Build Your Robot's Brain in aPositronic Studio
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Tens of millions of neuron updates per second on ordinary laptops and desktops.
Small and efficient enough to run on microcontrollers and embedded systems.
Built to one day power neuromorphic brains in robots.
It’s small, fast, and efficient enough to run on ordinary laptops, microcontrollers, and eventually inside real robots. This is the foundation for a new kind of intelligence that can live and learn in the physical world.
aPositronic is aimed at becoming a platform for creating and running neuromorphic models across a wide range of hardware and software platforms.
It is written in C for high portability and support of the full range of computing hardware, from microcontrollers to AI datacenters, and everything from microcontrollers with real-time operating systems (or none at all) to sophisticated operating systems such as Linux, BSD, MacOS, and Windows.
The development plan is for aPositronic to become aPositronic Studio, composed of two main parts: a development module for building models, and a runtime module, containing only the support necessary for running models in the development target (product).
By 2036, we may have neuromorphic computing technology that puts tens of billions of artificial neurons into the head of a humanoid robot, running off just 1-3 watts of power. We will need tools that make it possible, and hopefully not too difficult, to implement models for neuromorphic AI systems of that complexity. From its inception, aPositronic is being designed to grow into the needs of the future.
aPositronic is a neuromorphic computing platform for creating neural networks for AI. It is written in efficient C for use on hardware ranging from microcontrollers to the most powerful CPUs.
While it draws inspiration from neuroscience, aPositronic is a practical R&D tool for technology rather than scientific research. It is meant for building real systems - from small embedded devices like drones and robots to larger-scale intelligent applications.
aPositronic uses its own terminology, shifting from biological terms to engineering terms. The goal is not to simulate biological neurons exactly, but to capture their essential computational behavior.
| Neuroscience Term | aPositronic Term |
|---|---|
| neuron | node |
| membrane potential | potential |
| synapse | connection |
| spike | impulse |
The clean, simple design of the aPositronic API is one of its major features. All API functions are limited to using simple hardware data types, specifically integers and 32-bit IEEE floating point numbers, for their arguments and return values. This results in the API acting as a universal bridge to practically every programming language.
On Linux, aPositronic can be built as a shared object (.so) library. Practically every programming language on Linux can make use of .so libraries. Instead of putting everyone in a Python jail, aPositronic opens up neuromorphic programming to everyone, regardless of their preferred language.
Compiled languages, such as C, C++, Zig, Go, Rust, and even Fortran, can use the aPositronic API directly, for maximum execution speed and minimal energy consumption. (And if that weren't enough, even assembly language programs can access the API in the same manner.)
Interpreted and scripting languages, such as Python, Lua, Ruby, Java, Kotlin, etc. can access Linux .so libraries through FFIs (Foreign Function Interfaces) that have been developed to allow those languages to access the thousands of available Linux .so libraries. The Python programming interface included with the aPositronic is one example.
Since aPositronic is entirely contained in the apositronic.so library, it can easily be included into other applications to add neuromorphic computing functionality to them.
Version 0.1.0 is the very first release of aPositronic. The basic functionality is implemented. There are working Python demos and models written in C. You can run them, modify them, or write your own. There is a very simple tutorial and API documentaton for the Python API. However, the API may change, and documentation is at an early stage of development. This release is intended for developers who are early adopters and are comfortable exploring very early releases of software.
You will need to have a C compiler, 'make', Git, and Python installed. Then you can install aPositronic and run the lif.py demo with the following commands:
Then read the README file, and continue to the tutorial and Python API documentation.
Future development is supported by individual donations, grants, and sponsorships.
See the README file or Contact me for directions on making individual donations.
Hardware donations are also welcome.
Contact me for the shipping address.