sentdex

Hey I work @ Lucky Robots.

The differences are pretty big, but the simplest way to illustrate is to try to use gazebo, isaac...etc, and then try to build a whole physically interactive kitchen.

First off, it's gonna take you 3 months to author that thing, if you don't ragequit along the way.

Then, when you go to run, your "50 million steps per second" sim becomes 500 steps per second.

The reason we have robots doing backflips and acrobatics instead of actually useful stuff like picking up your house is making the scenes and getting the data is tough. It requires sensors like cameras and rendering, vs purely proprioceptive-only envs with a flat ground plane and no other physics interactions.

Right now, the industry is doing manual teleop to collect data because it's straight up easier than trying to build these sorts of things in simulators.

This is why we're building Lucky.

Odd, pretty sure it was you who misrepresented what I said in attempts to manipulate.

You were also the one who "exaggerat[ed]" my claims. I made a general statement about my thoughts about future AI-based software rather than human-coded.

I still think that's indeed the inevitable future. Doesn't seem like it's remotely outrageous or an exaggerated. I never said GameGAN would be that software, but you seem to want to make that be the case so you can put it down.

What makes you believe neural networks aren't or could not be deterministic? What makes you think NNs could not eventually produce far more robust, reliable, and secure operating systems?

Seems obvious to me, but I guess you're more informed than me :)

Memorizing a static succession of frames with nothing actually being dynamic and interactive isn't the same challenge as this.

No, that's just false. How about a direct quote?

I suggested there could be a "future where many game engines are entirely or even mostly AI based like this. Or even things like operating system or other programs."

The thought here was just a wondering of what the future might be and if we might have far more AI based programs.

I still think the answer is a strong yes, this is a glimpse into the future. No where did I say GameGAN would be that engine. You're just trying your hardest to hate.

Hah, awesome! Any plans to apply GAN Theft Auto to something else? :o

We'd like to try some further GTA stuff, as well as some IRL stuff. Have seen some recent IRL GAN stuff, and it looks super interesting.

There's just something about AI-based environments that is particularly intriguing!

I don't see why not. Might be something fun to try tbh.

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 any generalization. I imagine the original GameGAN researchers from NVIDIA would be interested too.

Interesting @ guided diffusion, not aware of its existence til now. We've had our heads down for a while. Will look into it, thanks!

> I immediately felt insincerity bordering on scamming the audience

MFW I read this. Jeez man. Model size is 173MB. It didn't just memorize every possible combo.

How the hell you went from our excitement about a fun project we shared on YT to accusing us of "scamming" the audience I really don't know. What a terribly rude and hateful attitude you have =/

We had ~100GB of data (and that was gzip compressed data). The final model is 173MB.

It's simply not large enough to have memorized every combo.

In the end, everything is boiling down to matrix math, so you can always make the argument that no neural network is impressive if you want.

The model's size is ~173MB, depending on settings. That's not much space to have memorized every single possible combination of events, nor was our data enough to cover that either.

The GAN model is the game environment. You're playing a neural network. The novelty is no game engine, no rules, just learned how to represent the game and you can play it.

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.

When you take an algorithm from a book, or copy and paste from stack overflow, you put a comment in the code with a link to the source, really no different than how you'd cite a quote in a paper.

To me, it just doesn't seem like it's even remotely challenging to figure out how to do this, or when to do this. If it's not yours, say where you got it.

When in doubt, cite it. What exactly would the harm be if you cited something when you weren't sure if it was necessary, anyway?

The plagiarism that I personally see is specifically code plagiarism. I am a programming educator on youtube.com/sentdex and pythonprogramming.net

Lately, I have been digging into this, and it's far more rampant than I ever expected (I am still digging, but we're talking in the 10's of thousands of examples that I've found with basic automated searching just in matches to my own personal code). I have found some seriously absurd examples where an entire portfolio consists of my code, and the person got a job from it at a large company.

Compare a student who writes their own code to the student who plagiarizes.

If you're the non-copy-pasta student, you're competing with the fakes for jobs.

If you're an employer, you're tasked with figuring out who is who, and I strongly doubt you would personally want the copy-paster at your business for both legal and productivity reasons.

I think some people confuse plagiarism and innovation, especially when we start to wrap in "intellectual property" into it.

Plagiarism is a shortcut used to fake skills/credentials.

Innovation is a real skill, though could be debated I am sure.

Intellectual property value is up for debate.

People who are cheating/faking their way, lying about their value/skills harms both employers and students.

Just don't let people debating about plagiarism try to sneak in innovation/building-upon as a means of a straw man.

We're talking copy and paste here. Maybe some synonym swaps.

Using transfer learning on top of a DCTTS model (deep convolutional text to speech), I wanted to see how quickly one could recreate voices remotely convincingly.

TLDR/W, using ~15 minutes of audio and about 1.5 hours of training, I was able to create what I think are pretty good examples of voices of myself, Donald Trump, Obama, Musk, and Joe Rogan.

None are perfect, and very much still a work in progress, but maybe something you might want to note that exists now (and has for years).

Even if you don't post videos of yourself on YouTube, your audio is almost certainly stored, tagged by your name, by Google (Assistant), Apple (Siri), Amazon (Alexa), and probably many other providers.

People just expect it to happen much too quickly, there's no patience.

The time it takes to get from say a car that just drives about randomly to a car that drives pretty well 75% of the time is about a day's worth of work with today's technology. Going from 75-80% is a week or two. 80-85% is months. Getting to the 90% is years, and who knows what we need for 99+%.

I did a self-driving car in GTA V project that streamed on Twitch 24/7. If the car wasn't improving noticeably day by day, people were getting angry and frustrated, as if the car was meant to be perfectly driving within months, surely!

There's definitely a major disconnect between the hype and reality of what the challenge of self-driving cars is. The bubble is just simply bursting at the moment, but the dream itself is not dying amongst actual engineers. It's just dying for the people who never understood how absolutely challenging the problem actually is.

I've just never felt the urge to post on hacker news, but it's in my list of places I check frequently for news, I just lurk though. Maybe it's because I dunno how to hacker news, but I just look at the front page. Usually, by the time I am seeing something on HN, whatever I think or have to offer has already been said, usually more eloquently than I'd come up with.

I have more of a presence on reddit (https://www.reddit.com/user/sentdex/). The bar is lower there. ;)

For news, I have a bookmark dir with a bunch of sources in it, I right click and open all whenever I want to check in and see what the world is up to.

Hey there, author here. It's just me who does the entire site of pythonprogramming.net and the youtube channel.

The way I have gone about things has changed over time, but I have found the worst way to do documentation is to write 100% of the code, the full series in this case, then go back and document/write a tutorial on it.

I used to just do the videos, but had lots of requests to do write-ups too, so I started that and really hated it at first, because I was just timing it all wrong.

So now, I usually will do maybe 1-5 videos, and then make sure to do the write-ups on them before continuing...otherwise the write-ups suffer significantly. I also try to do the write-ups in the same day, and before I personally progress on to the next topics.

It's just hard, because the last thing I want to do after I've made something that I think is cool is document it.

Other times I will actually work locally, and just either save my scripts in a step-by-step manner, or just work in an ipython notebook to save the steps I took in development, and then film the video, and then go back to the notebook to do the documentation.

Not sure that really helps much, it's an "it depends," but the main thing is to not get too far ahead of any accompanying documentation.

Wow, hello hacker news! I haven't seen pythonprogramming.net load this slow in a ... ever.

Thanks for sharing my silly project!

Any ideas, pull requests, or critiques are welcome. (https://github.com/sentdex/pygta5/)

I'm currently working on PID control, and also contemplating switching the model to a DQN, with a reward for speed (whether this is perceived, or read from the game directly) IF we're on a paved surface. If you know about either, don't be shy.

If you hate long loading, you can watch just the videos on youtube: https://www.youtube.com/playlist?list=PLQVvvaa0QuDeETZEOy4Vd...

edit: added link to github, as well as links to just the videos since pythonprogramming.net is going slow from traffic.

Any chance you know how to implement PID control? I'm still throwing errors. Last night I was looking through a pull request that threw a breaking error and realized it was due to two uses of D (one for the key, one for the D in PID). Still having issues though after fixing that.

If you have any ideas: https://github.com/Sentdex/pygta5/pull/3

Part of my idea for this course was that you could use these methods on any game. You don't need anyone to make an API, you read the frames in, send direct keys, and you're all set.

That said, there are various things like scripthookpy that let you communicate with GTA V to do things other than AI with Python.

I am personally more curious about the AI aspect, so I figure any game that I can play visually, an AI can too with these methods.

Thanks for sharing this, will definitely look into it. With the ever improving FPS, this AI's reflexes are going to be insane.