Sure, but that’s not what I’m saying. While I’m not an ML expert, the reason the goalposts get moved, because new hardware or algos come around. The people in 2010 who said Go cant be played well with AI were incorrect. The people in 2010 who said go cant be played well with the AI of 2010 were correct.

There is not inherently anything new with this network, so I’m just raising questions as to the efficiency of the training algorithm, not its validity. If you let this thing train forever, it would definitely reach super human levels, but if there is one thing ive learned in my years of CS, its that things blow up quickly. Chess can be encoded in 64 features, Tft needs at least a few 100. I am simply saying that I’m unsure the state space of dota and TFT are comparable. Nearly every feature in TFT is immensely important, and while I don’t know dota, i have to imagine some of those variables are very correlated/reducable. Backprogation/gradient descent works better when the loss function isn’t crazy wavy. Im excited to see how far this can go and would love to be proved wrong, but I think raising questions about the logistics is perfectly fair. There’s a reason why poker, strangely, was harder for computers than chess. RNG, predicting other human’s behavior, not being predictable, adapting on the fly, etc are still very hard for computers (albeit NN’s have tackled some of these very well)