yoshua

So far they've had interviews with many of the big names in ML: Yann LeCun, Goeff Hinton, Yoshua Bengio.

Also, Yoshua gave a great, albeit slightly controversial for the crowd, talk at AGI 14 in Quebec this summer.

Geoffrey Hinton's and Yoshua Bengio's impact were at least as high as his, if not much higher.

A great paper on learning embeddings for sparse representations is a paper by Yoshua Bengio et.

Same goes for Turing Award winner Yoshua Bengio, AI tech CEOs Dario Amodei, Sam Altman, Elon Musk, etc.

The most prominent I'm aware of saying thing to this effect are Yoshua Bengio, Geoff Hinton, and Yann LeCun.

In the case of machine learning that would be Geoffrey Hinton, Yann LeCun, Yoshua Bengio, Andrew Ng (this list is not exhaustive of course).

Pieter Abbeel, Yoshua Bengio, Alan Kay, Sergey Levine, and Vishal Sikka are advisors to the group.

No, like Joscha Bach, Yoshua Bengio, Ben Goertzel etc...

Didn't realize Yoshua & co had a book coming!

I feels its hard to argue that through a mistake a hallucinated citation emerge: > Real Citation Yann LeCun, Yoshua Bengio, and Geoffrey Hinton.

In my opinions, to explore the unknown, I think an institute like Mila, led by Yoshua Bengio, would have been more fitting.

Yoshua is part of the "loud contingent" being described.

Yoshua Bengio has touched on this with regards to depth from the point of view of circuit theory, but the argument is basically: "here's a couple circuits which are more efficiently represented by increased depth, therefore deep = good always".

Yoshua Bengio will point out that there are functions that require exponentially more gates to encode when using shallower circuits.

I'd also firmly reject everything that comes from that Yoshua.

Yoshua Bengio has been working on neural nets for years and years and he leads the only one of the big three deep learning labs to not have a lot of commercial entanglements.