Other TH-camrs would worry only about the amount of views that they get in their videos. Károly is the only one I've seen that sacrifice views in order to give his audience a better understanding of certain topic in which he's not an expert. Respect!
"It's not about winning this particular game, it's about playing in such a way that you get invited to the maximum number of games." -Jordan Peterson (Maps if Meaning lecture "Story and Meta-Story")
Attaching these nice graphics to the environment is the best PR stunt in reinforcement learning Deep Mind did so far. I'm happy these graphics make RL more interesting to the general public. Thanks to you for enabling further dissemination!
@@GabrieleNunnari I often wish all academic departments would have a team focusing on scientific infographics and helping their researchers with beautiful figures.
@@AICoffeeBreak I do also wish that academic departments would have a team working on that, but in research there is already the bare minimum amount of money to make research itself. A proper presentation would require another big investment, or a very talented researcher that is willing to take his work to the next level and spending his valuable time in learning how to do it.
@@atlascove1810 _"Heh, as if such an absurd thing could happen."_ - Homo Sapient (evolutionary carbon lifeform) *No.[EXPUNGED],* Earth (former of New Terra)
Not it didn't. To figure out the concept of destroying other beings to defend yourself, you would first need to understand what "beings" are, have a concept of self, and figure out destruction. This agent doesn't understand anything. Don't anthropomorphize an optimization algorithm.
@@rantingrodent416 I'm not anthropomorphizing, he has to destroy the other agent to keep winning right, its purly optimising. a purly "optimising agent" advanced enough can be threat to humanity just because we are inconvinenant to its goals. Its expected but concerning that this behavior is already being seen in prototype AIs.
@@rantingrodent416 it kind of does understand it needs to defend itself, but at the same time it doesn't understand that it itself is a being, since it's just an AI with no sense of self.
Just the fact you essentially said ‘I want to talk about this, and it would get a lot of views, but I don’t feel I’m at the level of knowledge/understanding to give it a proper video yet so I’m gonna hold off’ is amazing and got my subscription. Keep up the great work!!!
@@OnEiNsAnEmOtHeRfUcKa eh, card games are a lot different controlling a character in 3d or even 2d space. You might be better off following chess and go AIs
You give them simplistic, generalised functions like "maximise your points". The AI throws stuff at the wall until it notices something that increased points and then hones in on that, and repeats until optimisation has occurred.
@@PinataOblongata is that the actual number, only a thousand? Normally I thought reinforcement algorithms take millions of games for complicated stuff like this
I keep finding myself holding on to my papers. I think even if I only had a passing interest in machine learning, I'd still be watching this channel. You've created a great portal into piquing interest and promoting learning in your field. It's a great time to be alive. And we'll see you - next time.
Justs when i thought i couldn't like your channel anymore you admit your limitations in reference to covering alphafold, which I consider the height wisdom. Keep up the great work and thanks for the inspiration.
It is amazing to think, for millions of iterations in evolution. Like the AI that runs around aimlessly for millions of games, millions of generations of creatures have died due again and again to be able to benefit the entire species through gene selection.
My favorite part of the OpenAI hide and seek experiment was when the seekers learned to exploit the physics engine by grabbing the box that they stand on, or sandwiching themselves between the wall and a ramp.
I think it's worth pointing out that the main novelty of this work is a method to generate huge variety of unique worlds with "smooth" transitions between them. Each world is defined by 3 independently generated parts: environment, players, reward functions. This allows agents to be trained on a big variety of unique tasks and this is how trained agents succeed at 0-shot holdout set of manually crafted tasks (like hide and seek and capture the flag). In some sense 0-shot learning in XLand is similar to GPT-3.
I have a feeling that there's soon going to be an A.I. (through its process of elimination) that will finally be able to always generate many trillions of very beautiful unique images from learning what each of us love.
So incredible the progress made. I can only imagine the potential this kind of AI would have within video games. It would make video games far more immersive and interesting.
Kudos for knowing when there is a topic that you are not ready to cover yet. It is an admirable ability which appears to be in short supply on the interwebs. People who can't recognize that about themselves clog up the airwaves and make it harder to find the knowledgable folks.
They teach this in Cognitive Science classes in Cognitive Psychology too; these are Agent-Based Simulations, they can be designed from multiple softwares, but this one's with a learning A.I. which strategizes between past knowledge, but also what the agents are pre-configured and how the maps can let them do or not. Example: the maze experiment is a basic one, where the programmed agent can move in all 4 directions, has limited field-of-view so when it hits a wall, it will either try another direction or backtrack and find another way.
Great video, really fascinating what these generalized agents can do. ps. Friendly neighborhood Biochemist here if you want to ask any questions about proteins that you are struggling to understand happy to help
As a structural biologist, it makes me pleasantly happy that you are giving alphaFold and the protein solving problem its due diligence! We've already started using AlphaFold in our lab to start asking some tricky questions that we had only small amounts of experimental data on. AlphaFold is certainly not perfect but boy is it impressive!
How do agents "see" in these games? I mean, is there an image-recognition progress so they can understand they see each others by checking pixel color? OR, is there a data coming from game engine (like ray-cast result from Unity, Unreal Engine or OpenGL)?
Very thoughtful of you to not speak about something you think you don't know enough about, too many people spread false information these days in an attempt to seem clever. It takes a wise man to admit ignorance.
As a minecraft parkourist, (someone who plays parkour in minecraft alot) I wonder if this ai can find ways to do jumps in minecraft with set distance to gain momentum, and distance to end goal. We've never been able to do a 5 block jump using flat momentum (like only a floor, and nothing else) and have proven it using bare force and math, untill recently when we found a common mod called optifine had an exploitable speed miscalculation (on some old versions of it) which can give a speed boost by turning over 900million degrees, resulting in an about 1.03% speed increase, making a 5 block jump possible on flat ground.
I wonder if this AI could work in a different modality, say, in language instead of 2d environment. It'd be a nice addition to some NLP neural net, like GPT-3, acting as some implementation of long-term planning.
when they prune these sort of neural nets, typically how much smaller can the memory/computational foot print become over the initially trained neural net in terms of retaining say 99% of useful functionality, or are they just not that optimizable in terms of these things because they de facto self optimize resource usage?
The AI bending the rules to get closer to the pyramid is a perfect example of how asking AI to “end human suffering” will result in ending human existence 😅
Great video! I would love to hear your thoughts on some of the things revealed in Tesla's latest AI day. A lot of it goes over my head but when you get excited about something I know I should be too. I believe they even mentioned the Photorealism Enhancement paper you made a vid of a few weeks back. Do you have a platform where you may share such thoughts as its not exactly a paper?
Can you do summary of last few years of progress of AI and near future goals and regroup of more specific games achieved by ai deepmind atari, chess etc..
He left out the part where the red AI exploited the physics by charging into a corner and leaping over the wall...because that was the only way they could win at that point.
![The moment we stopped understanding AI [AlexNet]](http://i.ytimg.com/vi/UZDiGooFs54/mqdefault.jpg)
Thumbs up for maximizing meaning.
Other TH-camrs would worry only about the amount of views that they get in their videos. Károly is the only one I've seen that sacrifice views in order to give his audience a better understanding of certain topic in which he's not an expert. Respect!
Mad respect
Lets see Paul Allens Meaning.......
His credibility was greatly enhanced by acknowledging the extent of his present abilities.
"It's not about winning this particular game, it's about playing in such a way that you get invited to the maximum number of games."
-Jordan Peterson (Maps if Meaning lecture "Story and Meta-Story")
Attaching these nice graphics to the environment is the best PR stunt in reinforcement learning Deep Mind did so far. I'm happy these graphics make RL more interesting to the general public. Thanks to you for enabling further dissemination!
I was just thinking the same. A nice graphic does allow to understand what is happening and is also "pleasing" to the eye
@@GabrieleNunnari I often wish all academic departments would have a team focusing on scientific infographics and helping their researchers with beautiful figures.
If it wasn't for videos like this (and yours) hobbyist programmers like me wouldn't be interesting in trying AI projects.
@@AICoffeeBreak I do also wish that academic departments would have a team working on that, but in research there is already the bare minimum amount of money to make research itself. A proper presentation would require another big investment, or a very talented researcher that is willing to take his work to the next level and spending his valuable time in learning how to do it.
@@justinwhite2725 :blush:
"And you would think that the Starwars references would end here, no.
Not even close, look(Luke)"
That was smooth! 3:45
I thought he was about to point out the rotating agent, and say "Ah, let's try spinning - that's a good trick".
4:00 "grabs his lightsaber, and takes the high ground"
"What a time to be alive!" could have a whole different meaning in the future when we are the hiders.
^^^^ This
I swear every robot uprising joke will be used against us.
@@atlascove1810 _"Heh, as if such an absurd thing could happen."_
- Homo Sapient (evolutionary carbon lifeform) *No.[EXPUNGED],* Earth (former of New Terra)
bump
The fall of the global economy will come first, global anarchy will be first.
Finally, true gamer AI. cant wait to see their steam libraries
What a time to be a gamer!
@@4GdaTim 😂
5:58 AI already figured out the concept that you need to destroy other beings to defend yourself, this is earlier then expected.
Actually, it was taught that
Not it didn't. To figure out the concept of destroying other beings to defend yourself, you would first need to understand what "beings" are, have a concept of self, and figure out destruction. This agent doesn't understand anything. Don't anthropomorphize an optimization algorithm.
@@rantingrodent416 I'm not anthropomorphizing, he has to destroy the other agent to keep winning right, its purly optimising. a purly "optimising agent" advanced enough can be threat to humanity just because we are inconvinenant to its goals. Its expected but concerning that this behavior is already being seen in prototype AIs.
@@rantingrodent416 it kind of does understand it needs to defend itself, but at the same time it doesn't understand that it itself is a being, since it's just an AI with no sense of self.
@@bronzehd6212 bruh its not smart enough to do anything you just said lol
I'm just throwing an idea in the air.
Do you think someone at DeepMind would be interested in helping with the video on their protein prediction tech?
That would be kind of cool. I don't think I've ever seen him invite guest speakers for topics he isn't confident in speaking about himself yet.
Great idea! I would love to see it
With a million subs I think he can get who ever he wants for a 5-minute video.
I remember that hide and seek!
I love how they made them smile and laugh while playing. It's kinda adorable.
@@webx135 Adorable until its your turn to hide
Loved how they broke the engine at some point
Get the experts to guest in your videos. Maximum meaning! Thanks for the great videos.
Have no idea whether to be excited or scared by these incredible advances!
Not long until AI makes all human decisions
Be both.
Just the fact you essentially said ‘I want to talk about this, and it would get a lot of views, but I don’t feel I’m at the level of knowledge/understanding to give it a proper video yet so I’m gonna hold off’ is amazing and got my subscription. Keep up the great work!!!
Year 2030: 2 minute papers uploads are now 10-hour documentaries 👀
That are produced by AI.
2030. No man alive
Yep, just give the AI a 2 minute video as a starting point and it extrapolates the rest.
@@Naxt366 Oh my god... Women took over the whole world?
All that exists are AI bots that produce videos and farm views from other AI bots watching to generate their own relevant content
Great respect for optimizing for meaning and teaching, instead of views. Props to you!
Took a while for another video, glad youre back!
When you're a doctorate and your videos are top quality it makes sense life will delay these masterpieces of information.
Training artificial intelligence is definitely my favorite topic as of right now. Thank you for the awesome videos. love what you do.:)
Considering the tag video was my favorite video so far this is even better since it’s improved so much
My hope for this eventually working in Super Mario 64 keeps going up.
I'm excited for when it learns to play card games.
@@OnEiNsAnEmOtHeRfUcKa eh, card games are a lot different controlling a character in 3d or even 2d space. You might be better off following chess and go AIs
Make it rediscover all the A press saves from scratch and see how long it takes
Interesting video, but I would've liked to know how these agents were trained
Yea, I would be curious to know how many games they were shown
@@devanmallory5304 They run through thousands of iterations.
You give them simplistic, generalised functions like "maximise your points". The AI throws stuff at the wall until it notices something that increased points and then hones in on that, and repeats until optimisation has occurred.
@@PinataOblongata is that the actual number, only a thousand? Normally I thought reinforcement algorithms take millions of games for complicated stuff like this
@@devanmallory5304 depends on the thing, could be thousands or millions
I find the military potential of AI frightening, the human innovation of AI downright fascinating.
I have no mouth and I must scream warned us about this
Thanks for Maximizing Meaning! DeepMind is exploring the impossible and it's inspiring to see.
I keep finding myself holding on to my papers.
I think even if I only had a passing interest in machine learning, I'd still be watching this channel. You've created a great portal into piquing interest and promoting learning in your field. It's a great time to be alive. And we'll see you - next time.
Phenomenal finding and equally spell binding narrator. Keep up the great work. Meaning will prevail.
This is so cool! Thank you for sharing in such a clear and understandable manner :)
0:20 that was the video that made me sub to your channel.
We got an 8 minute paper today!
Thanks... for making... this informative...video!
Justs when i thought i couldn't like your channel anymore you admit your limitations in reference to covering alphafold, which I consider the height wisdom.
Keep up the great work and thanks for the inspiration.
Ahh... I really love these kinds of stuff.
I hope more these kinds of game emerge and want to see their creativity!
"These agents are not preparing for an exam, they are preparing for life" ... or dear, we are doomed :D
Haven't seen interesting stuff around YT in a while, very nice
I love how you made a two minute long summary of another two minute paper.
These videos make my day!
Subscribed for maximizing meaning.📈
THANK YOU for everything you do!
Can't wait for this exact footage to make up the first five minutes of the next RL video!
It is amazing to think, for millions of iterations in evolution. Like the AI that runs around aimlessly for millions of games, millions of generations of creatures have died due again and again to be able to benefit the entire species through gene selection.
We are exactly the same except our environment is more complex and we experience time differently.
My favorite part of the OpenAI hide and seek experiment was when the seekers learned to exploit the physics engine by grabbing the box that they stand on, or sandwiching themselves between the wall and a ramp.
I think it's worth pointing out that the main novelty of this work is a method to generate huge variety of unique worlds with "smooth" transitions between them. Each world is defined by 3 independently generated parts: environment, players, reward functions. This allows agents to be trained on a big variety of unique tasks and this is how trained agents succeed at 0-shot holdout set of manually crafted tasks (like hide and seek and capture the flag).
In some sense 0-shot learning in XLand is similar to GPT-3.
I was waiting for this, bless you.
Maximizing meaning. Thank you.
Deepmind's really putting out some magic recently. I can't wait to see what this kind of research means for game agents!
I'll read the paper but I'd love a bit of information about how these AIs were trained and how the new problems were presented to them
I have a feeling that there's soon going to be an A.I. (through its process of elimination) that will finally be able to always generate many trillions of very beautiful unique images from learning what each of us love.
4:00 Takes the high ground while also spinning for a good trick, Uses both sides of the force this one does.
4:06 Don't do it Red Agent, Green Agent has the high ground!
So incredible the progress made. I can only imagine the potential this kind of AI would have within video games. It would make video games far more immersive and interesting.
I have been waiting for a new video like this every day since the hide and seek paper. ! Thank you
Incredible work done by Deep mind thank you for sharing.
It's incredibly humble that you are maximizing meaning not views.
6:27 I love the enthusiasm
Kudos for knowing when there is a topic that you are not ready to cover yet. It is an admirable ability which appears to be in short supply on the interwebs.
People who can't recognize that about themselves clog up the airwaves and make it harder to find the knowledgable folks.
can't believe its been 2 years since that open AI video.. its what got me into this channel lol
You can invite for an interview! And let the creators explain in a short amount of time, that would be a nice experiment for the channel!
Awesome vid bro!
They teach this in Cognitive Science classes in Cognitive Psychology too; these are Agent-Based Simulations, they can be designed from multiple softwares, but this one's with a learning A.I. which strategizes between past knowledge, but also what the agents are pre-configured and how the maps can let them do or not.
Example: the maze experiment is a basic one, where the programmed agent can move in all 4 directions, has limited field-of-view so when it hits a wall, it will either try another direction or backtrack and find another way.
I am so tired my eyes feel like they are about to fall out. But I need to watch this video before I sleep
The AI catch paper is already two years old?! How time flies!
Maximizing meaning. God I love this channel
Great video, really fascinating what these generalized agents can do.
ps. Friendly neighborhood Biochemist here if you want to ask any questions about proteins that you are struggling to understand happy to help
I Love these Game Ai's
I also made my own snake Ai
Thanks for educating us :D
As a structural biologist, it makes me pleasantly happy that you are giving alphaFold and the protein solving problem its due diligence! We've already started using AlphaFold in our lab to start asking some tricky questions that we had only small amounts of experimental data on. AlphaFold is certainly not perfect but boy is it impressive!
This guy single handedly made me interested in this type of things. And I think I've seen this scene before in a video.
Remember making sense is also mental. So working together is one single sense where every atom in the Universe is a sense.
How do agents "see" in these games? I mean, is there an image-recognition progress so they can understand they see each others by checking pixel color?
OR, is there a data coming from game engine (like ray-cast result from Unity, Unreal Engine or OpenGL)?
guess the 'games' backbone is standard CG. Just the decision making is AI/ML based but I might be wrong.
6:20 When deep mind is open minded and open mind is narrow minded xD
YAY YOU MADE A VIDEO ON THIS ONE 🥳🥳🥳
Thanks for this awesome video, do you have the link to the protein structure prediction paper plz? :)
i have waited a long time for a follow up on the hide and seek video and this is great!
Awesome as always!!
Very thoughtful of you to not speak about something you think you don't know enough about, too many people spread false information these days in an attempt to seem clever. It takes a wise man to admit ignorance.
Good training for Terminators!
What humble comments at the end of the video. (I believe you could do the AlphaFold ! ^^)
The hide and seek paper video was the first one I saw from you
Maximizing meaning? You just maximized my heart with that line man
sir you are great! thanks for the amazing video!
Love you man. You are a respectable person
Were do you find these papers?
Is Alpha Fold different from Auto dock Vina?
how can you differentiate learning from memorizing (or perpetual trial and error) when you run millions of trials??
What a time to be alive!
1:55 the other guy is helping to bring one of the boxes closer for his buddy.
As a minecraft parkourist, (someone who plays parkour in minecraft alot) I wonder if this ai can find ways to do jumps in minecraft with set distance to gain momentum, and distance to end goal.
We've never been able to do a 5 block jump using flat momentum (like only a floor, and nothing else) and have proven it using bare force and math, untill recently when we found a common mod called optifine had an exploitable speed miscalculation (on some old versions of it) which can give a speed boost by turning over 900million degrees, resulting in an about 1.03% speed increase, making a 5 block jump possible on flat ground.
that'd be cool
General rl ai vs baritone bot
900 million degrees quick scope
What are you smoking. You can totally do a 5 block jump, that's the furthest you can do though. And optifine is client side only. Wtf
@@Grocel512 it makes a weird calculation and just breaks it, giving more speed than usual lol
All hugs and puppies until the AI realizes that “stop the ball from touching the red floor” is best achieved by destroying either.
And I thought that Hungary had nothing going for it in the youtube scene, but here I am watching this video!
TMP: "look... Boom"
Blue agent: *Disintegrates*
I wonder if this AI could work in a different modality, say, in language instead of 2d environment. It'd be a nice addition to some NLP neural net, like GPT-3, acting as some implementation of long-term planning.
when they prune these sort of neural nets, typically how much smaller can the memory/computational foot print become over the initially trained neural net in terms of retaining say 99% of useful functionality, or are they just not that optimizable in terms of these things because they de facto self optimize resource usage?
The AI bending the rules to get closer to the pyramid is a perfect example of how asking AI to “end human suffering” will result in ending human existence 😅
I recommend Bad Writing Advice's video on evil AI
Amamazing video!!!!
Great video! I would love to hear your thoughts on some of the things revealed in Tesla's latest AI day. A lot of it goes over my head but when you get excited about something I know I should be too. I believe they even mentioned the Photorealism Enhancement paper you made a vid of a few weeks back. Do you have a platform where you may share such thoughts as its not exactly a paper?
Lex Fridman has made a video of some of the highlights from AI day,
Sounds like you might find interest in it!
AHH was waiting for part 2 of these nutty AI gamers. Love the content
What the time to be alive!! Said Skynet before getting read of mankind...
Can you do summary of last few years of progress of AI and near future goals and regroup of more specific games achieved by ai deepmind atari, chess etc..
Yes, like other comments said: thanks for maximizing meaning
ai is so incredible makes me excited for what is possible
Exactly.. what a time to be alive
1:54
that honestly made me giggle
He left out the part where the red AI exploited the physics by charging into a corner and leaping over the wall...because that was the only way they could win at that point.
@@justinwhite2725 Well, he did cover it when he did his original video on that paper, though not in this one.
@@walugusgrudenburg3068 yes, I know. But for anyone who didn't see that video its even funnier lol!
I'VE BEEN WAITING FOR THIS
5:54 I see red is doing a victory dance
I started beliving in AI with alpha go. If you play a bit of go you realize how amazing it is.
What about the methods used?