The proliferation of smart devices like AI-enabled home assistants in recent years provides an ideal target platform for deploying highly compact deep learning models into daily life. These devices are designed to operate at both low power and low computation resources. To function effectively, a home assistant must be easy to use and respond to user requests in real-time. Today, due to the compute and power requirements of complex AI models, most smart devices must send user data and requests to the cloud to carry out AI processing then returning the results to the smart devices.
Andes and Deeplite teamed up to enable human-machine interfaces like home assistants, to operate locally with little to no cloud connectivity required. The scenario is an embedded solution where a home assistant "wakes up" when it detects a person via a small camera. The goal was to optimize a deep learning model running on Andes A25 and D25F that are the first commercial RISC-V cores with DSP SIMD ISA for low-cost edge AI applications. The team started with a MobileNet model trained on a Visual Wake Words (VWW) dataset that was 13MB in size. Using Deeplite's hardware-aware optimization engine automatically found, trained and deployed a new model less than 188KB in size and with only a 1% drop in accuracy.
"We have more and more industry use cases where we see a need for embedded, optimized deep learning models running on our RISC-V cores such as A25 and D25F that have DSP instructions to accelerate deep learning algorithms," said Dr. Charlie Su, CTO and Executive VP of Andes Technology. "Deeplite has provided a solution that can be leveraged both internally within Andes as well as for our customers to bring deep learning on Andes RISC-V CPU cores to resource-limited devices at the edge."
"I am thrilled with the results of this collaboration! Not only has Deeplite delivered a 69x industry-changing deep learning optimization with minimal accuracy impact but we have done so by automating formerly manual techniques for neural architecture design that were time-consuming and error prone," said Nick Romano, CEO of Deeplite, Inc. "What used to take weeks of expensive trial and error is now accomplished automatically in a few hours! Lightweight Intelligence by Deeplite and best of breed hardware from Andes are taking us one step closer to enabling AI in the things we use every day."
By combining industry leading optimization by Deeplite with Andes' state of the art hardware for use cases like voice recognition or person detection to meet microcontroller-level memory and compute requirements, device OEMs and application developers may offer users the benefit of keeping their data on-device, while still providing the real-time and seamless responses necessary for real-world AI everywhere.
To receive our white paper on this collaboration, please contact Davis Sawyer, cofounder and VP, Product at email@example.com.
About Andes Technology
In only 14 years, Andes Technology Corporation is now a world class creator of innovative high-performance/low-power 32/64-bit processor cores and associated development environment to serve the rapidly growing global embedded system applications. Andes is also a founding Platinum member of the RISC-V Foundation and the first mainstream CPU vendor that adopted RISC-V as the base of its fifth-generation architecture, the AndeStar V5. In order to meet the demanding requirements of today's electronic devices, Andes delivers highly configurable and performance-efficient CPU cores with a full-featured integrated development environment and comprehensive software/hardware solutions to help customers innovate their SoC in a shorter time frame. Since 2018, the yearly volume of Andes-Embedded SoCs has surpassed the 1-billion mark. Andes Technology's comprehensive RISC-V CPU families cover from entry-level 32-bit N22, mid-range 32-bit N25F/D25F/A25 and 64-bit NX25F/AX25F, to high-end multicore A(X)25MP.
For more information, please visit https://www.andestech.com
Founded in 2018 and based in Montreal, Deeplite is an AI software company dedicated to enabling deep learning in the devices we use every day. Deeplite researches, designs and develops intelligent optimization software powered by reinforcement learning to make Deep Neural Networks (DNNs) faster, smaller and energy-efficient from cloud to edge computing.
Deeplite has received many industry recognitions including being named a 2019 Canadian Innovation Exchange (CIX) Top20early company and the 2019 Innovation Award Quebec. Deeplite is currently participating in both the MobilityXlab and L-Spark QNX autonomous vehicle accelerator programs. For more information please visit www.deeplite.ai
|Company Name: Deeplite
KY Kaung-Yeu Hsieh, Sr. Marketing Manager, Andes Technology Corporation
Email Contact Davis Sawyer, Cofounder and VP, Product, Deeplite, Inc.