Optimus was a major point of coverage at the 2024 Tesla Shareholder meeting, and we’ll help break down some of the key points for those interested in Tesla’s future humanoid robots.
What Is It?
Optimus is Tesla’s humanoid robot, built entirely in-house, from the batteries to the motors and actuators in the arms, legs, and hands. Tesla has taken a unique design approach to Optimus and intends to have it replace humans in mundane or risky tasks.
It is a bipedal robot, built around the same aspect as the human body. Optimus was originally unveiled in August 2021 and has since seen several major design iterations. And those aren’t the only ones, Optimus is scheduled to undergo at least one more major design revision this year, as well as one more major design revision for its hands – which will feature 22 degrees of freedom.
In comparison, the human hand has 27 degrees of freedom – Tesla is quite close to replicating the complexity of a hand in its custom-designed hands. Musk mentioned that with the 22 degrees of freedom, Optimus is capable of learning and playing music on a piano – an intricate task that many humans find difficult today.
Best of all, they’ve placed the immense learning prowess of FSD behind its brains – each Optimus unit runs similar hardware and software as Tesla cars . It can also navigate autonomously, using the same object recognition and learning that Tesla’s cars use every day. Optimus learns from watching humans do things or can be taught how to do something by a remote operator. Elon Musk also mentioned that it will eventually be able to watch a video and learn how to do a task.
What Can It Do?
Elon Musk has mentioned that Optimus’ primary goal is to replace humans in certain tasks, especially those that could put a human at risk. This could be anything from being a humanoid companion or caretaker, a construction worker, or even working in factories. Of course, it has a focus on high-precision tasks, owing to its intricately designed hands, and is intended to replace human workers doing everyday precision work that robots today cannot do.
The primary goal is to have Optimus robots begin working in factories, and to this end, two have been deployed to one of Tesla’s factories, and are working on the battery cell assembly lines in a prototype and testing deployment. Today, these two units are moving battery cells off the production line and into shipping containers.
2:1 Robot to Human Ratio
There are some ambitious plans for Optimus – Elon Musk envisions that there will be 2 humanoid robots for every human on the planet in the future. This is alongside an eye-watering build rate of 1 billion humanoid robots a year – of which Tesla intends to build at least 100 million per year or more.
With these numbers, Tesla sees the market cap for Optimus as double that of FSD – approximately $20 trillion, with an expected profit of $1 trillion per year at scale. That’s an expected profit of $10,000 per unit, which will be quite the achievement.
When’s It Coming?
Given the fact that Tesla still has design revisions planned, scale production isn’t starting anytime soon. However, Elon Musk did mention that Tesla currently plans to have approximately 1000 to 2000 Optimus units deployed for internal use in Tesla factories by the end of next year. This limited production run will be the start of Tesla’s larger Optimus deployments and will serve to help them refine the FSD stack that runs Optimus, helping teach it the many tasks it could do in a factory.
Costs
The next big question is what it will cost. Musk has mentioned that it will cost less than a car – with an expected cost of $20,000 USD, once large-scale production kicks off. Just like the Cybertruck, that means initial adopters will be faced with fairly high adoption costs for the initial production runs. Economies of scale will eventually lower the cost as more units are produced.
One of Tesla’s significant challenges will be scaling to reduce these costs. Currently, each unit is hand-built in Tesla’s Optimus labs. Eventually, this will have to scaled up to a proper production line, which will require a factory. Optimus also uses 4680 cells, which means some production of the newer 4680 batteries will be required to produce Optimus.
So perhaps, someday soon, there will be an Optimus knocking on your door, delivering itself to help you take care of your home. Definitely a bright future to look forward to.
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In our continued series exploring Tesla’s patents, we’re taking a look at how Tesla automates data labeling for FSD. This is Tesla patent WO2024073033A1, which outlines a system that could revolutionize how Tesla trains FSD.
We’ll be approaching this article the same way as others in the past, by breaking it down into easily digestible portions.
Training a sophisticated AI model like FSD requires a tremendous amount of data. But all of that data needs to be labeled - and traditionally, this process has been done manually. Human reviewers have to go in and categorize and tag hundreds of thousands of data points across millions of hours of video.
This isn’t just laborious and rote work, it's time consuming, expensive, and prone to human error. The perfect job to hand off to AI.
Tesla’s Automated Solution
Tesla’s patent introduces a model-agnostic system for automated data labeling. Just like their previous patent on the Universal Translator, this will function for any AI model - but FSD is really what it is for.
The system works by leveraging the vast amounts of data collected by Tesla’s fleet to create a 3D model of the environment, which is then automatically used to label new data.
Three Step Process
This process has three steps, so we’ll look at each individually.
High-Precision Mapping
The system starts by creating a highly accurate 3D map of the environment. This involves fusing data from multiple Tesla vehicles equipped with cameras, radar, and other sensors. The map includes detailed information about roads, lane markings, buildings, trees, and other static objects.
It's like creating a digital twin of the real world, and this is exactly the simulation data that Tesla uses to rapidly test FSD. The system continuously improves its accuracy as it processes more data and also generates better synthetic data to augment the training dataset.
Multi-Trip Reconstruction
To refine the 3D model and capture dynamic elements of the environment, the system analyzes data from multiple trips through the same area. This allows it to identify moving objects, track their trajectories, and understand how they interact with the static environment. This way, you have a dynamic, living 3D world that also captures the ebb and flow of traffic and pedestrians.
Automated Labelling
Once the 3D model is sufficiently detailed, it becomes the key to automated labeling. When a Tesla vehicle encounters a new scene, the system compares the real-time sensor data with the existing 3D model. This allows it to automatically identify and label objects, lane markings, and other relevant features in the new data.
Benefits
There are three simple benefits to this system, which is what makes it so valuable.
It is far more efficient. Automated data labeling drastically reduces the time and resources required to prepare training data for AI models. This accelerates development cycles and allows Tesla to train its AI on much larger datasets.
It is also scalable. This system can handle massive datasets derived from millions of miles of driving data collected by Tesla's fleet. As the fleet grows and collects more data, the 3D models become even more detailed and accurate, further improving the automated labeling process.
Finally, it is accurate. By eliminating human error and bias, automated labeling improves the accuracy and consistency of the labeled data. This leads to more robust and reliable AI models. Of course, human review is still involved, but that’s only to catch and flag errors.
Applications
While this technology has significant implications for FSD, Tesla can use this automated labeling system to train AI models for various tasks.
Object detection and classification: Accurately identifying and categorizing objects in the environment, such as vehicles, pedestrians, traffic signs, and obstacles.
Kinematic analysis: Understanding the motion and behavior of objects, predicting their trajectories, and anticipating potential hazards.
Shape analysis: Recognizing the shapes and structures of objects, even when partially obscured or viewed from different angles.
Occupancy and surface detection: Creating detailed maps of the environment, identifying occupied and free space, and understanding the properties of different surfaces (e.g., road, sidewalk, grass).
These different applications are all used by Tesla - which uses different AI subnets to analyze all these different things before feeding them into the greater model that is FSD, which means things like pedestrians, lane markings, and traffic controls are all labeled on-vehicle.
In a Nutshell
Tesla's automated data labeling system is a game-changer for AI development. By leveraging the power of its fleet and 3D mapping technology, Tesla has created a self-learning system that continuously improves its ability to understand and navigate the world.
Imagine a world where self-driving cars can label and understand the world around them without human help. This patent describes a system that could make that possible. It uses data collected from many Tesla vehicles to create a 3D model of the environment, which is like a virtual copy of the real world.
This 3D model is then used to label new images and sensor data, eliminating most needs for human intervention. The system can recognize objects, lane markings, and other important features, making it easier to train AI models.
Back in 2021, while Giga Berlin was still undergoing construction, Elon Musk said that he wanted to fill the factory with graffiti artwork. Just months later, Tesla posted a submission link to find local artists for the project.
It remained relatively quiet for about two years until Musk resurfaced with a post congratulating the team on their progress—and revealing that the factory’s concrete would be entirely covered in art. By 2023, that vision was already taking shape. Tesla began by collaborating with local artists, who created much of the artwork seen in the 2023 image above.
The Giga Berlin West Side in 2023
Not a Tesla App
Graffiti at Scale
As expected from Tesla, they didn’t just hire a group of artists to paint and scale the walls. True to their ethos of autonomy, robotics, and innovation, they sought a more futuristic approach. The local crews couldn’t work fast enough or cover enough ground, so Tesla did what it does best—push the boundaries of technology.
Covering an entire factory in art is a massive undertaking, especially when that factory spans 740 acres (1.2 sq mi / 3 km²). With such an immense canvas, Tesla needed a high-tech solution.
More of the awesome digital artwork
@tobilindh on X
Enter a graffiti start-up that had developed a robotic muralist. Tesla partnered with the company, sourcing digital artwork from independent artists while also commissioning pieces from its in-house creative team. Armed with this collection, the robot meticulously printed the artwork directly onto the factory’s concrete, turning Gigafactory Berlin-Brandenburg into a futuristic masterpiece.
The Robot
Not a Tesla App
This ingenious little robot is equipped with a precision printhead and a sophisticated lifting mechanism. It moves using two kevlar cables that allow it to glide up, down, left, and right while a pair of propellers generates downforce to keep it steady against the wall.
The printhead itself is capable of painting approximately 10 million tiny dots per wall, adding up to a staggering 300 million dots just for the west-facing side of Giga Berlin. Each mural features five distinct colors, and the robot carries 12 cans of paint, ensuring it can keep working for extended periods without interruption.
Check out the video below to see the robot action, along with mesmerizing time-lapse footage of the printing process. It’s an exciting glimpse into how Tesla is blending technology and creativity at Giga Berlin—and we can’t wait to see what’s next.
![Tesla’s Giga Berlin Artwork: Where Creativity Meets Autonomy [VIDEO]](https://www.notateslaapp.com/img/containers/article_images/2025/giga_berlin_art_tobias.jpg/074b092609d4477c5cafb71e90dbaf57/giga_berlin_art_tobias.jpg)
![Tesla's Hidden 'Elon Mode' Unveiled: A Sneak Peek into the Future of FSD [Video]](https://www.notateslaapp.com/images/news/2022/fsd-beta-inside_300w.jpg)
![Tesla Shows Off Robotaxi Cleaning Robot [VIDEO]](https://www.notateslaapp.com/img/containers/article_images/2025/tesla_robotic_cleaner.png/08bbe7d309afe2f4bfee710a5df8cf25/tesla_robotic_cleaner.jpg)
