We believe everyone should be able to use and profit from AI, so we spent this year building Hal9, which aspires to become "Roblox for AI".

* What is Hal9?

Roblox is many things: A game development environment with a visual editor that makes it easy to get started but unconstrained to advanced users that want to code. Roblox is also a library of assets, and a marketplace for games.

We are taking a similar approach, we are building a visual editor to assemble anything from simple data analysis by importing data and visualizing it with charts, to data forecasting with regressions, to complex workflows to do web-scraping and run deep learning models like LSTMs.

However, visual editors are constrained and at some point they just don't work, so every block is backed by open source code which you can modify to your hearts' contempt using our code editor.

In addition, you can also add new blocks and share them with others in a library of assets. We are currently using GitHub as a library of open source scripts.

Finally, we have aspirations to help contributors profit from their work by sharing profits with them.

* How are we building this?

We are building everything with web technologies, let me explain why.

First, the whole purpose of this is to make AI more accessible. Technologies like Electron allow us to easily deploy to multiple platforms and avoid having users troubleshoot system dependencies. To put it simply, web technologies allow users to get started with no additional setup.

However, we also see the ecosystem of web technologies converging with Data Science and AI. For instance, the tensorflow.js [1] project allows users to run TensorFlow in the client and optionally train models in GPUs in NodeJS. We currently provide NodeJS infrastructure to run server-side code and hopefully GPUs as well soon.

Another great example is webassembly, which can allow us to run Python with PyIodide [2]; same for SQL with sql.js [3], etc. We are also very excited for WebGPU [4], an initiative to bring proper GPU support to web technologies, which should make it so much easier to use proper GPUs locally.

Momentum is growing around Data Science with libraries like tidy.js [5], danfo.js [6], and ml5.js [7]. Currently this ecosystem is a bit fragmented but we believe they will eventually come together.

Finally, web technologies like CSS and D3.js are arguably the best platform for visualizations. We are big fans of the new ObservableHQ Plot [8] library which we are already using in Hal9.

* Call to action

Head to https://hal9.ai and try it out.

You will need your desktop to interact with the embedded app at the top of our site. The app is diabled on mobile but the site should give you a good idea of how it works.

We are looking for feedback, users and contributors.

If you find this useful, you can download Hal9 for Windows, Mac, or use the Web version and our cloud service for $19.99/month.We are planning to use this revenue to become self-sustained and share profits with our community of developers.

As a developer, you can download and use the development versions to contribute to the open source repo of scripts in https://github.com/hal9ai/hal9ai

* Resources

- Site : https://hal9.ai
- Github : https://github.com/hal9ai
- Twitter : https://twitter.com/hal9ai
- Discord : https://discord.gg/dKYgga84
- YouTube: https://www.youtube.com/user/jluraschi

* References

[1] https://www.tensorflow.org/js
[2] https://github.com/pyodide/pyodide
[3] https://github.com/sql-js/sql.js/
[4] https://www.w3.org/TR/2021/WD-webgpu-20210518/
[5] https://pbeshai.github.io/tidy/
[6] https://danfo.jsdata.org/
[7] https://ml5js.org/
[8] https://observablehq.com/@observablehq/plot