We are happy to announce the public release of Tesseract Core, a free and open source application to define, build, and execute Tesseracts. Plus we're launching the Tesseract dev forum to support the Tesseract ecosystem and build alongside researchers, teams, and labs across the simulation intelligence community.

What are Tesseracts?

At Pasteur Labs, we are continuously faced with the challenge of bridging the gap between research-grade code and production systems.

Tesseracts accelerate this process significantly, allowing users to package complex scientific and machine learning code into components that are readily usable, effortless to deploy in production, and expose a uniform and self-validating API — all without the need to write excessive boilerplate.

In particular, Tesseracts provide native support for endpoints that interface with automatic differentiation frameworks. As a result, users can perform gradient-based, adaptive optimization involving multiple differentiable components in a pipeline, even in settings where components are executed on different machines (for example in the cloud, or on a GPU compute cluster), with only a few lines of code.

Tesseract Core is a command line app and Python SDK that enables scientists and engineers to build these end-to-end differentiable pipelines consisting of wildly different components like physical simulators, geometric operators, differentiable meshers and renderers, scientific data transforms, neural networks, and more.

Just installing these heterogeneous components can be a challenge for researchers who simply want to get things done — let alone integrating them into large-scale, optimization-driven workflows. That's why Tesseract Core is an important step toward making AI-simulator hybrid systems usable in real-world scenarios.

Be part of the Tesseract ecosystem

The release of Tesseract Core marks the beginning of the Tesseract ecosystem. Join our community, and take a peek at our documentation. You'll also find differentiable physics demos and interactive walkthroughs like this:

Rosenbrock

From the JAX-based Rosenbrock function minimization tutorial

There are many more tutorials, case studies, toolkits, and applications we can’t wait to release to the world. In the meantime, head over to GitHub to get started with Tesseracts, and let us know what you think!