Literal Labs AI Pipeline
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About
Literal Labs provides a comprehensive software pipeline for training, testing, and deploying a novel class of AI models called Logic-Based Networks (LBNs). Unlike traditional neural networks, LBNs are built from the ground up to be high-speed, low-energy, and logically explainable. They offer up to 54x faster inference and 52x more energy efficiency, with an accuracy difference of only "2% compared to larger, resource-hungry AI algorithms. A key advantage is their ability to run on standard microcontrollers, CPUs, and servers, eliminating the need for expensive GPUs, TPUs, or custom hardware. LBNs are compact (average model size under 40kB) and C++-ready, making them ideal for edge deployment on IoT devices and MCUs. The pipeline intelligently tests thousands of configurations to create precisely trained models for specific deployment and performance needs. Literal Labs also offers a Managed Inference Server for CPU-driven, cost-cutting deployments. The platform is set to launch for users to train their own zero-code, logic-based AI models soon.
Platform
Task
Features
• accuracy within "2% of neural networks
• compact model sizes (< 40kb average)
• edge deployment on mcus & iot
• no gpus, tpus, or custom hardware required
• logically explainable ai models
• 52x more energy-efficient ai
• 54x faster ai inference
• train logic-based networks (lbns)
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