Silly how OpenAI could blow all voice assistants out of the water today, if they just added Android intents as function calls to the ChatGPT app. Yes, the "voice chat mode" is that good.
With alexa i can program if/then statements, like basically when i say X then do Y. If something like chatgpt requires the same thing then i don't see the advantage.
So LLMs today can do this a few ways. One they can write and execute code. You can ask for some complex math (eg calculate the tip for this bill), and the LLM can respond with a python program to execute that math, then the wrapping program can execute this and return the result. You can scale this up a bit, use your creativity at the possiblities (eg SQL queries, one-off UIs, etc).
You can also use an LLM to “craft a call to an API from <api library>”. Today, Alexa basically works by calling an API. You get a weather api, a timer api, etc and make them all conform to the Alexa standard. An LLM can one-up it by using any existing API unchanged, as long as there’s adequate documentation somewhere for the LLM.
An LLM won’t revolutionize Alexa type use cases, but it will give it a way to reach the “long tail” of APIs and data retrieval. LLMs are pretty novel for the “write custom code to solve this unique problem” use case.
> and to a lesser degree malformed output
What's cool, is that this isn't a huge issue. Most LLMs how have "grammar" controls, where the model doesn't select any character as the next one, it selects the highest-probability character that conforms to the grammar. This dramatically helps things like well-formed JSON (or XML or... ) output.
Yes, I was thinking about even something as if/then, which could be configured in the UI and manifest to GPT-4 as the usual function call stuff.
The advantage here would be twofold:
1. GPT-4 won't need you to talk a weird command language; it's quite good at understanding regular talk and turning it into structured data. It will have no problem understanding things like "oh flip the lights in the living room and run some music, idk, maybe some Beatles", followed by "nah, too bright, tone it down a little", and reliably converting them into data you could feed to your if/else logic.
2. ChatGPT (the app) has a voice recognition model that, unlike Google Assistant, Siri and Alexa, does not suck. It's the first model I've experienced that can convert my casual speech into text with 95%+ accuracy even with lots of ambient noise.
Those are the features ChatGPT app offers today. Right now, if they added a basic bidirectional Tasker integration (user-configurable "function calls" emitting structured data for Tasker, and ability for Tasker to add messages into chat), anyone could quickly DIY something 20x better than Google Assistant.
Of course this isn't fool proof, and there still needs to be work defining capabilities of systems, etc. (although these are tasks AI can assist with). But it's promising - "teaching" the system how to do new things is relatively simple, and effectively akin to describing capabilities rather than programming directly.
The basic idea is to instruct the llm to output some kind of signal in text (often a json blob) that describes what it should do, then have a normal program use that json to execute some function.