[P-NP]

It's actually on an academic review site called OpenReview where the dispute is ongoing: https://openreview.net/forum?id=BZ5a1r-kVsf

LeCun claims four "main original contributions" and Schmidhuber basically debunks them one by one, for example:

> (IV) your predictive differentiable models "for hierarchical planning under uncertainty" - you write: "One question that is left unanswered is how the configurator can learn to decompose a complex task into a sequence of subgoals that can individually be accomplished by the agent. I shall leave this question open for future investigation."

> Far from a future investigation, I published exactly this over 3 decades ago: a controller NN gets extra command inputs of the form (start, goal). An evaluator NN learns to predict the expected costs of going from start to goal. A differentiable (R)NN-based subgoal generator also sees (start, goal), and uses (copies of) the evaluator NN to learn by gradient descent a sequence of cost-minimizing intermediate subgoals [HRL1].

It will be interesting to follow this.