I think the vs. humans result should be taken with a huge grain of salt. These are blitz games, and their engine’s elo was far higher against humans than against other bots. So it’s likely that time was a factor, where humans are likely to flag (run out of time) or blunder in low time situations.

It’s still very cool that they could learn a very good eval function that doesn’t require search. I would’ve liked the authors to throw out the games where the Stockfish fallback kicked in though. Even for a human, mate in 2 vs mate in 10 is the difference between a win and a draw/loss on time.

I also would’ve liked to see a head to head with limited search depth Stockfish. That would tell us approximately how much of the search tree their eval function distilled.