[tdrdt]

It seems the flaws are too binary. 90% of the results are great, the other 10% absolute trash.

You can see this everywhere. For example those app that generate a non existing person. A lot of times the results are great except for that one spot which makes the overall result useless.

Another example is the OptiX denoiser (NVidia). You can get very nice renders in a few seconds which speeds up the workflow. But every time it has areas with a lot of flaws. This doesn't matter when you are still working on something but for production it is useless.

ML has it's use in a lot of areas where the outcome doesn't have to be perfect. But I am still not convinced it is 'production ready'.

[michaelbuckbee]

There's the notion that over time the flaws of the previous generation of technology are held up as traditional artifacts.

Things like:

- the "warm" sound of vinyl records. - nostalgia for early myspace, tumblr, geocities, web design - faux edison lightbulbs - low vs high frame rate movies

I wonder if the flaws of all the current ML techniques will eventually be thought of similarly.