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Insane New AI Recreates Games Like GTA and RDR2 and Let's You Play Them Live
High tech & Ai world
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9/17/2024
A groundbreaking new AI called gamegen-0 can instantly re-create open world AAA games like GTA and red dead Redemption, allowing Users to play theml live in real time.
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🤖
Tech
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00:00
Game development is about to change in a big way, and it's all thanks to Game Gen O,
00:07
the first AI model designed specifically to generate open-world video games.
00:12
This technology has the power to create entire game worlds, characters, and events from scratch,
00:18
pushing the limits of what we thought possible in gaming.
00:21
Game Gen O is the first-ever diffusion transformer model specifically designed to generate open-world
00:26
video games.
00:28
I know that might sound a bit technical, but stick with me because I promise you, it's
00:32
worth it.
00:33
We're talking about a whole new way of creating video games, so this is a model that can generate
00:37
high-quality open-world content on the fly.
00:41
It doesn't just spit out pre-programmed environments or characters, it actually simulates
00:45
everything.
00:47
Think of innovative characters, dynamic environments, complex actions, and diverse events, all generated
00:52
from scratch by an AI.
00:54
Oh, and did I mention that this model provides interactive controllability too?
00:58
Yeah, we're talking about a future where game engines could be replaced by AI models
01:03
like this one.
01:04
Let's go through this step-by-step, and by the end, you'll see why this technology
01:07
marks a major breakthrough for gaming.
01:10
Now, Game Gen O didn't just pop out of nowhere.
01:12
The development team at Tencent, yeah, the giant company behind some of the most popular
01:16
games on the planet, put in some serious work to get this off the ground.
01:21
And they didn't just start with some basic game data either.
01:24
They built something called O Game Data, which is a massive dataset specifically tailored
01:29
for open-world video games.
01:31
Now, O Game Data is key here.
01:34
Tencent compiled 32,000 raw videos from various sources, including the internet and game engines.
01:40
The clips range from a few minutes to several hours of gameplay, featuring over 100 next-generation
01:45
open-world games like Red Dead Redemption 2 and GTA 5.
01:49
This massive collection forms the foundation for training Game Gen O.
01:54
The team then filtered these clips down to about 15,000 usable videos, which were broken
01:59
up into smaller clips using scene detection.
02:01
These clips went through a process that looked at their aesthetics, optical flow, and even
02:05
their semantic content.
02:06
In simple terms, the AI sorted through all the visual and gameplay elements, ranking
02:11
and scoring the clips so that only the best made it through to the next stage.
02:15
After that, they added detailed annotations.
02:18
So basically, there is a human expert sitting down, labeling these clips with everything
02:23
from environmental details to character actions.
02:26
On top of that, they used multimodal large models, think GPT-4 but trained for video
02:31
games, to further enhance these annotations.
02:35
The result?
02:36
A super detailed interactive dataset that forms the core of what Game Gen O is trained on.
02:40
Alright, so let's talk about the training process.
02:43
Game Gen O's development happens in two key stages.
02:46
The first is called foundation pre-training, and here's where things get really technical.
02:50
The team used something called a 2 plus 1 DVAE, variational autoencoder, specifically
02:55
a version of MagVit V2, to compress the video clips.
03:00
This VAE was adapted specifically for the gaming domain, meaning it could handle the
03:04
unique challenges of generating game-like content.
03:07
During this stage, the model learned to generate text to video content.
03:11
So essentially, Game Gen O can take a simple text description and turn it into a fully
03:16
rendered video.
03:17
Not just that.
03:18
But it can also continue an existing video, making it perfect for open-world game generation
03:24
where the story and environment evolve over time.
03:27
Next up is the instruction tuning stage, which is where things get interactive.
03:32
At this point, Game Gen O has already learned how to generate high-quality video clips,
03:36
but now it's time to give it the power to respond to multimodal inputs.
03:40
Things like structured text prompts, operation signals, and video prompts.
03:44
This is what gives the model its interactive controllability, meaning it doesn't just
03:49
generate content passively, it can respond and adapt to changes based on what's happening
03:54
in the game world.
03:55
For example, let's say you input something like, make the sky dark and stormy, and the
04:00
model generates a dark, moody environment.
04:03
Then you could follow up with a command like, move the character forward, and the AI would
04:07
dynamically adjust both the character and the environment in real time.
04:12
Alright, now the fun part.
04:14
What kind of stuff can Game Gen O generate?
04:17
The capabilities of this model are truly impressive, because the range of what this model can create
04:22
is just enormous.
04:24
Character generation?
04:25
Yes, it's all there.
04:27
Think of characters like Geralt of Rivia, Arthur Morgan, or even Robocop.
04:31
But it doesn't stop with familiar faces.
04:33
Game Gen O can generate completely original characters like a Venom Druid touring Rune
04:38
Forest, or a Cybermonk roaming through a futuristic Chinatown.
04:42
So whether you're looking for something realistic or more fantasy-based, this model
04:46
has it covered.
04:47
Then there's environment generation.
04:49
You can create anything from lush lavender fields to vast pyramids in the desert, or
04:53
even something as surreal as a traveler walking on Mars.
04:57
And we're not just talking static images here.
04:59
The AI can generate dynamic environments where things change over time, seasons shift, the
05:04
weather evolves, and events like snowstorms, tsunamis, and tornadoes unfold in real time.
05:11
Action generation is another big one.
05:13
Game Gen O can generate everything from motorcycle chases in first-person to horseback riding
05:18
in third-person.
05:19
Whether your game involves high-speed action like flying or something more grounded like
05:23
walking, the model can simulate it with impressive accuracy.
05:27
And then there's event generation.
05:30
Imagine a game where at any moment a random event like a sandstorm or sunrise could completely
05:35
change the vibe.
05:37
With Game Gen O, you can generate those events dynamically based on the storyline or player
05:42
actions.
05:43
Now, one of the most impressive aspects of this technology is its interactive control.
05:48
For example, during gameplay, you can input commands such as move the character left or
05:53
increase the intensity of the storm.
05:56
And the AI will instantly respond, generating the next scene or action based on those instructions.
06:02
This real-time adaptability allows for dynamic and responsive gameplay that adjusts to your
06:08
actions.
06:09
The core of this interactivity is InstructNet, a branch of Game Gen O designed to handle
06:13
multimodal inputs.
06:15
So whether you're giving it structured text like fire on the sky or operation signals
06:19
like move right, the model knows how to generate the next set of content accordingly.
06:23
It's this real-time interaction that makes Game Gen O stand out as more than just a fancy
06:28
video generator.
06:30
Right now, Game Gen O can generate what you'd call simulated gameplay, meaning it's not
06:35
yet fully interactive in the way traditional games are.
06:39
You can't control every little movement in real time, but Tencent has already hinted
06:43
that future versions will allow for more direct control over the game world.
06:47
So yeah, the future of AI-generated games where you can have full control isn't that
06:51
far off.
06:53
Game Gen O may seem similar to Roblox, where users create their own games, but the key
06:58
difference is that Game Gen O targets professional developers.
07:02
While Roblox is for casual creators, Game Gen O automates complex tasks that typically
07:07
take large teams months or even years to complete.
07:10
This model could potentially democratize game development, meaning smaller teams or even
07:14
individual developers could use it to create triple-A level games without the need for
07:18
massive resources.
07:20
And when you think about that, the implications are huge.
07:23
This could fundamentally change how games are made, opening up the industry to more
07:27
diverse voices and creative ideas.
07:30
The potential for Game Gen O goes beyond video games, extending into virtual reality, filmmaking,
07:35
and city design.
07:37
Tencent's GeneX, another AI model, is already generating large-scale cities.
07:42
And when combined with Game Gen O, it opens up possibilities for creating entire virtual
07:47
worlds and fully interactive films.
07:49
However, this raises serious concerns around intellectual property and copyright.
07:54
If AI generates content based on existing games, the boundaries of ownership become
07:58
unclear.
07:59
These are issues the industry will need to address as models like Game Gen O grow in
08:03
use.
08:04
We're really only at the beginning stages of what this technology can do.
08:08
In just a few years, it's entirely possible that games could be fully generated and controlled
08:13
by AI.
08:14
So what do you think about Game Gen O?
08:16
Could this be the future of gaming, or are we still far from fully realizing AI-driven
08:21
game worlds?
08:22
It's an exciting time in tech, and I'm eager to see how it all unfolds.
08:25
Alright, don't forget to like, subscribe, and comment for more updates on tech and gaming.
08:30
Thanks for watching, and I'll see you in the next one.
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