Загрузка видео...

Не удалось загрузить видео

Возникла проблема при загрузке этого видео. Это может быть связано с временными проблемами сети или видео может быть недоступно.

На главную

FP4 Explore, BF16 Train Diffusion Reinforcement Learning via Efficient Rollout Scaling paper:

AK

532,304 subscribers

12,817 просмотров • 6 месяцев назад •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Physics3D: Learning Physical Properties of 3D Gaussians via Video Diffusion Paper: (not yet) Project: Code:

Physics3D: Learning Physical Properties of 3D Gaussians via Video Diffusion Paper: (not yet) Project: Code:

MrNeRF

20,087 просмотров • 2 лет назад

Diffusion policies have demonstrated impressive performance in robot control, yet are difficult to improve online when 0-shot performance isn’t enough. To address this challenge, we introduce DSRL: Diffusion Steering via Reinforcement Learning. (1/n)

Diffusion policies have demonstrated impressive performance in robot control, yet are difficult to improve online when 0-shot performance isn’t enough. To address this challenge, we introduce DSRL: Diffusion Steering via Reinforcement Learning. (1/n)

Andrew Wagenmaker

65,261 просмотров • 1 год назад

Frontier models that use reasoning to "think" during inference are generating 5X more AI tokens per year. ✨ "Inference is now a thinking process. And in order to teach AI how to think, reinforcement learning and very significant computation was introduced into post-training," said NVIDIA CEO Jensen Huang in a recent keynote at #CES2026. Reinforcement learning is increasing computation demands across all AI scaling laws: pre-training, post-training, and test-time scaling. Learn more about reinforcement learning and AI scaling ➡️

Frontier models that use reasoning to "think" during inference are generating 5X more AI tokens per year. ✨ "Inference is now a thinking process. And in order to teach AI how to think, reinforcement learning and very significant computation was introduced into post-training," said NVIDIA CEO Jensen Huang in a recent keynote at #CES2026. Reinforcement learning is increasing computation demands across all AI scaling laws: pre-training, post-training, and test-time scaling. Learn more about reinforcement learning and AI scaling ➡️

NVIDIA AI Infrastructure

13,329 просмотров • 9 месяцев назад

🤔Want a principled way to RL your diffusion model? Check Data-regularized Reinforcement Learning (DDRL)! Post-train NVIDIA #Cosmos World Foundation models with a million GPU hours! 🤯 Novel formulation ➡️ Theoretically integrates SFT into RL ➡️ Robust to Reward Hacking 🛑 Details: #DDRL #Diffusion #RL #NVIDIA #Cosmos

🤔Want a principled way to RL your diffusion model? Check Data-regularized Reinforcement Learning (DDRL)! Post-train NVIDIA #Cosmos World Foundation models with a million GPU hours! 🤯 Novel formulation ➡️ Theoretically integrates SFT into RL ➡️ Robust to Reward Hacking 🛑 Details: #DDRL #Diffusion #RL #NVIDIA #Cosmos

Haotian Ye

78,565 просмотров • 10 месяцев назад

Reinforcement Learning for Robotics Part 2: Train a Balance Bot with PPO with Shawn Hymel Full video:

Reinforcement Learning for Robotics Part 2: Train a Balance Bot with PPO with Shawn Hymel Full video:

maker.io

18,712 просмотров • 1 месяц назад

Reinforcement learning

Reinforcement learning

Massimo

3,407,939 просмотров • 2 лет назад

ManipTrans is out on Hugging Face Efficient Dexterous Bimanual Manipulation Transfer via Residual Learning

ManipTrans is out on Hugging Face Efficient Dexterous Bimanual Manipulation Transfer via Residual Learning

AK

22,289 просмотров • 1 год назад

Train your avatars to interact with 3D scenes. We use adversarial imitation learning and reinforcement learning to train physically-simulated characters that perform scene interaction tasks in a natural and life-like manner. Today at #SIGGRAPH2023.

Train your avatars to interact with 3D scenes. We use adversarial imitation learning and reinforcement learning to train physically-simulated characters that perform scene interaction tasks in a natural and life-like manner. Today at #SIGGRAPH2023.

Michael Black

46,237 просмотров • 3 лет назад

Redwood AI | Mobility Reinforcement Learning

Redwood AI | Mobility Reinforcement Learning

1X

1,326,424 просмотров • 1 год назад

MatAnyone 2 is out on Hugging Face Scaling Video Matting via a Learned Quality Evaluator paper: app:

MatAnyone 2 is out on Hugging Face Scaling Video Matting via a Learned Quality Evaluator paper: app:

AK

34,927 просмотров • 7 месяцев назад

An interesting example of reinforcement learning.

An interesting example of reinforcement learning.

Historic Vids

1,564,042 просмотров • 3 лет назад

Watch Gemini 2.5 Pro implement a landmark Google DeepMind research paper. 🕹️ It codes the reinforcement learning algorithm, visualizes the training live and even debugs errors. ↓

Watch Gemini 2.5 Pro implement a landmark Google DeepMind research paper. 🕹️ It codes the reinforcement learning algorithm, visualizes the training live and even debugs errors. ↓

Google DeepMind

369,902 просмотров • 1 год назад

An Interesting example of Reinforcement learning!! 🐓

An Interesting example of Reinforcement learning!! 🐓

OpenMoon

7,059,191 просмотров • 2 лет назад

This is a single uncut video, showing a robot learning several tasks instantly, after just one demonstration each ... This is possible because we've now been able to achieve in-context learning for everyday robotics tasks, and I'm very excited to announce our latest paper: 🎆 Instant Policy: In-Context Imitation Learning via Graph Diffusion 🎆 (1/6) 🧵👇

This is a single uncut video, showing a robot learning several tasks instantly, after just one demonstration each ... This is possible because we've now been able to achieve in-context learning for everyday robotics tasks, and I'm very excited to announce our latest paper: 🎆 Instant Policy: In-Context Imitation Learning via Graph Diffusion 🎆 (1/6) 🧵👇

Edward Johns

74,683 просмотров • 1 год назад

Getting Cyn ready for reinforcement learning >:3

Getting Cyn ready for reinforcement learning >:3

DT

14,557 просмотров • 1 год назад

NeurIPS 2025 Paper: LLMs are Reinforcement Learners 🤯! Surprisingly, we show that LLMs can solve RL tasks without any external component! We introduce Prompted Policy Search (ProPS), an RL method based only LLMs and in-context learning. [Paper]

NeurIPS 2025 Paper: LLMs are Reinforcement Learners 🤯! Surprisingly, we show that LLMs can solve RL tasks without any external component! We introduce Prompted Policy Search (ProPS), an RL method based only LLMs and in-context learning. [Paper]

Heni Ben Amor

51,248 просмотров • 11 месяцев назад

Introducing Adapt-1 Machina: Learning Continuous Control Sequences With Adapt-1 Machina, we explore how continuous sequences of machine controls can be learned through reinforcement learning, starting with coarse outcome feedback and without demonstrations or a critic.

Introducing Adapt-1 Machina: Learning Continuous Control Sequences With Adapt-1 Machina, we explore how continuous sequences of machine controls can be learned through reinforcement learning, starting with coarse outcome feedback and without demonstrations or a critic.

Rei

42,587 просмотров • 1 месяц назад

Baby steps towards physically based animation with reinforcement learning...

Baby steps towards physically based animation with reinforcement learning...

Dennis Gustafsson

33,418 просмотров • 1 год назад