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Tesla vehicles and Optimus share core technology: Actuators Power electronics Battery Manufacturing Data communication Audio system Cameras A14/A15 chips Training cluster Neural simulation Real-world AI

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The Humanoid Hub

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19,499 görüntüleme • 8 ay önce •via X (Twitter)

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Tesla is continuously improving the deep learning neural networks that power our real-world AI. Data labeling is vital to our autonomous systems. We're seeking passionate, detail-oriented minds to train the future of physical AI. Join us.
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One of the most interesting parts of our interview with Tesla VP Lars Moravy wasn't just about Optimus, it was why Tesla thinks it can win! Tesla VP Lars said Tesla's biggest advantages are manufacturing at scale, designing high-performance actuators, and using real-world AI trained on millions of hours of data. He also shared why Tesla started with a humanoid design. People naturally trust something that looks familiar, making it easier to introduce robots into everyday life before exploring other designs. It's a reminder that building a great robot isn't just about AI. It's also about engineering, manufacturing, and getting people to accept it. $TSLA Jeff Lutz 🔋
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One of the most interesting parts of our interview with Tesla VP Lars Moravy wasn't just about Optimus, it was why Tesla thinks it can win! Tesla VP Lars said Tesla's biggest advantages are manufacturing at scale, designing high-performance actuators, and using real-world AI trained on millions of hours of data. He also shared why Tesla started with a humanoid design. People naturally trust something that looks familiar, making it easier to introduce robots into everyday life before exploring other designs. It's a reminder that building a great robot isn't just about AI. It's also about engineering, manufacturing, and getting people to accept it. $TSLA Jeff Lutz 🔋

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ELON MUSK: 2026 is going to be great for Tesla. • Massive production expansion across multiple factories and five major new production lines • Cybercab production starting in Texas, scaling through the year, with potential European manufacturing • Tesla Semi ramping up, heavy truck expansion targeting Europe next year • Full Self Driving rollout accelerating, with expected approval in the Netherlands and broader Europe • Goal of achieving real world AI so advanced you could sleep in the car and wake up at your destination • Optimus humanoid robot program advancing toward real world use cases • Optimus positioned to help with daily tasks like childcare, walking the dog, and elderly care • In house battery cell manufacturing scaling at Gigafactory level • Tesla lithium refinery operational in Texas • Tesla nickel cathode refinery running in Austin • Significant battery cell production ramp throughout the year • Potential expansion of Cybercab and Optimus manufacturing into Europe
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DogeDesigner

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🚨NEWS: Uber co-founder says Tesla is the “Google of Physical AI” Travis Kalanick says Tesla dominates across AI, manufacturing, energy and real world systems
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Muskonomy

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ELON: TESLA VEHICLES AND OPTIMUS WILL PLAY A BIG ROLE ON THE MOON AND MARS “Optimus is gonna play a big role. Optimus and Tesla vehicles will play a big role on the Moon and Mars. For a Moon base and a Mars city, Tesla vehicles and Optimus robots are a natural fit for building and operating a Moon base and a Mars city.” Source: Tesla
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ELON: TESLA VEHICLES AND OPTIMUS WILL PLAY A BIG ROLE ON THE MOON AND MARS “Optimus is gonna play a big role. Optimus and Tesla vehicles will play a big role on the Moon and Mars. For a Moon base and a Mars city, Tesla vehicles and Optimus robots are a natural fit for building and operating a Moon base and a Mars city.” Source: Tesla

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The next frontier of AI is physical. 🤖 From simulation to synthetic data, developers are training robots to understand the real world with NVIDIA Cosmos, Isaac simulation frameworks and open-source physics engine, Newton. Watch the video to see how partners like Hon Hai Technology Group (Foxconn), Hexagon, Humanoid, Noble Machines, and Skild AI are building the future. 🎥
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The next frontier of AI is physical. 🤖 From simulation to synthetic data, developers are training robots to understand the real world with NVIDIA Cosmos, Isaac simulation frameworks and open-source physics engine, Newton. Watch the video to see how partners like Hon Hai Technology Group (Foxconn), Hexagon, Humanoid, Noble Machines, and Skild AI are building the future. 🎥

NVIDIA Robotics

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AI for robotics has some monumental challenges, like high dimensionality and reasoning with the physical world. Ashok Elluswamy, AI lead at Tesla, thinks the hardest problem is Evaluation. - Loss isn't a perfect indicator of Policy Neural Network's quality. - Testing in the real world for all the long-tail failure cases is not possible. To solve the evaluation challenge, Tesla has developed a World Simulator Model. It is trained on state and action pairs, so for a given current camera feed and current action, the model generates the next frame in the cameras. Once the world simulation is good enough, it can be hooked up to the policy network for a closed-loop simulation. In this setup, the model generates the next video frames, and based on those, the policy network comes up with the next action, which feeds back into the world simulation; this continuous loop creates a coherent simulation. The world simulation neural network is not just applicable to self-driving but also to humanoids, because Tesla trains it on common data. The examples show Optimus navigating or manipulating inside the world simulation, with all the pixels being generated by the world simulation model. The robotic agents can be tested in an accurately reproduced edge case and in other potential variations of the same edge case.
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AI for robotics has some monumental challenges, like high dimensionality and reasoning with the physical world. Ashok Elluswamy, AI lead at Tesla, thinks the hardest problem is Evaluation. - Loss isn't a perfect indicator of Policy Neural Network's quality. - Testing in the real world for all the long-tail failure cases is not possible. To solve the evaluation challenge, Tesla has developed a World Simulator Model. It is trained on state and action pairs, so for a given current camera feed and current action, the model generates the next frame in the cameras. Once the world simulation is good enough, it can be hooked up to the policy network for a closed-loop simulation. In this setup, the model generates the next video frames, and based on those, the policy network comes up with the next action, which feeds back into the world simulation; this continuous loop creates a coherent simulation. The world simulation neural network is not just applicable to self-driving but also to humanoids, because Tesla trains it on common data. The examples show Optimus navigating or manipulating inside the world simulation, with all the pixels being generated by the world simulation model. The robotic agents can be tested in an accurately reproduced edge case and in other potential variations of the same edge case.

The Humanoid Hub

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AI6 will not be used in Tesla vehicles AI5 will already be more than enough At $5000+ per chip, 2 chips per car, it makes no sense to put AI6 in the cars AI6 will be used in Optimus (only one chip needed) and in AI data centers
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AI6 will not be used in Tesla vehicles AI5 will already be more than enough At $5000+ per chip, 2 chips per car, it makes no sense to put AI6 in the cars AI6 will be used in Optimus (only one chip needed) and in AI data centers

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Tesla has posted a new video on their career website, featuring Cybercab testing, Optimus building, crash testing, cell manufacturing, and more. They also now have specific job sections for Robotaxi, Optimus, FSD (Supervised), vehicles, Megapack, and more,

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The secrets of AI uncovered! Bilingual junior reporters from the Xiamen Daily International Communication Center visit Tesla to explore the world of intelligent manufacturing.
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🚨INSIDE CORTEX: Tesla massive AI supercluster at its HQ in Austin. Cortex is designed to solve real-world AI, powering projects like FSD, Optimus, and beyond.
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🚨INSIDE CORTEX: Tesla massive AI supercluster at its HQ in Austin. Cortex is designed to solve real-world AI, powering projects like FSD, Optimus, and beyond.

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51,401 görüntüleme • 11 ay önce

It’s not going to be easy competing against Tesla’s Optimus. Just like no one’s been able to match Tesla’s FSD, this will be the same story. Only this time, it’s going to be even harder. Bc Tesla has everything integrated from AI training to hardware to real-world data, and Optimus is powered by the same FSD tech that’s already mastering real-world autonomy. No other company is this vertically integrated, it’s just that Tesla makes it look easy.
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It’s not going to be easy competing against Tesla’s Optimus. Just like no one’s been able to match Tesla’s FSD, this will be the same story. Only this time, it’s going to be even harder. Bc Tesla has everything integrated from AI training to hardware to real-world data, and Optimus is powered by the same FSD tech that’s already mastering real-world autonomy. No other company is this vertically integrated, it’s just that Tesla makes it look easy.

Teslaconomics

99,840 görüntüleme • 8 ay önce

As robotics teams scale, collecting real-world data can quickly become slow and expensive. 📉 Lightwheel is changing that with a simulation-first platform built on our technology, helping customers generate a 100:1 simulated-to-real data ratio for training autonomous systems. Together, we’re turning synthetic and real data into more capable, more reliable robots. Read the full success story 🔗
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As robotics teams scale, collecting real-world data can quickly become slow and expensive. 📉 Lightwheel is changing that with a simulation-first platform built on our technology, helping customers generate a 100:1 simulated-to-real data ratio for training autonomous systems. Together, we’re turning synthetic and real data into more capable, more reliable robots. Read the full success story 🔗

NVIDIA Robotics

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ELON: TESLA IS UNIQUELY POSITIONED TO MANUFACTURE A HUMANOID ROBOT “We really have by far the best team of humanoid robotics engineers in the world. We also have all the other ingredients necessary. You need a great battery pack, you need great power electronics, you need a great charging capability, you need great communications, it's going to have Wi-Fi and cellular connectivity. And of course you need real-world AI. And then, the ability to scale that production to huge levels. You have to design for manufacturing. What other companies are missing is they're missing the real-world AI, and they're missing the ability to scale manufacturing to millions of units a year.” Source: Tesla Financial Results Webcast, January 29, 2025
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ELON: TESLA IS UNIQUELY POSITIONED TO MANUFACTURE A HUMANOID ROBOT “We really have by far the best team of humanoid robotics engineers in the world. We also have all the other ingredients necessary. You need a great battery pack, you need great power electronics, you need a great charging capability, you need great communications, it's going to have Wi-Fi and cellular connectivity. And of course you need real-world AI. And then, the ability to scale that production to huge levels. You have to design for manufacturing. What other companies are missing is they're missing the real-world AI, and they're missing the ability to scale manufacturing to millions of units a year.” Source: Tesla Financial Results Webcast, January 29, 2025

Mario Nawfal

1,336,887 görüntüleme • 1 yıl önce

How to use simulation data for real-world robot manipulation? We present sim-and-real co-training, a simple recipe for manipulation. We demonstrate that sim data can significantly enhance real-world performance, even with notable differences between the sim and the real. (1/n)
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How to use simulation data for real-world robot manipulation? We present sim-and-real co-training, a simple recipe for manipulation. We demonstrate that sim data can significantly enhance real-world performance, even with notable differences between the sim and the real. (1/n)

Zhenyu Jiang

44,299 görüntüleme • 1 yıl önce

Train the AI behind real-world robots We’re hiring Data Labelers to annotate images and videos to train Optimus & autonomous systems. You’ll work with real production data & directly impact how these systems learn and operate in the real world Come join!
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Train the AI behind real-world robots We’re hiring Data Labelers to annotate images and videos to train Optimus & autonomous systems. You’ll work with real production data & directly impact how these systems learn and operate in the real world Come join!

Tesla Recruiting

650,030 görüntüleme • 2 ay önce