The future of game development... has no game engine?

Summary

Google and Tel Aviv University's paper introduces a revolutionary neural network-based game engine, 'Game and Gen,' which generates real-time gameplay without coding. The technology, inspired by the 1993 classic 'Doom,' uses stable diffusion and reinforcement learning to simulate environments and player actions. While the engine is in its infancy, it hints at a future where game development could be transformed, with potential applications in robotics and real-time environment simulation.

Takeaways

• 🎮 Google and Tel Aviv University have published a paper on a new game engine called 'game and gen', which is entirely neural network-based and does not require traditional coding for level development.
• 🔮 The game engine uses stable diffusion .4 and a reinforcement learning agent to simulate real-time gameplay at 20 frames per second, including environment, collisions, and graphics.
• 👨‍💻 The script mentions John Carmack, the lead developer of Doom, who is now working on artificial general intelligence, highlighting the evolution of game development from 2D sprites to advanced AI-driven engines.
• 👽 The technology behind 'game and gen' is not yet practical for commercial game development, but it hints at a future where AI could generate game content dynamically.
• 🤖 The script suggests that the real-world application of this technology could be in robotics, where real-time environment simulation could train robots without the need for physical hardware.
• 🧩 The concept of 'auto-regressive drift' is mentioned, which is a challenge in maintaining the quality of gameplay over longer sequences in AI-driven engines.
• 🕊️ Google's Project Talent is introduced as a new device designed for humane capital punishment, showing the diverse applications of AI and robotics in society.
• 🚀 Elon Musk's Optimus robots, Nvidia's project Groot, and Google's investment in robotics research are cited as examples of the race to develop advanced humanoid robots.
• 🌐 The script ends with a philosophical reflection on the future of AI and robotics, suggesting that biological evolution may come to an end as machines start to outthink their creators.

Q & A

What significant development in the gaming industry was announced by Google and Tel Aviv University?

Google and Tel Aviv University published a paper about 'Game and Gen,' the world's first entirely neural network-based game engine that can simulate environments, collisions, and graphics in real time without any traditional coding.

What is the difference between the graphics technology used in the original Doom game and modern 3D games?

The original Doom game used 2D sprites rendered at fixed angles, a technique known as 2.5D graphics or billboarding, whereas modern 3D games use billions of triangles and linear algebra to render true 3D objects.

Who is John Carmack, and what is his contribution to the gaming industry?

John Carmack is a legendary programmer and lead developer of Doom. He is known for creating Doom, Wolfenstein, and Quake, and for open-sourcing the Doom engine in 1997, which inspired a generation of new programmers. Currently, he is working on artificial general intelligence at Keen Technologies.

What is 'stable diffusion' and how is it used in the new game engine?

Stable diffusion is a technology that the new game engine relies on. It is an augmented version of stable diffusion .4, trained to predict the next frame of a sequence based on past frames and actions.

What is the role of the reinforcement learning agent in the game engine?

The reinforcement learning agent is trained to play the game and record itself, similar to an artificial Twitch streamer. It helps in addressing auto-regressive drift and maintaining the quality of gameplay over sequences.

What is auto-regressive drift, and how does the game engine address it?

Auto-regressive drift refers to the decrease in the quality of gameplay over longer sequences. The game engine addresses this by using a model with a limited context window of about 3 seconds or 60 frames, which is sufficient for real-time gameplay in fast-paced games like Doom.

Does the new game engine make game developers obsolete?

No, the new game engine does not make game developers obsolete. While it can generate new terrain, NPCs, and storylines, it is currently barely playable and has no practical application for the time being. It is expected to complement developers' work in the future.

What is the potential application of this technology in the future of game development?

In the future, developers could use reinforcement learning agents to play and generate new content in games, combined with futuristic generative 3D models to create unique terrains, NPCs, and storylines on the fly.

What other industries could benefit from this technology apart from gaming?

This technology could have real-world applications in robotics, where real-time environment simulation would allow robots to train rapidly without physical hardware.

What is Google's Project Talent, and how does it relate to the new game engine technology?

Google's Project Talent is a new device designed for capital punishment, which is unrelated to the new game engine technology. It was mentioned in the script as an example of Google's investment in technology, but it does not have a direct connection to the game engine.

What is the potential impact of this technology on robotics and AI development?

The technology could significantly advance robotics and AI by enabling rapid training of robots in simulated environments, potentially leading to more sophisticated and autonomous machines.

Outlines

00:00

🎮 AI-Powered Game Engine Revolution

Google and Tel Aviv University have unveiled a groundbreaking paper introducing 'Game and Gen', the world's first neural network-based game engine. This engine, showcased through a simulated environment of the classic game Doom, operates in real time at 20 frames per second without any traditional coding. The technology combines stable diffusion to predict game progression and a reinforcement learning agent to mimic gameplay. The implications of this advancement are vast, suggesting a future where game development could be significantly streamlined through AI, although current applications are limited and the technology is not yet ready for practical use.

Keywords

💡Game Devs

Game Devs, short for game developers, are professionals who create video games. They are integral to the gaming industry, designing and programming the mechanics, storylines, and graphics of games. In the video, the term is used to highlight the potential impact of AI on game development, suggesting that AI could eventually take over some aspects of game creation.

💡AI Doomers

AI Doomers refers to individuals who believe that the advancement of artificial intelligence will lead to negative outcomes, possibly even the end of human civilization. The video mentions them in the context of AI's role in game development, suggesting that some may fear AI's growing capabilities could replace human developers.

💡Neural Network

A neural network is a type of machine learning model inspired by the human brain that is capable of recognizing patterns. It is composed of layers of artificial neurons and is used for various tasks, including image and speech recognition. The video discusses a neural network-based game engine, which is a significant technological advancement in the gaming industry.

💡Doom

Doom is a classic first-person shooter video game released in 1993, known for its revolutionary 3D graphics and gameplay at the time. The video script uses Doom as a reference point to illustrate the evolution of game technology, from 2D sprites to real-time 3D environments generated by AI.

💡2.5D Graphics

2.5D Graphics, also known as billboarding, is a technique used in older games like Doom where 2D images are manipulated to create the illusion of a 3D environment. The video explains that Doom was not a true 3D game and used this technique to render its environments, which is a key concept in understanding the evolution to AI-generated graphics.

💡John Carmack

John Carmack is a legendary programmer and game developer, known for creating Doom, Wolfenstein, and Quake. He is mentioned in the video as the lead developer of Doom and for his contributions to the gaming industry, including open-sourcing the Doom engine, which inspired many programmers.

💡Stable Diffusion

Stable Diffusion is a type of AI model used for generating images from text descriptions. In the context of the video, an augmented version of Stable Diffusion is used in the game engine to predict and generate the next frame of the game based on past frames and player actions.

💡Reinforcement Learning

Reinforcement Learning is a branch of machine learning where an agent learns to make decisions by performing actions in an environment to maximize some notion of cumulative reward. The video describes how a reinforcement learning agent is used in the game engine to play the game and record its actions, contributing to the AI's ability to generate gameplay.

💡Auto-regressive Drift

Auto-regressive drift refers to the phenomenon where the quality of generated content decreases over time due to the limitations of the model's context window. The video mentions this challenge in the development of the game engine, where maintaining the quality of gameplay over longer sequences is a concern.

💡Robotics

Robotics is the branch of technology that deals with the design, construction, operation, and use of robots. The video suggests that the real-world application of the technology discussed, such as real-time environment simulation, will have significant implications for robotics, allowing for more efficient training of robots without the need for physical hardware.

💡Artificial General Intelligence (AGI)

Artificial General Intelligence refers to the hypothetical ability of an AI to understand, learn, and apply knowledge across a wide range of tasks at a level equal to or beyond that of a human. The video mentions that John Carmack is currently working on AGI at Keen Technologies, indicating the pursuit of advanced AI capabilities beyond specific, narrow tasks.

Highlights

Google and Tel Aviv University published a paper on a neural network-based game engine.

The new game engine generates environments, collisions, and graphics in real-time without traditional coding.

The technology is showcased through a 2024 version of the classic game Doom.

Doom's 2.5D graphics technique, also known as billboarding, is explained.

John Carmack, lead developer of Doom, is recognized for his contributions to game development and current work in AI.

The game engine is based on an augmented version of stable diffusion .4 for frame prediction.

A reinforcement learning agent is used to play and record gameplay.

Google's combination of reinforcement learning and generative AI is highlighted in projects like Alpha Coder and Alpha Proof.

The challenge of addressing auto-regressive drift in the model is discussed.

The model's limited context window and its implications for real-time gameplay are explained.

The potential for this technology to make game developers obsolete is considered and refuted.

Future applications of the technology in game development, such as dynamic terrain and NPC generation, are speculated.

The real-world application of this technology in robotics and environment simulation is highlighted.

Google's Project Talent, a device for capital punishment, is mentioned with its humane design.

The current state of robotics with companies like Tesla, Nvidia, and Google is discussed.

The potential for AI and robots to outthink their creators and the philosophical implications are considered.

The video concludes with a reflection on the future of robotics and the end of biological evolution.

Transcripts

yesterday Google and Tel Aviv University

published a paper that put game devs and

AI doomers on life support what you're

looking at right now is not gameplay

from John CarX 1993 classic firstperson

shooter Doom it's actually a brand new

game from 2024 powered by game and gen

the world's first entirely neural

network based game engine the

environment the collisions and the

graphics are all simulated in real time

at 20 frames per second and not a single

line of code was written to develop this

level back in March Jensen Wong

predicted that most video game Graphics

could be generated by AI in real time

within 5 to 10 years if he's right when

GTA 7 comes out in 2042 just imagine

being able to run over billions of

unique NPCs across multiple parallel

universes sorry about in today's video

we'll find out how this black magic

actually works and whether or not it's

the future of game development it is

August 29th 2024 and you're watching the

code report before we can understand how

game and gen works we must first

understand Doom a game that was

revolutionary when it came out in 1993

three Not only was it a violent game

that moms hated but it was a huge

technical achievement in 3D gameplay

while the player runs around

obliterating demons from a 3D

perspective the enemies and objects are

actually just 2D Sprites rendered at

fixed angles this differs from Modern

games that use billions of triangles and

linear algebra to render 3D objects the

key takeaway here though is that Doom is

not a true 3D game and its underlying

technique is often called 2.5d Graphics

or billboarding in other words you take

a bunch of 2D images but skew and scale

them in ways that make it look like a 3D

environment it's genius so let's take a

moment of respect for its lead developer

and legendary programmer John carmac not

only did he create doom and Wolfenstein

and Quake but he opened Source the Doom

engine in 1997 which inspired an entire

generation of new programmers currently

he's working on artificial general

intelligence at Keen Technologies and

let's hope he gets there before Sam

Alman does but now that you understand

how Doom is just a bunch of 2D Sprites

game and gen becomes a little less

magical which is based on stable

diffusion it relies on an augmented

version of stable diffusion .4 which is

trained to predict the next frame based

on the sequence of past frames and

actions and the other big component of

the architecture is a reinforcement

learning agent which is trained to play

the game and record itself like an

artificial twitch streamer Google has

taken a lot of L's recently but it's

also been shipping some amazing Tech

especially when it combines

reinforcement learning with generative

AI like Alpha coder uses a similar

technique to beat virtually all

competitive programmers and Alpha proof

can beat almost all math olympiads but

when it comes to the game engine their

biggest challenge was addressing Auto

regressive drift where the quality of

gameplay starts to decrease over longer

sequences the model only has a limited

context window of about 3 seconds or 60

frames but in a fast-paced game like

Doom that's all you need for real-time

gameplay and despite the small context

it does keep track of health and ammo

based on the actions taken by the player

the big question though is does this

make game developers obsolete the answer

of course is no this game is barely

playable and the tech has no practical

application for the time being but in

the not so distant future you could

imagine a developer like Rockstar Games

using an RL agent to play the GTA world

combined with some futuristic generative

3D model they can spit out new terrain

NPCs and even story lines on the fly but

you really shouldn't be playing video

games because women find it the most

unattractive hobby for men the real

world changing application of Technology

like this is going to come in robotics

real-time environment simulation will

allow robots to train rapidly without

physical Hardware like when it comes to

Capital Punishment it's extremely hard

to gather enough data for a large model

well not anymore thanks to Google's

Project Talent the new device is

designed to be as Humane as possible

emitting soothing white noise and

putting prisoners on a cushioned seat

before its metallic Talons dig into

their necks and painlessly wrench their

heads off the figure 2 robot was just

released a few weeks ago Elon is

building Optimus robots Nvidia recently

unveiled project Groot Google's

investing heavily in robotics research

and they're all trying to make

Terminator like humanoid robots a thing

and if they succeed we'll have to put

yet another dollar in the arthury Clark

was right jar future does belong to the

robots biological evolution has about

come to its end they will start to think

and eventually they will completely

outthink their makers is this depressing

Yep this has been the code report thanks

for watching and I will see you in the

next one