Any specific reason this is relevant to the arguments in his post?
He's (at least to some extent) arguing that if you're going to say someone's paper is "mostly wrong", saying the same things 4 years later should probably warrant a "ok, you were right" at least.
Ie. the whole "idea" being "hey, for gai we need something different than this gtp3" tweet, not "idea" as in "hey I invented this new thing I call LSTM, check it out [link to paper, results what not]".
Well, the LSTM fella does pop up later calling out Lecun for "rehashes but doesn't cite essential work of 1999-2015". Which I guess does mean people with real "ideas" are also fed up with him?
"Deep learning pioneer Jürgen Schmidhuber, author of the commercially ubiquitous LSTM neural network, arguably has even more right to be pissed [...]"
He's proven time and time again that he doesn't understand the methods at work and doesn't even seem interested in trying to do so.
Why? If their arguments are sound, why shouldn't we listen to them?
Where is this silly credentialism coming from?
>Why? If their arguments are sound, why shouldn't we listen to them?
Generally arguments from non-experts like this fall into the "not even wrong" category and don't merit much attention.
How exactly holding the SOTA record of any, or even all, machine learning task gives you any authority on true intelligence?
What gives LeCun any authority on true intelligence?
Even Lecun points out that his paper is not technical.
The only thing that matters is the of the argument.