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Open-source AI leader Hugging Face has released a detailed tutorial that guides developers through the process of building and training their own AI-powered robots, taking a major step towards democratizing low-cost robotics.
The tutorial released today builds on the company's LeRobot platform, which it announced in May, and marks a big step toward bringing artificial intelligence to the real world.
Finally the wait is over!!!
We've published a detailed tutorial on how to build your own robot.
Show them some moves with just your laptop and teach them new skills.
Now let's observe how our robot operates autonomously.
1/?? pic.twitter.com/ReeDvNlrg9
— Remi Cadene (@RemiCadene) August 19, 2024
The effort marks a pivotal moment in the field of robotics, which has traditionally been led by large, well-funded companies and research institutions.
Hugging Face enables developers of all skill levels to experiment with cutting-edge robotics technology by providing a comprehensive guide covering everything from sourcing parts to deploying AI models.
From code to reality: AI revolutionizes DIY robotics
Remi Cadene, principal research scientist at Hugging Face and a key contributor to the project, describes the tutorial as “a way to unlock the power of end-to-end learning, like an LLM for textbooks, but designed for robotics.”
In a series of tweets, Kayden highlighted the possibility that developers could train neural networks to predict motor actions directly from camera images, similar to how large language models (LLMs) process text.
“You will learn how to train a neural network to predict the next motor rotation directly from camera images,” Kaden explained, emphasizing the tutorial's focus on practical, real-world applications of AI in robotics.
2/ Find the tutorial at this link: https://t.co/Hy8DudA9ul
Unleash the power of end-to-end learning — like an LLM for textbooks, but designed for robotics.
Learn how to train a neural network to predict the next motor rotation directly from camera images. pic.twitter.com/T34vWb658I
— Remi Cadene (@RemiCadene) August 19, 2024
At the heart of the tutorial is Koch v1.1, an affordable robotic arm designed by Jess Moss.
The version improves on Alexander Koch's original design, simplifying the assembly process and enhancing functionality. “First, we provide you with a bill of materials to order the robot parts (in dollars, pounds or euros),” Cadenet tweeted, highlighting the global accessibility of the project.
The tutorial includes detailed videos that guide users through each step of the assembly process, allowing even those new to robotics to successfully build their own AI-powered arm. This approach significantly lowers the barrier to entry for robotics development, making it accessible to a wider range of users.
Building the Future: Collaborative AI and the Democratization of Robots
One of the most innovative aspects of this tutorial is its emphasis on data sharing and community collaboration: Hugging Face provides tools for visualizing and sharing datasets, encouraging users to contribute to a growing repository of robot behavior data.
“If we all recorded our datasets and shared them on the hub, anyone could train AI with an unparalleled ability to perceive the world and act accordingly,” Cadene said, pointing to the potential for collaborative innovation that could accelerate progress in AI-driven robotics.
10/ One last thing I forgot to mention…
We are working on developing even more affordable robots.
No 3D printing required.
Cost $150 total (for 2 arms).
It's called Moss v1.
Join us on Discord for more information.
— Remi Cadene (@RemiCadene) August 19, 2024
In a future-proof move, Cadene hinted at an even more accessible robot in development. The new model, called Moss v1, promises to reduce the cost of two arms to just $150 and eliminate the need for 3D printing. This development will further democratize access to robotics technology, making it available to a wider range of users.
The AI Robot Revolution: Impact on Industry and Society
The release of this tutorial comes at an important time for AI and robotics. As industries increasingly turn to automation to solve complex problems, the integration of AI and physical systems represents the next frontier of technological innovation. Training robots to perform tasks autonomously based on visual input could have a profound impact on a variety of sectors, from manufacturing to healthcare.
But the democratization of robotic technology also raises important questions about the future of work, privacy, and the ethical considerations of widespread automation. Hugging Face's open-source approach means these technologies are no longer limited to the realm of large corporations, making them available to a wider range of users, potentially leading to more diverse applications and innovation.
Hugging Face's new tutorial is more than just a technical guide; it's a roadmap to the future of AI and robotics. By lowering the barrier to entry and fostering a supportive community, Hugging Face is making AI-driven robotics more accessible than ever. For developers, entrepreneurs, and tech decision makers, the message is clear: the future of robotics is within reach, and now is the time to start building.
As this technology matures, it has the potential to reshape industries, create new opportunities, and fundamentally change how we interact with machines in our daily lives. The true impact of this effort will become clear in the coming months and years, but one thing is certain: Hugging Face marks a major step toward democratizing the future of robotics and AI.
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