This looks to be much more heavily using GPT3/Codex/Copilot, which I've found to be eerily effective. It basically feels like a voice interface to Copilot. The main difference between these and something like Google Home is how effectively they pick up on context. "Hey Github" would be able to use all the code in the file as context, so when you say "wrap this in a function", it'll have an idea of what you mean, without that function having to be explicitly programmed. Voice assistants have to _always_ be in a voice space, so context is very limited. And generally the way Google home-style voice assistants are created is by programming specific actions linked to specific phrases. ML helps make the phrase matching flexible, but the action is usually entirely explicitly coded. Using Codex would let the action be ML influenced as well.
If Copilot is any indicator of effectiveness, then I have high hopes for this! I've always wanted to program while stationary biking :)
I think yes this could be a real multiplier for seniors, you're doing something you have done lots of times before just a bit different you know pretty much everything you need to do, describe it until it is in a state where you can through and finish it off. Exactly like a stationary bike or out in the garden with your kid type thing.
IF the voice analysis was any good of course. But maybe it will also be able to be better than typical voice analysis because the syntax is limited, when programming I use a much more limited vocabulary than when writing literary criticism. So while text to speech is total crap for handling complex literary phrasing it might be adequate for programming structures.
If Copilot is any indicator of effectiveness, then I have high hopes for this! I've always wanted to program while stationary biking :)