Literal Labs develops AI models using the Tsetlin machine approach, offering significant speed and energy efficiency improvements over neural networks. Their models are designed for edge deployment, enabling faster inference and reduced power consumption. The Tsetlin approach is based on propositional logic, resulting in explainable AI. The company boasts benchmarks showing up to 250x faster inference and 52x less energy usage compared to optimized models. Literal Labs' technology is suitable for various applications where low power consumption, speed, and explainability are critical.
• explainable ai
• on chip training
• high throughput
• ultra low power
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