DeepMind’s AI bots playing soccer in simulation.
The agents don’t communicate with each other and only try to maximize their own incentive. But teamwork and complex strategies *emerge* through repeated competition!
↓
Are you technical? Check out https://AlphaSignal.ai to get a daily summary of breakthrough models, repos and papers in AI. Read by 200,000+ devs.
DeepMind’s AI bots playing soccer in simulation.
The agents don’t communicate with each other and only try to maximize their own incentive. But teamwork and complex strategies *emerge* through repeated competition!
↓
Are you technical? Check out https://AlphaSignal.ai to get a daily summary of breakthrough models, repos and papers in AI. Read by 200,000+ devs.
DeepMind’s AI bots playing soccer in simulation.
The agents don’t communicate with each other and only try to maximize their own incentive. But teamwork and complex strategies *emerge* through repeated competition!
↓
Are you technical? Check out https://AlphaSignal.ai to get a daily summary of breakthrough models, repos and papers in AI. Read by 200,000+ devs.
It’s interesting to see how teamwork emerges as a successful strategy, even in a non-collaborative game.
It shows how collaboration can naturally arise, even when agents are focused solely on their own incentives.
AI keeps revealing fascinating insights, and it’s a great reminder of how game theory principles play out even in simulations!
#AI#Teamwork#GameTheory
DeepMind’s AI bots playing soccer in simulation.
The agents don’t communicate with each other and only try to maximize their own incentive. But teamwork and complex strategies *emerge* through repeated competition!
↓
Are you technical? Check out https://AlphaSignal.ai to get a daily summary of breakthrough models, repos and papers in AI. Read by 200,000+ devs.
Cooperation and Teamwork Proven as a Mathematical Emergent Evolutionary Processes through AI Training.
This video from Google’s DeepMind offers a fascinating glimpse into the process of training humanoid bots to play soccer from scratch, with zero prior knowledge. Through neural net training and reinforcement learning with human feedback (RLHF), these bots embark on an iterative journey that parallels human evolution—repeated cycles of failure, success, and adaptation.
Initially, the bots know nothing of soccer. Yet through countless trials, they learn to kick, dribble, and eventually pass the ball. What’s truly remarkable is that teamwork and cooperation emerge as complex, evolving behaviors. The bots discover that collaborating with teammates greatly improves their chances of scoring and winning.
This emergent cooperation reflects the arc of human development, where interaction, feedback, and adaptation lead to higher-order behaviors. Like nature’s trial-and-error process over millennia, the bots’ learning is driven by complexity and refinement. What begins as isolated action transforms into a cooperative strategy—teamwork as an emergent evolutionary necessity.
A powerful reminder of how complexity, RLHF, and neural net training echo Darwinian models while revealing teamwork as a surprisingly evolved adaptive trait.
#AI#Emergence#Complexity#ReinforcementLearning#Evolution#Teamwork
DeepMind’s AI bots playing soccer in simulation.
The agents don’t communicate with each other and only try to maximize their own incentive. But teamwork and complex strategies *emerge* through repeated competition!
↓
Are you technical? Check out https://AlphaSignal.ai to get a daily summary of breakthrough models, repos and papers in AI. Read by 200,000+ devs.
DeepMind’s AI bots playing soccer in simulation.
The agents don’t communicate with each other and only try to maximize their own incentive. But teamwork and complex strategies *emerge* through repeated competition!
↓
Are you technical? Check out https://AlphaSignal.ai to get a daily summary of breakthrough models, repos and papers in AI. Read by 200,000+ devs.
I really enjoy building out my Battle Simulation model. My AI Agent now uses game theory as well as the open internet to research battle tactics and find way to overcome an enemy force. Check it out and let me know what you think! #AIagents
𝐓𝐞𝐬𝐭𝐢𝐧𝐠 Midjourney'𝐬 𝐢𝐦𝐚𝐠𝐢𝐧𝐚𝐭𝐢𝐨𝐧!
I asked the famous AI model for generating football stadiums while increasing the in each image and here are the results!
Curious about the last slide. Any thoughts? 💡
🎉🎉Kling AI video generator tool is now open to everyone!🎉🎉
🤓You just need to log in using your email here, https://klingai.com , and you’ll get 6 free generations per day using text-to-image or Image-to-Image.
🦾This is my first quick test on the fly, using a random image from Deadpool & Wolverine movie which I want to watch soon.
🐺I used img-to-video and uploaded that image, using the prompt “Deadpool and Wolverine celebrate a goal together”.
(I was thinking about football but didn’t specify that so the model could have understood any other goal definition 😅)
🙌🏻As you can see, while faces and hands are a bit distorsioned, the consistency of the image is really good. Even more, given the lack of details provided on my lazy prompt.
I’ll play a but more with it and share more ideas soon. Feel free to play as well now that it’s open to everyone and share with us here! 😉
Learn about all things GenAI in this Federal News Network AI & Data Exchange Interview with #GuidehouseExpert Bassel Haidar! Some inside baseball, Bassel is a master of communicating complex concepts to folks like me - thank you!
Technologist & Operator (Casually exploring)
1wAny potential practical applications —besides video games development I guess—?