Hello! Today, we're announcing the beta launch of Kobra, a visual programming language for machine learning.
A Kobra program using a machine learning model to diagnose breast cancer
What are we doing? Why?
Learning machine learning is hard. We're trying to fix that.
Machine learning is playing an increasingly important role in our society, but very few people understand it. Even to programmers, it's portrayed as this super complicated wizardry that you need to have gone to graduate school to understand. However, we think that machine learning doesn't have to be incredibly complicated, and that it can be taught to anyone, even non-programmers.
Right now, most machine learning tutorials/frameworks use languages like Python (along with many libraries) and assume coding experience, but this discourages people who don't have these prerequisites. ML concepts don't have a fundamental link with text based languages, so we created a system that doesn't pretend they do.
Kobra is a block-based visual programming language (like Scratch) designed to help people learn machine learning. Our editor, Kobra Studio, is tailored to building machine learning applications, featuring built-in data visualization, a dataset manager and editor, and an easy-to-use library of machine learning models. We use a block-based code editor to reduce the barrier of entry as much as we can and to make it possible to focus on what your project is doing, not syntax or complicated constructs like classes.
We've also developed a community site, allowing users to share their projects with the world and fork other peoples' projects. Being able to see other people's projects and experiment with them makes learning ML a lot more exciting, makes the concepts less abstract and gives learners motivation.
We've been doing all development publicly on GitHub because we value open source software, find the development model advantageous, and want to give back (what's the point of keeping the source private?). We're now at the point where we're ready to release Kobra to the world, but we'll keep making it better (we have a lot of features in the works).
To summarize, machine learning is already a cornerstone of modern technology and its role in society will only increase. We're on a mission to remove as many unnecessary barriers of entry from the path to learn it as we can, and Kobra is how we're doing that.
Who are we?
We're a team of high school students (10th-12th grade) from all over the world who work on Kobra in our free time:
- Pranav Teegavarapu: https://github.com/pranavnt, https://www.linkedin.com/in/pranavnt/
- Benjamin Smith: https://github.com/Merlin04, https://www.linkedin.com/in/benjamin-smith-2785bb16b/
- Makuza Mugabo Verite: https://github.com/veritem, https://www.linkedin.com/in/makuza-mugabo-verite-99369a184/
- Eddie Zhou: https://github.com/eddwz, https://www.linkedin.com/in/eddiezh0u/
When we first found Replit Ventures, we thought it would be a perfect fit. We were approaching being ready for launch, but weren't quite there yet, and needed some guidance on how to turn our prototype into an actual product (and the monetary resources certainly would help too). Once we got accepted, we set the following goals for ourselves:
- Make the editor more intuitive and user friendly (including adding documentation)
- Improve the user experience of our product by conducting user interviews
- In general, figure out how to take Kobra from a prototype to a fully-featured product
Replit Ventures was incredibly beneficial for us. It helped shift our focus from building a small personal project to turning into something bigger. Haya's talk about user experience and user studies helped us run our own and gather feedback, allowing us to make changes to improve UX (for example, users didn't notice the run button, so we modified the design to make it stand out more). We've also started thinking about how to develop revenue streams, and we've refined our vision to focus on usefulness as well as education.
Next steps for Kobra
As mentioned earlier, today we are publicly launching Kobra as a beta. Go try it out at https://kobra.dev! Now that we have finished a lot of the core development (and have more time because school is out), we're going to start focusing on shipping additional features in 2-week sprints (inspired by the talk that Sergei gave on shipping fast). We also have some exciting ideas planned that will increase the size of Kobra's audience and help us achieve a better product-market fit, so stay tuned for updates (@kobra_dev on Twitter and @kobra-dev on GitHub)! Finally, feel free to reach out to us at any time if you have any questions about what we're doing or if you want to chat about anything else - just email [email protected].