Tsetlin algorithms are less compute heavy than neural networks, and orders of magnitude lower energy usage per inference with acceleration
250X faster inferencing with Tsetlin machine models, and up to 1,000X when accelerated
Our technology uniquely enables edge training, without the need for cloud support
Our architecture enables explainability and ensures accountability for decisions made
Similar to neural networks in that it can perform complex machine learning training, Tsetlin is an alternative approach that offers significant current and future benefits over other AI architectures such as speed, energy efficiency, and explainability.
Tsetlin-based AI is based on propositional logic, rather than biology, making it more efficient, speeding up inferencing and computationally less complex, and therefore less energy-intensive.
