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Neuronix AI Labs

About Neuronix AI Labs


Neuronix AI Labs was at the forefront of developing innovative AI solutions that were both innovative and practical. Neuronix provided neural network sparsity optimization technology that enabled a reduction in power, size and calculations for various tasks, including image classification, object detection and semantic segmentation.

Microchip acquired Neuronix on April 15, 2024 to expand our capabilities for power-efficient, AI-enabled edge solutions deployed on Field-Programmable Gate Arrays (FPGAs). The acquisition of this technology enables us to develop cost-effective, large-scale edge deployments of components designed for use in computer-vision applications on systems that have cost, size and power constraints. Designers will be able to harness powerful parallel processing capabilities using industry-standard AI frameworks without in-depth knowledge of FPGAs.

In the sections below, see how Neuronix’s AI technology is being incorporated into Microchip’s products and learn more about how Microchip enables the use of AI in designs.

AI in FPGAs


Neuronix's AI algorithms and models are being leveraged to create more powerful and efficient PolarFire® FPGAs and System-on-Chip (SoC) FPGAs.

VectorBlox™ Accelerator


The VectorBlox Accelerator Software Development Kit makes it easy to program a trained neural network for Smart Embedded Vision solutions without prior FPGA experience. Neuronix technology combined with our VectorBlox accelerator design flow produces an increase in neural network performance efficiency and delivers outstanding GOPS/watt performance in our low-power PolarFire FPGAs and SoCs. Systems designers will now be able to architect and deploy small-footprint hardware that was previously difficult to build due to size, thermal or power constraints.

Our Intelligent Edge Solutions 


We deliver intelligent edge AI solutions that enable real-time processing directly on MCUs, MPUs and FPGAs. Our platforms support efficient model deployment and optimized inference performance for embedded systems operating in resource-constrained environments.

We combine hardware-optimized architectures with integrated development tools and acceleration technologies such as the VectorBlox™ Accelerator SDK to help developers bring AI-driven features into production-ready applications.

Explore Edge AI Applications


Smart Embedded Vision With Machine Learning

  • Deliver real-time visual intelligence at the edge
  • Detect, track, and analyze objects for industrial inspection, robotics, Augmented Reality and Virtual Reality (AR/VR), and security systems
  • Support high performance while minimizing power consumption and footprint

Smart Predictive Maintenance

  • Optimize operations with predictive insights at the edge
  • Monitor equipment health and anticipate failures
  • Support proactive maintenance scheduling to help reduce downtime, increase safety, and improve operational efficiency

Smart Human-Machine Interfaces

  • Enhance user interactions with AI-powered gesture and touch recognition
  • Deliver responsive, intuitive interfaces for industrial controls, automotive dashboards and consumer devices
  • Enable operation without reliance on cloud connectivity

Machine Learning Workstations, Servers and Appliances

  • Support high-performance Machine Learning (ML) workloads with scalable workstations and servers
  • Support real-time image classification, speech recognition, autonomous systems and video analytics 
  • Optimize latency, throughput and overall system efficiency

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