[bigyabai]

There's a lot of reasons. The largest reason though is that an Airpods mic consumes ~100x less power than the $200 XLR mic and therefore needs a 100x lower impedence microphone. The low-detail recordings are a feature, not a bug.

[SilverElfin]

Can’t you do an AI power improvement of the input sound on your computer, from where you’re doing work video calls?

[bigyabai]

No? You can amplify the audio digitally (which also amplifies analog imperfections like noise/ground hum/wind) or you can try fancy denoising algorithms which are incredibly lossy and imperfect.

I don't know of any "download better audio" solutions to-wit, at least from my time handling live audio.

[ryeguy_24]

Exactly. This was my point. Televisions can upconvert from 720p to 4k. In the same sense, the machine learning model would fill in the waveform and mimic a high powered mic. It can do this at the connection point (iPhone / computer).

[bigyabai]

Televisions have considerably more temporal data to work with than an audio stream does. It's very easy to hack together interpolated images, not so easy to predict/denoise/upres time-series audio information.

Past a certain point it's probably easier/more efficient to use the Airpods as a speech-to-text mic and then infer a "high quality" text-to-speech version on your connected device.