Desktop Robots and Coding Ideas in Classrooms

Imagination is the motor of development. We have the option in the Age of AI to recraft the West Indies. We can act to realise a world we can re-imagine with indigenous knowledge and ideas. But ideas do not record reality. Ideas distort or exceed it. Ideas are the products of imaginative effort, because you can’t have them simply by describing the existing world.  We can never think of nothing, since the idea of Nothing is, by definition, unexampled in experience. Ideas anticipate.

Anticipation is the ability to perceive what is not yet there. Highly developed powers of anticipation are likely to precede fertile imaginations. But imagination is more than anticipation. Imagination may be, in part, the consequence of a flourishing faculty of anticipation. When we anticipate, we see the worries behind the next obstacle. In the worlds that we can recraft, robots will be in classrooms, homes, and offices,and they will be Open Source, never black box. It is unthinkable that millions of robots may be controlled by an offshore technological behemoth, where its clients are unable to control them or reprogram them. In the futures we can reimagine, we must have some control over the robots around us.

In classrooms, children can have the opportunity to create digital artefacts. Seymour Papert supported a constructionist approach to learning, where students actively build knowledge through bricolage. This involves using resources to create and solve problems, often through collaboration and iterative design. Unlike traditional problem-solving, which often follows a rigid, step-by-step process, bricolage encourages experimentation, iteration, and learning from mistakes. It fosters teamwork, idea-sharing, and building on each other’s creations, promoting a shared understanding of knowledge. Papert’s constructionist theory emphasizes that learning is most effective when students are involved in making something tangible, whether a physical object or a digital artefact. This type of activity connects children directly with students in classrooms everywhere.

Recently, Hugging Face released two versions of the Reachy Mini Desktop Robot. The Reachy Mini Wireless runs on a Raspberry Pi 5 minicomputer, while the Reachy Mini Lite needs to be connected to a computing source. These open-source robots are available in kits for developers to assemble themselves. The Reachy Minis have two tiny spiral aerials and two screens that look like the eyes of an owl. Once assembled, these robots can be fully programmed in Python.

Python is a superb programming language for students to learn. It allows beginners to create games and animations, while providing a solid foundation for more advanced programming concepts. Python’s syntax is quite easy to read and understand, making it less intimidating for newcomers. Since Python is used across many industries, learning it can open future career opportunities. Python Tutor helps students visualize how their code runs, making it easier to understand the logic.

The new Hugging Face devices come with pre-installed demos, but what is even better is that they are integrated with the Hugging Face Hub. This hub is the company’s open-source machine learning platform, which provides every child with autonomous access to about 1.7 million AI models and 400,000 datasets. Since the two desktop robots are open source, makers and coders everywhere can extend and modify anything they choose.

The target audience for these robots is AI developers. The Reachy Minis allow users to author code, design, imagine, anticipate, and test AI applications. Children can build their features and Apps to share with the open-source community. These robots can foster the development of the connected curriculum, the connected-child, and the connected classroom, unleashing creators to develop countless Apps and features to share within the Hugging Face community.

These mini robots make learning to code fun and accessible by providing an interactive, hands-on platform with built-in AI capabilities. The open-source design, community support, and modularity encourage exploration and creativity, letting children build, program, imagine, anticipate, and share robot behaviours. They can test ideas and misconceptions to spark new ones. As buildable kits, students experience assembling a robot from scratch, demystifying its parts and mechanics.

While Python is the main language for programming Reachy Mini, support for JavaScript and Scratch is coming soon, making it easier for beginners to start with block-based coding and then move to more advanced text-based languages. The robot’s link with Hugging Face’s AI models allows students to experiment with speech and vision, creating collaborativebricolage experiences. Children will be able to program their robots to respond to voice commands or recognize objects.

The open-source hardware and software, along with the vast Hugging Face community, offer endless learning and collaboration opportunities. Children can access pre-made behaviours, download new features, and share their creations, fostering ownership and innovation. Before receiving the physical robot, children can begin coding and testing their ideas in a virtual simulation environment, enabling rapid prototyping and experimentation.