WHAT IS ON-DEVICE EDGE AI?

When decisions must happen instantly, latency is no longer acceptable. On-device edge AI brings intelligence directly to the source, delivering real time response. Together with cloud AI, this hybrid architecture powers faster, scalable intelligence everywhere.
WHEN IS IT NEEDED?
WHEN IS IT NEEDED?
When data is generated and instant response is required, on-device edge AI delivers intelligence at the source. Combined with cloud AI, it accelerates intelligent computing everywhere.
WHY IS IT NEEDED?
WHY IS IT NEEDED?
Complementing cloud-based AI, on-device edge AI strengthens privacy, delivers real time performance with low latency, and lowers the cost of deploying AI across everyday devices.
WHO IS LEADING IT?
WHO IS LEADING IT?
Kneron edge AI is already powering intelligent devices around the world. While others are still building concepts, our technology is leading the shift to on-device AI.

Reconfigurable NPU

As a leader in the field of reconfigurable NPUs.Kneron has innovated in the industry by proposing dynamic memory (DMA) to enhance memory access efficiency and dynamically support different data accuracy requirements of the same neural network.enabling NPU SoC with high performance ASIC without sacrificing programmability of data-intensive algorithms. With its unique and innovative architecture and outstanding performance.the Kneron team received the IEEE CAS 2021 Darlington Best Paper Award. Kneron's 4th generation reconfigurable NPU can support running CNN and Transformer networks simultaneously.and can do both machine vision and semantic analysis with excellent computational power efficiency.providing end-users with higher performance.lower power consumption and lower cost solutions for AI applications in various end devices.
Most AI models are limited to specific applications and frameworks. Kneron's Reconfigurable Artificial Neural Network (RANN) technology adapts in real-time to audio. 2D.or 3D recognition applications while also being compatible with mainstream AI frameworks and convolutional neural network (CNN) models.
Reconfigurable NPU
RANN Technology can:
  • Compute audio and images including 2D/3D visual recognition
  • Support AI frameworks: ONNX/TensorFlow/Keras/ Caffe/PyTorch
  • Support CNN models: ResNet/GoogleNet/ VGG16/LeNet/MobileNet/DenseNet/YOLO/Tiny YOLO/ and more

RANN Technology helps partners:
  • Lower costs by up to 20%
  • Create commercial applications 
  • Customize edge AI to fit unique use cases

TOTAL SYSTEM SOLUTIONS

Kneron can customize integrated total system hardware + software solutions that are ideal for hardware makers and industry partners looking to instantly accelerate on-device edge AI computing affordably.
TOTAL SYSTEM SOLUTIONS
Kneron's expertise in both hardware and software solutions sets us apart in the edge AI industry and consistently saves our partners tim.energy. and money. Kneron's total system solutions are embodied by the KL520 AI SoC because it integrates Kneron's neural network algorithms to maximize power efficiency and performance for segments such as:

  • Smart home 
  • Mobile
  • IoT
  • Security