Congratulations also to Patrick 👍 for his #ICLR paper... on Temporal Difference (TD) learning , in it We solve the decades-old puzzle of why TD can solve complex RL tasks that Gradient Descent cannot.show more

RL is back! But is it always the best... choice? In a new paper, we investigate under what circumstances neuroevolution outperforms RL in transfer learning tasks. See more details in the thread below 🧵 While NE performs best in simpler domains, it will be interesting to see if the lessons learned here can also be applied to more complex systems/tasks (LLMs?).show more

Tick Tock ⏰ Can you solve the clock puzzle?

1/ While most RL methods use shallow MLPs (~2–5... layers), we show that scaling up to 1000-layers for contrastive RL (CRL) can significantly boost performance, ranging from doubling performance to 50x on a diverse suite of robotic tasks. Webpage+Paper+Code:show more

Can Indy solve the Serpent Puzzle? The Order of... Giants DLC is available now for #IndianaJones and the Great Circle.show more

Can Vision-Language Models Solve the Shell Game? paper:

Congrats to Mario 👏 for the accept of his... ICLR paper on "Diffusion Graph Nets", predicting complex distributions of flow states on unstructured meshes Highly efficient, works even if the training data has only a fraction of the flow statistics.show more

Congratulations to QB Grant Jordan, earning the College GameDay... helmet sticker for his 7 TD performance on Saturday! #Team151show more

WE WON $5000 SOLVING THE RUST PUZZLE IN theburntpeanut... SERVER!💰 GG's to everyone! WAS SO MUCH FUN TO SOLVE!!🎯show more

Robots struggle with strict action rules…memory and symbols help... them learn fast. [Project + Full video link ⬇️] Robots struggle when tasks require specific steps in a fixed order. What if memory helped them think symbolically and learn faster? Solving tasks like unlocking a door then opening it is hard for deep RL. But by learning constraint relationships and storing them in memory, robots can solve these tasks much faster; with fewer trials and less training. Why it works ✅ Learns symbolic rules about action constraints ✅ Uses memory to transfer what it learned across tasks ✅ Handles real-world exploration with just 30 minutes of data ✅ Needs 10x fewer episodes than deep RL approaches This memory-based method shows a promising path forward for robots learning structured, real-world tasks. Full video: Paper: Thank you, Mrinal Verghese for sharing this amazing work! 🙏show more

Jonathan Taylor runs it in for his 2nd TD... of the day! LVvsIND on FOX/FOX Oneshow more

My favorite paper this year: "Video models are zero-shot... learners and reasoners" It illustrates that video models show emergent visual reasoning at scale - they can solve vision tasks they weren't trained for. This may be the "GPT moment" for vision. Let's break it down 👇show more

It’s like trying to solve a puzzle cube .

Be honest… How long would it take you to... solve this puzzle? 🤔🧩show more

Patrick Mahomes to Jason Brownlee for a beautiful back... shoulder TD! Stream on NFL+show more

Kenneth Gainwell gets his second TD of the day... MINvsPIT on NFL Network Also streaming on NFL+show more

Gradient experiment in Paper and I genuinely cannot stop

Patrick Mahomes finds Noah Gray for the TD 📺:... #KCvsCLE on CBS/Paramount+ 📱:show more

If can Tesla AI can solve the most infamous... round about in the world in France, they can solve India.show more

How can we solve the issue with trump? Most... of yall:show more

You CANT solve Suzy Snacktime’s puzzle 🍭