Always getting skeptical when you hear of a name before you hear of a concrete achievement. I can respect his research but a bit too much Jürgen Schmidhuber before even getting into what his contributions are.
He's been an AI researcher for a while. I think his biggest contribution is understanding the vanishing gradient problem and creating the LSTM architecture. LSTMs are widely used in both industry and academia, and many neural net architectures that aren't LSTMs are heavily inspired by the LSTM idea.
One of his students, Alex Graves, is a researcher at DeepMind who is seen as one of the top people in RNNs.
To be fair, it's a popular magazine piece written for the layperson.
I don't know enough about AI research to judge the value of Dr. Schmidhhuber's contributions, but I've seen his name multiple times in past HN discussions.
>hear of a name before you hear of a concrete achievement
That's an excellent criterion.
I often wonder if many famous past intellectuals were mere celebrities where I can't recall a single achievement. And if one can't name a famous true idea in an current academic field, perhaps the field itself is worthless.
It is a poor criterion, because it is so subjective and dependent on PR machines.
The OP just has not heard of any accomplishments, but anyone with a little expertise in deep (reinforcement) learning knows about the major contributions to the field by Schmidhuber.
Using this criterion you are using popular media and fields you know not much about, to brush away the accomplishments of respectable scientists. Don't base your skepticism on your own lack of knowledge: that makes it selective -- You can not cut through the bullshit, if you don't know how to wield a sword.
The criterion is not about assessing a particular individual's contributions, it's about choosing what and whom to investigate in the first place. Of course this is subjective, and rightly so.
