月間参加
月額私のコンテンツの定期的な席。購読者はキューに入るか、枠よりも購読者が多い場合はランダム抽選で、ビデオ本体、クレジット、または説明に登場します。
月額
価格はお問い合わせ
次に再生
Chelsea Finn: This is the State of the Art in Robotics 59 分 
$5 vs $500 Guitar Hero Controller! 24 分 
These Earbuds have a World Record 1 分 
The Problem with Geothermal Energy 2 分 
Your Next Budget PC Upgrade is...Custom Watercooling?? 25 分 
How I wasted $52,000 in my Dream Smart Home 20 分 
What Would Linus Save? 1 分 
NVIDIA CEO Jensen Huang's Vision for the Future 64 分 
How many LTT MCM Arches can hold a PC? 1 分 
LMG Show and Tell 32 分 
Every iPhone Camera vs LOW Light 1 分 
How to be less neurotic | The Gray Area 38 分 
Is Gen Z Dumb? 8 分 
POV: You locked in for 3 months 1 分 
How Does Science Really Work? The Myth of the Great Experiment: Crash Course Scientific Thinking #3 11 分 
Neutron stars gave you jewelry. #shorts #science #SciShow 1 分 
The Pi Song 3.0 (Memorize 300 Digits Of π) 5 分 
What they don't tell you about iPhone 1 分 
Does this new data represent you? 🤡 #stats #happiness #science 2 分 
This Underwater Machine Sees Ghost Particles 1 分 
Cameroon’s Deadly Lake Bomb Has Been Defused 14 分 
The drawing took five minutes. The build did not. #engineering # #3dprinting #building #partner 1 分 
Making my Skull BULLETPROOF with Real Life Adamantium!? 25 分 
New POWER ARMOR update COMING SOON! | #ChatGPT_Partner @OpenAI #fallout #engineering 2 分 
We've kept this project secret for months! 19 分 
Tallest Sunflower EVER! 🌻 #PeppaPig #Shorts #Summer #LEGODUPLO 1 分 
Peppa Pig Tales 2026 🫣 Peppa Plays CAMOUFLAGE HIDE AND SEEK! 👀 BRAND NEW Peppa Pig Episodes 31 分 
The Basement: Thomas Campbell | NASA Secrets, Binaural Beats, Simulation Theory 251 分 
Weather CHAOS on the Family Lake Trip! #PeppaPig #Shorts 1 分 
How billionaires buy American elections 45 分 
My bed is basically a JARVIS at night 💤 #eightsleep #sleepingpod #engineering 1 分 
Humanity’s Real Plan to Stop This Asteroid (Feat. Mark Rober) 22 分 
Why NASA Is Sending This Truck To The Moon 24 分 
WILL THIS DRIFT TRIKE WORK ON GRASS?? 19 分 
Magnet Bikes Magnets are so Powerfull 1 分 
72 Hours Lost in the World’s Richest Dictatorship (no hotel, no food, no transportation...) 38 分 
Something Huge Is Coming... 3 分 
50 Hours on Europe's Most Dangerous Island 32 分 
Exploring World's Strangest Border: A Country Inside a Country Inside a Country? Why? 30 分 
I Wrote a NEW Sci-Fi with Project Hail Mary Author Andy Weir 60 分 
Why American Houses Are So Flimsy 15 分 
Something’s Happening to the Ozone Hole 17 分 
Astronauts Are Seeing Weird Things In Space 1 分 
Zero Gravity Is Weirder Than You Think (Bonus Episode) 12 分 
Why isn't Congress doing more to protect America's food safety? 2 分 
How do you reconstruct an old story? 1 分 
What happens when we stop reading? | The Gray Area 52 分 
Why Gravity Is A Lie, explained in Zero G 23 分 
Have I built the most amazing door Ever? 28 分 
Name That Infrastructure (Ep. 1) #shorts 1 分 
Why you should still send in your mail-in ballot 2 分 Chelsea Finn: This is the State of the Art in Robotics
2026 59 分
Robots can already fold laundry, make espresso, clean kitchens, and assemble things. The harder problem is getting them to do those tasks reliably, for long periods of time, without a human babysitting them. At Startup School 2026, Physical Intelligence cofounder Chelsea Finn explains what it takes to build general-purpose robots that work in the real world. She shares how reinforcement learning pushed robot throughput up 2x, how their systems can run autonomously for hours, and why she believes robotics is entering its GPT era: moving from specialized models toward general-purpose systems that can work across tasks, robots, and environments. Transcript: https://www.ycrootaccess.com/p/chelsea-finn-on-the-next-decade-in Apply to Y Combinator: https://www.ycombinator.com/apply Work at a startup: https://www.ycombinator.com/jobs Chapters: 00:00 — The State of Physical Intelligence 01:23 — What It Takes to Make Robots Useful 05:11 — The Reliability Problem 07:43 — Reinforcement Learning for Robotics 09:35 — Learning From Failures 12:43 — Training Robots to Improve Themselves 14:21 — Can a Robot Work for 13 Hours Straight? 17:36 — Why Robots Need Memory 21:22 — Building a General-Purpose Robot 25:02 — From Fine-Tuning to Out-of-the-Box Models 27:35 — Training on All the Data 30:20 — One Model That Beats the Specialists 31:21 — Compositional Generalization 37:49 — The GPT Era of Robotics 39:49 — Q&A
このクリエイターと仕事をする
このビデオのクリエイターが公開したパッケージ。
このクリエイターはまだ料金を設定していません。リクエストを送信してください — 何かが請求される前に価格が合意されます。
保証配置 — 新規ビデオ
一回限り次のビデオに10秒以上の保証出演。価格は挿入が作品のどこに配置されるかによります。
- 最初の1～3分
- ビデオの中盤
- ビデオの終盤
価格はお問い合わせ
- 最初の1～3分
- ビデオの中盤
- ビデオの終盤
保証配置 — ショート
一回限り既存のビデオからカットしたショート動画内に10秒以上の保証出演。
一回限り
価格はお問い合わせ