is that nobody had to program this. Nobody had think up front "Will the user need a color picker?"

Are you sure the training dataset didn't have a few articles explaining how to code a color picker? Did it figure it out by itself like you say?

[Planktonne]

I don't think that's the point; it's not that no one had to program the colour picker - it's that no one did. The workaround shows that there was a need for it.

Having to copy and paste code to get a colour picker that you can then use and then paste the output back into the chatbox is less efficient than using a colour picker. LLMs can work as general interfaces, but the trade-off is that they're less efficient than a specific one.

[esafak]

One duty of the programmer and product manager is to think about the likely uses of the program and to build a UI to enable it. If users wanted a blank slate they could write the program themselves, or have chatGPT write it.

Maximum expressiveness is not the goal, because it comes with a price. There is a balance to be struck between expressiveness, and economy of effort and cognition.

[TT2048]

For now, until running ToolFormer or one of the other Jarvis like models get* better