Introduction to GANs, NIPS 2016 | Ian Goodfellow, OpenAI

[@Michel-gv1sr]

This guy has contributed so much to the field and still has most of his hair.

[@sheikhmansoor202]

😂

[@joecincotta5805]

His recall in the Q&A was pure gold. I want to channel that during PhD defence

[@IKGchiller]

They made us read goodfellows papers in every single AI class and never bothered to mention that he's literally just our age

[@matthewchunk3689]

it's like comparing zion williamson to your average college player: it will just hurt students' feelings

[@techgamer1333]

Sad , But they are mentioning some lectures on youtube though🤣🤣😂😂 check his lectures on youtube😅😅

[@wireghost897]

The Q&A section basically shows you how Ian thinks and learns stuff. He has absolute clarity of the maths behinds not just his work but the related work that he has studies. It is as he he did not just understand the maths, but he pretty much speaks maths like english.

[@Gabcikovo]

Thank God

[@Gabcikovo]

Copy, paste & upgrade.. Thank you.. 🇸🇰

[@sabrinad1922]

From 26:52, I really liked his last comment about how to teach yourself anything. Really inspiring.

[@mermich]

can I say that Ian Goodfellow is the GOAT in modern computer science? T.T

[@boisiul]

a great contribution to synthetic data field!

[@lorforlinux]

26:50 - 28:10 is the best part

[@zrmsraggot]

Nah you are wrong but you feel that way because he tells you how you should learn, and that's obviously what you re/were trying to do at the time you watched the video.

[@bright1402]

I think in the Q&A session, every sentence that Ian said could be a paper 😂

[@ghazarosbarseghyan7645]

Actually it is. An example is SeqGAN :D

[@dosomething3]

“Let somebody else ask questions” - Crickets. .

[@TusharKale9]

GANs very well explained. Great examples too. Thank you very much. Tushar

[@francoisdavid8487]

Super clear explanation! Awesome presentation

[@arielgamboavazquez4250]

Ianm you have always been a good fellow :v

[@rumourscape]

We have come so far!

[@saikrishnapujari]

As this guy is now with Apple, any influence on their Memoji and Animoji or their Camera improvement using GAN ?

[@vikaspoddar001]

The Man, The Myth one n only Ian Goodfellow

[@peasant12345]

Abstract Expressionism 19:23

[@generichuman_]

19:36 one way to fix this, is to not use the Chernobyl data set.

[@mayukhmalidas]

Great session

[@PixelSenseiAvi]

The man in the house!!!!

[@jackcuervo2262]

Wow Ian is awesome!

[@Gabcikovo]

2:48 both players are neural networks

[@Gabcikovo]

5:16

[@Gabcikovo]

5:26 the goal of the generator is to fool the discriminator

[@Gabcikovo]

5:30 eventually the generator is forced to produce data as true as possible

[@Gabcikovo]

Uhrik and Putin cried bitter tears

[@Gabcikovo]

3:10 one of the players is trained :) to do the best as possible on the worst possible input

[@sureshothwarang]

This dude is awesome

[@alexbarnadas]

Where was it?

[@igorcherepanov4765]

do already exist any approaches to solve the problem with counting?

[@supreetkurdekar5726]

Ian Goodfellow is Jim Halpert!!!

[@vanglequy7844]

Here is my summary: So basically what he is trying to say is that let D tries to defeat G and vice versa, until the battle becomes so challenging for both sides. And then ML users can benefits from the skills of the two (D and G) to make cool things like fake images, fake videos, and fake news that are indistinguishable. And in many cases, these fake things are useful. Don't ask me what happens under the hood. Need to read his paper and some more background info. Brilliant work I must say, but not so good "introduction to GANs" for broad audience.

[@phuccoiinkorea3341]

cha hieu gi ong a =))

[@redryan20000]

Sounds pretty bad tbh

[@generationai2211]

Hi, this comment partially inspired a recent video I made, I agree that this video is hard for the “general public” to understand.

[@agiisahebbnnwithnoobjectiv228]

The objective function of animal brain and hence AGI is to maximize impact. You heard it first from me. gj

[@hzg4013]

what a legend!!!

[@quickpresent8987]

how could this video "lan Goodfellow" are having less views than Siraj Raval video - * -

[@MPXVM]

9:14 - schrödinger's cat logic or Quantum state :) 50% - 50%

[@bingeltube]

Recommendable

[@robelle1357]

Everything was great except for the QA session. The questioner was rude.

[@jackq2331]

Not really，his question help us think.

[@catsaresocute650]

The last part is bs, the right price doesn't exist. It's always a proposal of worth and it's a proposal that can be accepted/rejected. That's what makes it work. They are all proposals of the value of something and every single marked participend is judge. That's the fucking point. NOT some ideal price.

[@tzywg3399]

Down voters were scared by the fallout cow.

[@kicksessentials7]

The narrow wren analytically share because tortellini similarly smile upon a telling domain. unkempt, charming veil

[@wiiiiktor]

i like Ian, but it's hard to follow his mundane voice tone ...

[@stonetech1000]

I think his voice is just fine

[@p.z.8355]

hes a robot ;)

[@prathyusha5393]

I had similar difficulty for quite some time ... But, I guess it's focus.. rather divided focus .. With a lot of practice... I am able to focus on the content at it's root, and a little more continually now .. Edit: Not talking about Ian here... Was speaking in general.. Love listening to Ian s lectures

[@WaterMelonHead9922]

Instead of speaking in disjointed mathematical jargon, he could have went more into practical applications and how to test/troubleshoot the models by showing actual code. Most people won't get anything out of this

[@manUNITED986]

That is absolutely nonsensical, if you understood what he was saying you can go out of your way to find architectures that define what he speaks of. Just say that you're lazy and move on.

[@kulturfreund6631]

This is something for really intelligent people, not for me.

[@BiancaAguglia]

This is hard for me to understand also, but only because I haven't studied enough math and ML to understand Ian. I'm sure you are the same: you're smart enough to understand it, but you haven't put in the work and time to learn ML. There's nothing stopping you from learning it, if you want. 😊

[@DeViLTh0rn]

@@BiancaAguglia i like your positive comment, do you have twitter?

[@JousefM]

@@BiancaAguglia It's definitely not easy to get into the field if you really want to understand it and there are people grasping the concepts faster and more easily than you or I do but that should not demotivate us and keep working on the skill every day :)

[@BiancaAguglia]

@@JousefM True. 😊

[@shubhamchandra9258]

@@JousefM You should be concerned about your own development only. You're good as long as you're learning and improving. Competition is an unnecessary burden.