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GAN Theft Auto [video]

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Re: GAN Theft Auto [video]

#31

Post by godelski »

sentdex wrote: post #17
ShamelessC wrote: post #10

Great work! Hacker News still seems to have a deeply skeptical culture with regard to machine learning - not sure why. There's always someone saying it's "not novel" and it's "just doing x". Overfitting is a known issues in machine learning, people. If you still think all neural networks are doing is memorizing the dataset completely in the year 2021 - you might want to revisit the topic. It is one of the first conce…

Heh, yeah, tough crowd I guess. The full code, models, and videos are all released and people are still skeptical. I feel like 95%+ of papers don't do anything besides tell you what happened and you're just supposed to believe them. Drives me nuts. Not sure why all the hate when you could just see for yourself. I'd welcome someone who can actually prove the model just "memorized" every combo possible and didn't do an…

> I feel like 95%+ of papers don't do anything besides tell you what happened and you're just supposed to believe them.

Honestly I think there's a big problem with page limits. My team recently had a pre-print that was well over 10 pages and we still didn't get everything and then when we submitted to NeurlIPS we had to reduce it to 9! This seems to be a common problem and why you should often check different versions on ArXiv. And we had more experiments and data we needed to convey since the pre-print. This problem is growing as we have to compare more things and tables can easily take up a single page. I think this causes an exaggeration of the problem that always exists of not explaining things in detail and expecting readers to be experts. Luckily most people share source code which helps show all the tricks authors used and blogging is becoming more common which further helps.

> I'd welcome someone who can actually prove the model just "memorized" every combo possible

Honestly this would be impressive in of itself.

Re: GAN Theft Auto [video]

#32

Post by godelski »

andrepd wrote: post #22
ShamelessC wrote: post #10

Great work! Hacker News still seems to have a deeply skeptical culture with regard to machine learning - not sure why. There's always someone saying it's "not novel" and it's "just doing x". Overfitting is a known issues in machine learning, people. If you still think all neural networks are doing is memorizing the dataset completely in the year 2021 - you might want to revisit the topic. It is one of the first conce…

> Hacker News still seems to have a deeply skeptical culture with regard to machine learning Is... that a bad thing? Skepticism is good. When it's about something as hyped as "deep learning", even more so.

> Skepticism is good

There's skepticism and then there's being a non-expert in a field and talking with high confidence. How do you differentiate these? Conspiracy theorists use the same logic. You're right that skepticism is good, but it is easy to go overboard.

Re: GAN Theft Auto [video]

#33

Post by godelski »

sentdex wrote: post #6
senkora wrote: post #5

Someone did a similar project with the exact same name for an ML art project at CMU a few years ago. https://m.youtube.com/watch?v=eP5hHKne_gE&feature=youtu.be Full list of projects: https://sites.google.com/site/artml2018/showcase/final-proje...

Jeez, scared me. Same name yep, totally different project. That project is pix2pix. That is not a GAN-based game engine that you play within.

Honestly "GAN Theft Auto" is the obvious choice for the name of the project (your project).

Re: GAN Theft Auto [video]

#34

Post by jcims »

andrepd wrote: post #22
ShamelessC wrote: post #10

Great work! Hacker News still seems to have a deeply skeptical culture with regard to machine learning - not sure why. There's always someone saying it's "not novel" and it's "just doing x". Overfitting is a known issues in machine learning, people. If you still think all neural networks are doing is memorizing the dataset completely in the year 2021 - you might want to revisit the topic. It is one of the first conce…

> Hacker News still seems to have a deeply skeptical culture with regard to machine learning Is... that a bad thing? Skepticism is good. When it's about something as hyped as "deep learning", even more so.

>Skepticism is good.

It can be, but its certainly not an unmitigated good. Especially when it leads to aspersions of fraud and conspiratorial thinking (e.g. rasz's comment thread below).

Re: GAN Theft Auto [video]

#35

Post by reasonabl_human »

emptyparadise wrote: post #25

One throwaway line about GAN operating systems now made me want to see a shell GAN. Keypresses as inputs, 80x24 terminal screens as outputs. Could a neural network dream of Unix?

This exists via recent NLP models, I’ll see if I can dig up a link…

Edit: https://www.reddit.com/r/linux/comments/mtnld7/programmer_cr...

Re: GAN Theft Auto [video]

#36

Post by godelski »

rasz wrote: post #12
ShamelessC wrote: post #10

Great work! Hacker News still seems to have a deeply skeptical culture with regard to machine learning - not sure why. There's always someone saying it's "not novel" and it's "just doing x". Overfitting is a known issues in machine learning, people. If you still think all neural networks are doing is memorizing the dataset completely in the year 2021 - you might want to revisit the topic. It is one of the first conce…

One of the main problems with ML/NN is it often works like magic, aka the trick works as long as audience doesnt know the secret behind it. Its fascinating to gullible audience, mundane bordering on boring to practitioners. My Tiger repelling rock^^^^^^leopard detection model works great on all animal pictures ... until you feed it a sofa https://web.archive.org/web/20150703094328/http://rocknrolln... >able to genera…

> My Tiger repelling rock^^^^^^leopard detection model works great on all animal pictures ... until you feed it a sofa

I'm sorry, how is this different than normal software engineering? There's dozens of unit/integration testing memes poking fun at specifically this (which is a mostly solvable problem in ML btw, when you use out of distribution data. Give your model a 3rd end state that represents "neither").

> id did none of that, what this model did is learn all the frames of video and their chronological order according to the input.

A better explanation is that the network knows what frame to generate given the current frame (and n previous frames) and the current user input. If it was memorizing then it'd have to generate an extremely large number of scenarios (it would exponentially grow as any given frame has k possible actions from your current frame to the next frame). If Sendex can run the game for arbitrary length and take arbitrary actions then it is a far more reasonable explanation that the model is generating the frames rather than memorizing. Apply Occam's Razor.

Edit: Sentdex said the model was ~173MB, so that is not large enough to memorize the gameplay.

Re: GAN Theft Auto [video]

#37

Post by nitrogen »

Something I'd like to see is a visualization of subsets of the network's internal state that correlate with simple quantities like compass direction, velocity, position, etc. It'd be really fascinating to see where in the model these things are being learned, whether they are concentrated in a small area or spread out, and whether this is somewhat consistent across different iterations of the model.

Re: GAN Theft Auto [video]

#39

Post by kristintynski »

rasz wrote: post #13
ShamelessC wrote: post #11

Earlier quoted context omitted.

The first link provided seems to need a very detailed human-provided cost function for specific development needs. The second one is indeed interesting research and seems to be a combination of the prior learned motion mapping working in tandem with a generative model. I suppose you could say that the automation of the dataset is considered as "augmentation"; but the difference here is that the dataset is just pixels…

The first link exposes the trick employed by your model. >animation info and simulation data but did your model learn any of that? >explicit goal of the video you posted is to combat runtime constraints The trick to motion mapping is feeding a lot of data with accompanying inputs to build an atlas you can reference during playback. >first large-scale GAN successfully trained on GTA V Its really cool. The problem I ha…

Accusations of scamming are serious. What evidence do you have? None as far as I can see. This is wrong and should be remedied.

Re: GAN Theft Auto [video]

#40

Post by emptyparadise »

reasonabl_human wrote: post #35
emptyparadise wrote: post #25

One throwaway line about GAN operating systems now made me want to see a shell GAN. Keypresses as inputs, 80x24 terminal screens as outputs. Could a neural network dream of Unix?

This exists via recent NLP models, I’ll see if I can dig up a link… Edit: https://www.reddit.com/r/linux/comments/mtnld7/programmer_cr...

But this is converting natural language input to commands, right? It's not actually dreaming up the entire shell and the output.
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