Neuronix AI Labs provides neural network sparsity optimization technology that reduces power consumption and computational requirements by up to 95% for computer-vision applications on cloud and edge devices. This enables cost-effective deployment of AI solutions in systems constrained by size, power, and budget.
Funding
$146.3K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Deploying computer vision applications on edge devices is often limited by the high power consumption and computational demands of neural networks. This restricts the use of AI in systems with size, power, and budget constraints.
Solution
Neuronix AI Labs (now part of Microchip) offers neural network sparsity optimization technology that significantly reduces the power consumption and computational requirements for computer vision applications. This technology enables the deployment of AI solutions on resource-constrained edge devices and in the cloud. By leveraging Neuronix's AI algorithms and models, Microchip's PolarFire FPGAs and SoCs achieve increased neural network performance efficiency and deliver outstanding GOPS/watt performance. The VectorBlox Accelerator Software Development Kit further simplifies the process of programming trained neural networks for smart embedded vision solutions, even without prior FPGA experience.
Target Audience
The primary audience includes system designers and engineers developing computer vision applications for edge devices, particularly those facing size, thermal, or power constraints.
Features
- Neural network sparsity optimization for reduced power consumption and computational load
- Compatibility with industry-standard AI frameworks like TensorFlow, Keras, and Caffe
- VectorBlox Accelerator SDK for simplified neural network programming on FPGAs
- Support for image classification, object detection, and semantic segmentation tasks
- Integration with Microchip's PolarFire FPGAs and SoC FPGAs for efficient edge deployment