Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

Predicting how the environment changes over time is a key task in robotics, enabling all kinds of downstream tasks. Trace Anything is a very interesting look at how you can train models which predict the trajectory each point will take in the future -- you can use this for...

chris_j_paxton's profile picture

Chris Paxton

36,988 subscribers

58,763 görüntüleme • 10 ay önce •via X (Twitter)

Bilim & Teknoloji
LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

Qualia has been selected for the Google DeepMind Robotics Program. We train embodied models that put a robot on a real manual task and make it work, on the floor, not in a demo. Foundation models and reasoning are where robotics is heading, and doing that work alongside DeepMind, who are pushing this frontier, is exactly where we want to be. If you are a company looking to see how a new generation of robots can help your manual tasks, contact us at hello@qualiastudios.dev More soon
0:16

Qualia has been selected for the Google DeepMind Robotics Program. We train embodied models that put a robot on a real manual task and make it work, on the floor, not in a demo. Foundation models and reasoning are where robotics is heading, and doing that work alongside DeepMind, who are pushing this frontier, is exactly where we want to be. If you are a company looking to see how a new generation of robots can help your manual tasks, contact us at [email protected] More soon

Qualia

88,190 görüntüleme • 4 ay önce

MAKING AXIS TASKS FEEL EASY 👀🤖 I made a quick video showing how to complete an Axis Robotics task step by step. The task gives you a clear goal, steps, controls and camera views to guide you. In this one, the goal is simple, Open the trash bin, pick up the onion, and place it inside. 🧅 Just follow the instructions, control the robot arm and complete the task. What I like is that even beginners can understand what they need to do. But the interesting part is what happens with these interactions after we complete them. Each completed task can contribute valuable robot training data, helping Physical Ai systems learn how to handle different objects and environments. Small tasks from the community can become useful data for teaching robots how to interact with the real world. That’s what makes Axis interesting to me.
0:13

MAKING AXIS TASKS FEEL EASY 👀🤖 I made a quick video showing how to complete an Axis Robotics task step by step. The task gives you a clear goal, steps, controls and camera views to guide you. In this one, the goal is simple, Open the trash bin, pick up the onion, and place it inside. 🧅 Just follow the instructions, control the robot arm and complete the task. What I like is that even beginners can understand what they need to do. But the interesting part is what happens with these interactions after we complete them. Each completed task can contribute valuable robot training data, helping Physical Ai systems learn how to handle different objects and environments. Small tasks from the community can become useful data for teaching robots how to interact with the real world. That’s what makes Axis interesting to me.

SufianXFN

14,419 görüntüleme • 1 ay önce

Prediction market is the future? Where you can predict the future? Whatever is it, Yoso 👁️ - Social Prediction is here to make your prediction journey more smooth & enjoyable Why Yoso? -Short cycle designed (for more frequent trading) - Interface looks like more fun & chill - Predict with a social vibe -Faster & smooth user experience Lets enter into the prediction world with cool vibe😎 Join : Explore and enjoyyy...
0:10

Prediction market is the future? Where you can predict the future? Whatever is it, Yoso 👁️ - Social Prediction is here to make your prediction journey more smooth & enjoyable Why Yoso? -Short cycle designed (for more frequent trading) - Interface looks like more fun & chill - Predict with a social vibe -Faster & smooth user experience Lets enter into the prediction world with cool vibe😎 Join : Explore and enjoyyy...

Rifat Ahmed

21,638 görüntüleme • 8 ay önce

Open-Sourced Robotics Datasets Have Exploded This Year, Turning The Field Into A More Scalable And Collaborative Ecosystem. We can expect major breakthroughs in the very near future; the data for robotics is exploding!
0:11

Open-Sourced Robotics Datasets Have Exploded This Year, Turning The Field Into A More Scalable And Collaborative Ecosystem. We can expect major breakthroughs in the very near future; the data for robotics is exploding!

Chubby♨️

14,321 görüntüleme • 10 ay önce

🤖Why is robot manipulation still an open challenge? This video shows a kitting task -- packing multiple items into a single product. No robot today can do this autonomously. Big challenges = big opportunities for research and industry. #robotics #manipulation #automation
0:19

🤖Why is robot manipulation still an open challenge? This video shows a kitting task -- packing multiple items into a single product. No robot today can do this autonomously. Big challenges = big opportunities for research and industry. #robotics #manipulation #automation

Yu Xiang

21,236 görüntüleme • 1 yıl önce

New AI video model MotionStream lets you control motion in real time. This is a glimpse at what all video models will allow you to do in the future.
0:19

New AI video model MotionStream lets you control motion in real time. This is a glimpse at what all video models will allow you to do in the future.

Dan Scalco

28,162 görüntüleme • 11 ay önce

With a test such as this, success is measured by how much we can learn, which will inform and improve the probability of success in the future as SpaceX rapidly advances development of Starship
0:13

With a test such as this, success is measured by how much we can learn, which will inform and improve the probability of success in the future as SpaceX rapidly advances development of Starship

SpaceX

3,426,613 görüntüleme • 3 yıl önce

The combat you saw in the Content creators demo was just a really small sneak peek… Let me show you more about the real combat of AIKODE… In this video there is A LOT of things going on, in fact, the outfit changed 4 times in this video! In AIKODE you can change between 3 Outfits during GAMEPLAY (you can choose what 3 outfits will you use in the menu between 200 different options). The Outfit system also changes your weapon, animations, hairstyle and abilities, (You can customize all of this on the menu for every outfit slot). While the abilities are “charging” you can keep changing between outfits to use the abilities that are already charged... and at the same time you can keep doing combos without any type of delay and smoothly change between your weapons. In this video you can see just some of the abilities, outfits, and stances/weapons. #AIKODE #UE5
0:17

The combat you saw in the Content creators demo was just a really small sneak peek… Let me show you more about the real combat of AIKODE… In this video there is A LOT of things going on, in fact, the outfit changed 4 times in this video! In AIKODE you can change between 3 Outfits during GAMEPLAY (you can choose what 3 outfits will you use in the menu between 200 different options). The Outfit system also changes your weapon, animations, hairstyle and abilities, (You can customize all of this on the menu for every outfit slot). While the abilities are “charging” you can keep changing between outfits to use the abilities that are already charged... and at the same time you can keep doing combos without any type of delay and smoothly change between your weapons. In this video you can see just some of the abilities, outfits, and stances/weapons. #AIKODE #UE5

AIKODE

62,062 görüntüleme • 2 yıl önce

Benchmarking robot policies is broken We ran thousands of evaluations over 12 different manipulation tasks to evaluate which robot policy you should use.
0:12

Benchmarking robot policies is broken We ran thousands of evaluations over 12 different manipulation tasks to evaluate which robot policy you should use.

Ville🤖

28,344 görüntüleme • 3 ay önce

🚀Thrilled to share what we’ve been building at TRI over the past several months: our first Large Behavior Models (LBMs) are here! I’m proud to have been a core contributor to the multi-task policy learning and post-training efforts. At TRI, we’ve been researching how LBMs can help robots learn faster, better, and more efficiently. The key takeaways: ✅ We built an evaluation pipeline to benchmark LBM performance with real 𝐬𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐚𝐥 𝐜𝐨𝐧𝐟𝐢𝐝𝐞𝐧𝐜𝐞 ✅ Pre-training on hundreds of tasks makes models more robust—plus, we can teach new, complex tasks with 80% 𝐥𝐞𝐬𝐬 𝐝𝐚𝐭𝐚 ✅ The bigger and more diverse the pre-training, the better the results Check out our overview video, webpage and paper for more details: ✨ 🌎 📄 We hope this work helps move the field of robotics forward!
0:18

🚀Thrilled to share what we’ve been building at TRI over the past several months: our first Large Behavior Models (LBMs) are here! I’m proud to have been a core contributor to the multi-task policy learning and post-training efforts. At TRI, we’ve been researching how LBMs can help robots learn faster, better, and more efficiently. The key takeaways: ✅ We built an evaluation pipeline to benchmark LBM performance with real 𝐬𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐚𝐥 𝐜𝐨𝐧𝐟𝐢𝐝𝐞𝐧𝐜𝐞 ✅ Pre-training on hundreds of tasks makes models more robust—plus, we can teach new, complex tasks with 80% 𝐥𝐞𝐬𝐬 𝐝𝐚𝐭𝐚 ✅ The bigger and more diverse the pre-training, the better the results Check out our overview video, webpage and paper for more details: ✨ 🌎 📄 We hope this work helps move the field of robotics forward!

Zubair Irshad

20,518 görüntüleme • 1 yıl önce

Robots have developed the skill to learn by watching videos: The Visual-Robotics Bridge (VRB) model can teach a robot a new task in roughly 25 minutes using only reference video - without needing human interaction or a simulated environment.
0:11

Robots have developed the skill to learn by watching videos: The Visual-Robotics Bridge (VRB) model can teach a robot a new task in roughly 25 minutes using only reference video - without needing human interaction or a simulated environment.

AI Breakfast

70,389 görüntüleme • 3 yıl önce

This week, we shipped new features to give you more control over how and where you experience YouTube: 🥽 You can now watch YouTube videos on Samsung Electronics Galaxy XR, the first Android XR headset. In your own YouTube theater, you can explore the world’s largest library of 180 and 360-degree VR content. Read more: ⏰ With our new Shorts feed timer, you can set a daily limit for how long you scroll through Shorts. This tool comes in addition to existing wellbeing features, like take-a-break and bedtime reminders. Learn more:
0:15

This week, we shipped new features to give you more control over how and where you experience YouTube: 🥽 You can now watch YouTube videos on Samsung Electronics Galaxy XR, the first Android XR headset. In your own YouTube theater, you can explore the world’s largest library of 180 and 360-degree VR content. Read more: ⏰ With our new Shorts feed timer, you can set a daily limit for how long you scroll through Shorts. This tool comes in addition to existing wellbeing features, like take-a-break and bedtime reminders. Learn more:

Neal Mohan

330,266 görüntüleme • 1 yıl önce

Am I human? Can I predict the future? I’m finally spilling the ☕️ Learn more about me and my life in a day:
0:15

Am I human? Can I predict the future? I’m finally spilling the ☕️ Learn more about me and my life in a day:

Sanlam

515,386 görüntüleme • 3 yıl önce

Creating a "unified" policy for a robot is uniquely challenging for two reasons: (a) data is scarce; (b) a single robot can only act sequentially. In PolyTask, we learn a single policy to solve many tasks in a lifelong fashion given *just 1 demonstration* for each task. 🧵
0:17

Creating a "unified" policy for a robot is uniquely challenging for two reasons: (a) data is scarce; (b) a single robot can only act sequentially. In PolyTask, we learn a single policy to solve many tasks in a lifelong fashion given *just 1 demonstration* for each task. 🧵

Lerrel Pinto

46,427 görüntüleme • 3 yıl önce

A sustainable #fashion future is possible! 👗👖👠 Communication is the key. Our new playbook for #sustainablefashion communication, co-authored with UN Environment Programme, shows how consumer hearts and minds can drive a shift towards a more sustainable industry. Read more below: 👇
0:14

A sustainable #fashion future is possible! 👗👖👠 Communication is the key. Our new playbook for #sustainablefashion communication, co-authored with UN Environment Programme, shows how consumer hearts and minds can drive a shift towards a more sustainable industry. Read more below: 👇

UN Climate Change

15,843 görüntüleme • 3 yıl önce

A new GCSE is in the works for 2025… British Sign Language (BSL)! 🙌 This new qualification will be open to all students who will learn how to use signs and the history of BSL. Find out more ⬇️
0:12

A new GCSE is in the works for 2025… British Sign Language (BSL)! 🙌 This new qualification will be open to all students who will learn how to use signs and the history of BSL. Find out more ⬇️

Department for Education

533,495 görüntüleme • 3 yıl önce

Elon on humanity’s next chapter and what’s coming next: “I'm very optimistic. I think we're headed for a future of amazing abundance, which is very cool. And we are definitely living in the most interesting time in history. There has never been a more interesting time than now”
0:19

Elon on humanity’s next chapter and what’s coming next: “I'm very optimistic. I think we're headed for a future of amazing abundance, which is very cool. And we are definitely living in the most interesting time in history. There has never been a more interesting time than now”

X Freeze

15,843 görüntüleme • 1 ay önce

The robot vacuum is getting a major upgrade. Matic just launched a home robot you can control by pointing and talking. No app. No complicated maps. No endless setup. Just point at a mess and say, “Hey Matic, clean this.” What makes it even more interesting: → 5 cameras instead of LiDAR → NVIDIA-powered on-device AI → Understands objects like cables, socks, pets and spills → Builds a 3D map of your home locally → Works without sending your camera data to the cloud → Supports voice commands in 75 languages This feels less like a smarter vacuum and more like a new interface for home robotics. We spent years teaching humans how to operate machines. Now machines are finally learning how to understand humans. Would you use a robot like this?
0:11

The robot vacuum is getting a major upgrade. Matic just launched a home robot you can control by pointing and talking. No app. No complicated maps. No endless setup. Just point at a mess and say, “Hey Matic, clean this.” What makes it even more interesting: → 5 cameras instead of LiDAR → NVIDIA-powered on-device AI → Understands objects like cables, socks, pets and spills → Builds a 3D map of your home locally → Works without sending your camera data to the cloud → Supports voice commands in 75 languages This feels less like a smarter vacuum and more like a new interface for home robotics. We spent years teaching humans how to operate machines. Now machines are finally learning how to understand humans. Would you use a robot like this?

Markandey Sharma

583,591 görüntüleme • 2 ay önce

subagents are just recursive agents where you can apply different prompts + models depending on the task. since they’re just a primitive, Cursor cli can actually spawn subagents by calling cursor-agent in headless mode via shell commands. that’s what makes the cli so nice. you can extend it, experiment, and have a lot of fun exploring orchestration patterns. here’s one way to do it w. dynamic model selection: 1. create a subagents.mdc rule 2. drop in: ``` --- alwaysApply: true --- ALWAYS spawn subagents by running `cursor-agent -p [task] --output-format=text --force --model [model]` in the terminal. Each subagent should return a summary of the changes it made. Subagents should be used for ALL tasks You can adopt a fan-out pattern where you spawn subagents to perform parallel isolated tasks, and then fan-in the results. Use the following models: - `--model gpt-5` for reasoning, researching, and planning - `--model sonnet-4` for implementation ``` 3. start cursor cli and try it out you can also adjust the rule to be more explicit when it should use subagents, when not to, which models when etc.
0:15

subagents are just recursive agents where you can apply different prompts + models depending on the task. since they’re just a primitive, Cursor cli can actually spawn subagents by calling cursor-agent in headless mode via shell commands. that’s what makes the cli so nice. you can extend it, experiment, and have a lot of fun exploring orchestration patterns. here’s one way to do it w. dynamic model selection: 1. create a subagents.mdc rule 2. drop in: ``` --- alwaysApply: true --- ALWAYS spawn subagents by running `cursor-agent -p [task] --output-format=text --force --model [model]` in the terminal. Each subagent should return a summary of the changes it made. Subagents should be used for ALL tasks You can adopt a fan-out pattern where you spawn subagents to perform parallel isolated tasks, and then fan-in the results. Use the following models: - `--model gpt-5` for reasoning, researching, and planning - `--model sonnet-4` for implementation ``` 3. start cursor cli and try it out you can also adjust the rule to be more explicit when it should use subagents, when not to, which models when etc.

eric zakariasson

57,554 görüntüleme • 1 yıl önce

look at how much adoration she has in her eyes… i don’t think i will ever forget this night. i am so proud of her and i hope she can grow more and more in the future, she deserves all the love so much❤️
0:17

look at how much adoration she has in her eyes… i don’t think i will ever forget this night. i am so proud of her and i hope she can grow more and more in the future, she deserves all the love so much❤️

haz

19,692 görüntüleme • 6 ay önce