The company drives creation of embedded AI products by providing accelerators featuring superior power and area efficiency.
LeapMind Incorporated, the industry leading provider of business solutions built around deep learning technology, demonstrates “Efficiera,” an ultra low power AI inference accelerator IP for companies that design ASIC and FPGA circuits, and other related products. “Efficiera” will enable customers to develop cost-effective, low power edge devices and accelerate go-to-market of custom devices featuring AI capabilities.
“Efficiera” functions as a circuit in an FPGA or ASIC device. Its “Extremely low bit Quantization” technology, which minimizes the number of quantized bits to 1–2 bits, does not require cutting-edge semiconductor manufacturing processes or the use of specialized cell libraries to maximize the power and space efficiency associated with convolution operations, which account for a majority of inference processing.
This product enables the inclusion of deep learning capabilities in various edge devices that are technologically limited by power consumption and cost, such as consumer appliances (household electrical goods), industrial machinery (construction equipment), surveillance cameras, and broadcasting equipment as well as miniature machinery and robots with limited heat dissipation capabilities.
LeapMind is simultaneously launching several related products and services: “Efficiera SDK,” a software development tool providing a dedicated learning and development environment for Efficiera, the “Efficiera Deep Learning Model” for efficient training of deep learning models, and “Efficiera Professional Services,” an application-specific semi-custom model building service based on LeapMind’s expertise that enables customers to build extremely low bit quantized deep learning models applicable to their own unique requirements.
Official product website URL: https://leapmind.io/business/ip/
(1) “Hazard Proximity Detection” using object detection. Helps ensure safety when using industrial vehicles such as construction machinery, by detecting surrounding people and obstacles.
(2)”High quality video streaming” using noise reduction. Improves image quality by eliminating image noise when shooting under low-light conditions and by blocking noise caused by image codecs.
(3)”Higher resolution for video footage” using super-resolution. Converts low-resolution video data into resolutions suitable for display devices.