I recently watched a podcast with Stephen Wolfram (few months old) where he runs a photo of himself through Wolfram Alpha "ImageIdentify" and it classifies him

I recently watched a podcast with Stephen Wolfram (few months old) where he runs a photo of himself through Wolfram Alpha "ImageIdentify" and it classifies him as a plunger with 50% probability and 8% probability it's a human [1]. He then goes on saying how he's working on systems that would allow a self driving system decide what to do based on if the collision detected is a human or inanimate object, etc. This was just one particularly ironic example of what I'm seeing with ML - we saw this level of accuracy in classification years ago - where is the enormous progress ? There have been pockets where ML shows it's applicable with encouraging initial results but after that it seems to me that we suck at perfecting those system and the progress has been incremental at best. The only exception I can see is stuff like self-play where the system can generate insane amount of training data. [1] https://youtu.be/ez773teNFYA?t=8420 https://youtu.be/ez773teNFYA?t=8420