Sure, there are a few edge-case failures and mistakes here and there, but I can't help but be in awe . AWE. Let me state the obvious, in case anyone here isn't clear about the implications: If the rate of improvement of these AI models continues at the current pace, they will become a superior user interface to almost every thing you want to do on your mobile phone, your tablet, your desktop computer, your car, your…
- constrained context
- part of a hands-free workflow
People are already used to using their phone or car's nav system to give them directions to an unfamiliar place. But even with such a system it's useful to have a human navigator in the car with you to answer various questions:
- What's my next turn again?
- How long till we get there?
- Are there any rest stops near here?
- What was that restaurant we just passed?
- Is there another route with less traffic?
- List of upcoming directions
- Overall route planning
- Surrounding place data
- Traffic data and alternate route information
The information is contextual and constrained based on a current task. In some cases it might be more desirable to whip out your phone and interact with the map to look up the answers on a screen, but often it won't be worth stopping the car, and so the conversational interface is better.
Cooking assistant is a similar case: you are busy stirring something and checking on the oven -- you don't want to wipe the flour off your hands to pick up your phone and ask how many teaspoons of sugar you need. Again: contextual and constrained info based on a current task, and your hands and eyes -- the instruments of traditional UIs -- are otherwise occupied.
Today, our software interfaces generally have one of two kinds of entity on the other end: humans, or other software. In the near future there will be another type of entity: language models. We need to start thinking of how our APIs will change when they're interacting with an LLM -- e.g. they'll need to be discoverable and self-describing; error states will need to be standardized or explicit with instructions on how to correct; they'll need to be fast enough to fit in a conversational interface; etc. It's arguable that such traits are part of good API design today, but in the future they may be required for the API to function in a landscape of virtual agents.