Kneron, Inc., a leading on-device edge artificial intelligence (AI) company based in San Diego, California, announces it has raised additional funding from Foxconn and Winbond.
Kneron will be working closely with the investors on strategic partnerships and new projects and concepts in the AI space. Kneron’s work with Foxconn will focus on serving AI use cases in industry 4.0 as well as the automotive industry, through Foxconn’s MIH open platform for electric vehicles. Winbond and Kneron will work on developing microcontroller unit (MCU)-based AI and memory computing.
Hong Kong businessman Li Ka-Shing’s venture capital firm Horizons Ventures was the lead investor in the previous $40mn round and has invested in earlier rounds. Other investors in the previous round included Alibaba Entrepreneurs Fund, CDIB, Himax Technologies Inc, Qualcomm, Thundersoft, Sequoia Capital and Weltrend brought the total Series A funding to $73mn.
Albert Liu, Kneron’s founder and CEO, said “In a time when so many companies have cut back on R&D we are thankful to our investors who believe in the work we are doing at Kneron. Kneron is a young company and has achieved a lot since it was founded in 2015, we plan on achieving much more this coming year and this would not be possible without the backing of investors such as Foxconn and Winbond. This is an incredibly exciting time for AI and Kneron will play a crucial role in the
development of this technology”.
Kneron provides complete end-to-end integrated hardware and software solutions that enable on-device edge AI inferencing in mobile devices, personal computers, and IoT use cases including smart home devices, surveillance, payments, and smart cars. Their solutions augment cloud-based AI to accelerate AI inferencing on any device. Kneron already includes air conditioning giant GREE and autonomous driving software company Teraki amongst its customers.
Albert Liu, Kneron’s founder and CEO, added “We are excited to continue our journey with our partners and investors. 2020 was a great year for Kneron, we released the KL720 and made executive-level hires including Davis Chen, Qualcomm’s former Taipei head of engineering. Aside from working on projects with our investors we also plan to release more chips in 2021. Edge AI is still a new concept for many and we are passionate about bringing this technology to everyone.”
As the entire on-device Edge AI industry is still emerging, Kneron’s early investment and
commercialization of its technology have positioned it in a leadership position to enable AI adoption in mass-market devices. Kneron product offerings include:
SoC AI chipsets –
1) KL720 AI chip supports 4K images, Full HD (1080p) video, and natural language audio
processing, enabling devices to capture more detail for facial and audio recognition
2) KL520 AI chip accelerates neural network models whether from Kneron or 3rd parties on
mass-market devices enabling 2D/3D visual recognition and audio recognition applications in everyday devices
On-device AI algorithms – Machine learning algorithms, which have among the smallest
memory footprints in the industry according to recent NIST test results, include face
detection, facial recognition, body detection, and gesture recognition
Neural Processing Units (NPU) – Kneron’s NPU provides commercially proven, high-efficiency solutions designed for devices with low power, low thermal profiles and yet complex neural network computational requirements
Reconfigurable on-device edge AI in real-time
Their edge AI solutions are reconfigurable allowing for real-time switching between audio recognition and 2D/3D visual recognition depending on application needs on the device. Furthermore, this reconfigurability is compatible in real-time with major AI frameworks such as Tensor Flow, ONNX, Keras, Caffe, and PyTorch as well as major CNN models such as VGG16, ResNet, GoogleNet, YOLO, Tiny YOLO, LeNet, MobileNet, Densenet, and more.
Edge AI Net
Because of Kneron’s reconfigurable technology, they are uniquely positioned to realize their vision of the Edge AI Net, or AIoT 3.0. In short, the Edge AI Net will democratize AI and create more Wall-Es and EVAs with fewer Skynets. The Edge AI Net will allow Edge AI devices to communicate with each other to create collective actions that can be independent of centralized cloud-based AI services.
Balance of size, power, performance, and cost
Kneron also separates itself in the on-device edge AI space through solutions that balance power usage, memory footprint, and cost while still performing above their model “size” class as evidenced by their results at the NIST Facial Recognition Vendor test of 2019. This balance is critical when storage space, size, and power are limited in many use cases like security cameras, smart doorbells, smart door locks, smartphones, etc. In addition, its solutions are compatible with all major AI platforms and can reconfigure in near real-time to adapt to different application needs.