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Pac-Man recreated with a GAN trained on 50k game episodes

blogs.nvidia.com

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Re: Pac-Man recreated with a GAN trained on 50k game episodes

#91

Post by [deleted] »

YayamiOmate wrote: post #83
YeGoblynQueenne wrote: post #77

Earlier quoted context omitted.

Or, to paraphrase: great paper, no application.

Like every so-called basic science. 1st batteries, radio, lasers etc also looked like that. I see a strong parallel. It's a poor performance but important proof of concept. Also, it's general in computing trend since assembly. Why compile when you can write machine code, waste of resources. Why have abstract compiler, when you can write assembly. Why have higher level language when it cant generate code optimal for t…

[deleted]

Re: Pac-Man recreated with a GAN trained on 50k game episodes

#92

Post by 101404 »

empath75 wrote: post #85
lumost wrote: post #70

I've observed an increasing trend with modern AI research that A) It's no longer practical to incorporate into real products given the hardware costs for training and inference. In NLP, large transformer based models can easily occupy a 5 thousand dollar GPU at a paltry 50-60 words per second processing pace. B) The Research often demonstrates things that existing non-ML toolchains were already reasonable at doing wi…

The ai has created a functional internal model of an external system based on limited sensory input. That is essentially a kind of consciousness.

Not at all.

It just means some people poked a pile of a bazillion if-else statements long enough, until the desired result came out. I believe everyone here knows the xkcd I am referring to.

Still, I think it's an interesting result. But, as someone on Fridman's podcast said the other day: recent advances in AI have all been thanks to advances in computing power, not any new ideas. The future if AI seems to depend on Moore's Law, more than anything.

Re: Pac-Man recreated with a GAN trained on 50k game episodes

#93

Post by YeGoblynQueenne »

esoterica wrote: post #90
SQueeeeeL wrote: post #80

Earlier quoted context omitted.

It really is a great paper, the problem is when your entire field has few real applications but everyone is making too much money to admit that. Cool tech demos like this is awesome as a blog post, but not sure why it's academic...

I don't know where you got the idea that the purpose of an academic paper is to produce the schematics for a working commercial product. The fact that it's novel and interesting is sufficient grounds for producing a paper about it. Why do you think projects like these are solely the domain of blog posts?

That is not true for academic papers in computer science and particularly in machine learning were contributions are expected to have some sort of practical application that is at least possible to foresee.

Indeed, a common criticism against papers in machine learning is "what is a real-world application of this approach?". If you can't answer that convincingly then it's unlikely your paper gets published, particularly if it has rather mediocre results otherwise, as is the case with this paper (see my earlier comment about the comparison to the two other systems which is a bit of an anticlimax).

In fact, the paper (well, the preprint version) makes a clear attempt to motivate the work with a practical application, saying that it aims to "learn a simulator [for robotic agents] by simply watching an agent interact with an environment".

Re: Pac-Man recreated with a GAN trained on 50k game episodes

#94

Post by plutonorm »

101404 wrote: post #92
empath75 wrote: post #85

Earlier quoted context omitted.

The ai has created a functional internal model of an external system based on limited sensory input. That is essentially a kind of consciousness.

Not at all. It just means some people poked a pile of a bazillion if-else statements long enough, until the desired result came out. I believe everyone here knows the xkcd I am referring to. Still, I think it's an interesting result. But, as someone on Fridman's podcast said the other day: recent advances in AI have all been thanks to advances in computing power, not any new ideas. The future if AI seems to depend on…

What makes you think the pile of if-else statements isn't conscious?

Re: Pac-Man recreated with a GAN trained on 50k game episodes

#95

Post by YeGoblynQueenne »

esoterica wrote: post #87
YeGoblynQueenne wrote: post #77

Earlier quoted context omitted.

Or, to paraphrase: great paper, no application.

There is a reason why "Research" and "Development" are listed as separate concepts when people talk about R&D. The point of most research papers is not to directly invent a working product, it's to produce fundamental insights that may be useful in future applications.

See my previous comment: not in machine learning research.

Also, the paper itself tries (hard) to motivate its approach with a real-world application, in particular, learning a simulator to train robotic agents to interact with the real world.

Re: Pac-Man recreated with a GAN trained on 50k game episodes

#96

Post by fpgaminer »

lumost wrote: post #70

I've observed an increasing trend with modern AI research that A) It's no longer practical to incorporate into real products given the hardware costs for training and inference. In NLP, large transformer based models can easily occupy a 5 thousand dollar GPU at a paltry 50-60 words per second processing pace. B) The Research often demonstrates things that existing non-ML toolchains were already reasonable at doing wi…

> It's no longer practical to incorporate into real products given the hardware costs for training and inference

I don't see that trend. Bleeding edge research has always been beyond what's practical, by its very nature. The focus is on pushing the boundaries, not to build something efficient/commercial.

It's the followup work that makes it practical. See for example the evolution of WaveNet. It was breakthrough research, but yeah it wasn't practical. Now a couple years later and we're generating speech on mobile devices of similar quality (see the recent Facebook research), and able to teach these machines using orders of magnitude less data (see 15.ai).

Not to mention the plethora of research that is explicitly about making neural networks more efficient and easier to train (e.g. EfficientNet; 1cycle; etc).

Bleeding edge stuff like AlphaStar, BigGAN, GPT-2, etc are just that: bleeding edge. They'll get more efficient and practical every year, just like everything else in machine learning.

Re: Pac-Man recreated with a GAN trained on 50k game episodes

#97

Post by philjohn »

YeGoblynQueenne wrote: post #77
lumost wrote: post #70

I've observed an increasing trend with modern AI research that A) It's no longer practical to incorporate into real products given the hardware costs for training and inference. In NLP, large transformer based models can easily occupy a 5 thousand dollar GPU at a paltry 50-60 words per second processing pace. B) The Research often demonstrates things that existing non-ML toolchains were already reasonable at doing wi…

Or, to paraphrase: great paper, no application.

A great sales pitch for data-center GPU's

Re: Pac-Man recreated with a GAN trained on 50k game episodes

#98

Post by mysterEFrank »

lumost wrote: post #70

I've observed an increasing trend with modern AI research that A) It's no longer practical to incorporate into real products given the hardware costs for training and inference. In NLP, large transformer based models can easily occupy a 5 thousand dollar GPU at a paltry 50-60 words per second processing pace. B) The Research often demonstrates things that existing non-ML toolchains were already reasonable at doing wi…

This is obviously not meant to be a real game engine. It shows that GANs can learn not only images but transitions between images given some action, which means they can be used as simulators. See world-models which used VAEs https://worldmodels.github.io/

Re: Pac-Man recreated with a GAN trained on 50k game episodes

#99

Post by rcxdude »

enchiridion wrote: post #65
weinzierl wrote: post #59

Earlier quoted context omitted.

Something similar to what you describe is already being done. Game video is streamed to a Raspberry Pi Zero that sits between the real mouse and the Gaming PC and adjusts the mouse movements. Google for "Valorant RPi0" for videos to see this in action. Here is an excerpt from a now deleted Reddit comment where the setup is described: > "My pi is connected to my pc as a HID device with all the descriptors matching a l…

There are cheats that work solely off of game recordings?

There are cheats that work just with input modification: FPS games often have a recoil simulation which requires you to adjust your aim downwards as you're firing (and it's predictable). You can make a hardware cheat device which just replays this motion when you click a button to fire, improving your aim substantially.

Re: Pac-Man recreated with a GAN trained on 50k game episodes

#100

Post by srnvs123 »

lumost wrote: post #70

I've observed an increasing trend with modern AI research that A) It's no longer practical to incorporate into real products given the hardware costs for training and inference. In NLP, large transformer based models can easily occupy a 5 thousand dollar GPU at a paltry 50-60 words per second processing pace. B) The Research often demonstrates things that existing non-ML toolchains were already reasonable at doing wi…

I don’t think that’s the point of bleeding edge research.

Pushing boundries != commercialization potential

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