Leopard launched a smart camera empowered by Hailo’s AI chip

Hailo’s AI processor has been integrated into a new product launched recently by Leopard; a manufacturer of embedded cameras for smart devices. The product, named EdgeTuring, is an embedded HD camera for image processing and video analytics applications, in which deep learning inference tasks like object detection and classification are performed at the end device rather than at the cloud. The camera is equipped with the Hailo-8 AI acceleration module, the SC2000 signal processor by Socionext, a japanese provider of advanced SoC, and it is also connected by a simple network connection to Amazon AWS cloud services.

The product is designed for a wide range of applications such as robotics and industrial automation, smart security cameras, machine vision applications in the retail sector and more. According to Leopard, the EdgeTuring consumes less power, performs at a higher level, and ensures greater reliability for video analytics and privacy at the edge than alternative solutions.. The camera is currently priced at $ 900.

Faster then Google and Intel

Founded in 2008 and based in California, Leopard develops embedded HD cameras for autonomous driving systems, drones and robotics, AR/VR and scientific and medical equipment. Among its customers are Nvidia, Xilinx, Qualcomm, On-Semi, Boston Robotics and Sony.

Launched just last year, the Hailo-8 enables customers to integrate high performance AI capabilities of 26 Tera Operations Per Second (TOPS) into edge devices. Hailo reported that a comparison between the Hailo-8 average Frames Per Second (FPS) with competitors across multiple standard NN benchmarks shows that Hailo’s AI modules achieve a FPS rate 26x higher than Intel’s Myriad-X modules and 13x higher than Google’s Edge TPU modules. The Hailo-8 M.2 module is already integrated into the next generation of Foxconn’s BOXiedge with no redesign required for the PCB.

Hailo Challenges Google and Intel

AI chipmaker Hailo announced the launch of its M.2 and Mini PCIe high-performance AI acceleration modules for empowering edge devices. Integrating the Hailo-8 processor, the modules can be plugged into a variety of edge devices. The modules provides high performance Deep Learning-based applications to edge devices. Hailo’s AI acceleration modules seamlessly integrate into standard frameworks, such as TensorFlow and ONNX, which are both supported by its Dataflow Compiler.

Hailo announced that a comparison between the Hailo-8 average Frames Per Second (FPS) with competitors across multiple standard NN benchmarks shows that Hailo’s AI modules achieve a FPS rate 26x higher than Intel’s Myriad-X modules and 13x higher than Google’s Edge TPU modules. The Hailo-8 M.2 module (photo above) is already integrated into the next generation of Foxconn’s BOXiedge with no redesign required for the PCB.

“Manufacturers across industries understand how crucial it is to integrate AI capabilities into their edge devices,” said Orr Danon, CEO of Hailo. “Simply put, solutions without AI can no longer compete.” The Hailo-8 AI modules are already being integrated by select customers worldwide. More information on the Hailo-8 M.2 and Mini PCIe AI modules can be found here.

Hailo-8 vs. Intel Myriad-X(1) and Google Edge TPU(2) Performance across common Neural Network benchmarks

Foxconn and Hailo to Launch Edge AI Computer

Foxconn has combined its edge computing solution, BOXiedge, with the Japanese Socionext parallel processor SynQuacer” SC2A11, and the Hailo-8 deep learning processor developed by Tel Aviv based chipmaker Hailo. The new device aimed to provide powerful AI processing solution for video analytics at the edge. The new BOXiedge is capable of processing and analyzing over 20 streaming camera input feeds in real-time, all at the edge, including image classification, detection, pose estimation, and other AI-powered applications.

This is a milestone win for Hailo, a chipmaker startup who was established in 2017 and had completed a $60 million financing round in March 2020, with the participation ABB Technology Ventures (VC arm of ABB) and NEC Corporation. The funding will be used to enter mass production of the company’s Hailo-8 Deep Learning chip during 2020. Today the company employs approximately 80 employees.

The company’s Hailo-8 processor is a dedicated Neural Networks processor aimed to implement inference functions on edge devices in Automotive and Industrial applications. Hailo-8 processor reaches up to 26 Tera Operations Per Second (TOPS) and 3 TOPS per Watt. It is comprised of four main components: an Image Signal Processor to improve the image arriving from the sensor before its transfer for processing by the neural network core, an H.264 encoder that handles the video stream, an ARM-M4 processor to manages the chip, and a unique Neural Network core.

Orr Danon, CEO and Co-Founder of Hailo
Orr Danon, CEO and Co-Founder of Hailo

“Our vision is to pave the way for next generation AI solutions,” said Gene Liu, VP of Semiconductor Subgroup at Foxconn Technology Group. “We recognize the great potential in adopting AI solutions for a multitude of applications, such as tumor detection and robotic navigation. This platform will positively impact rapidly evolving sectors including smart cities, smart medical, smart retail, and industrial IoT.”

Foxconn has already deployed several in-house developed AI solutions on different production lines, leading to a reduction of at least one third of the operating costs for appearance defect inspection projects. “We are thrilled to collaborate with two of the global leaders in AI solutions,” said Orr Danon, CEO and Co-Founder of Hailo. “A new generation of chips means a new generation of capabilities at the edge.”

AI Chipmaker Hailo Raised $60 Million

The Tel Aviv based chipmaker startup Hailo, has successfully completed a a $60 million financing round with the participation of key strategic investors ABB Technology Ventures (VC arm of ABB) and NEC Corporation. The funding will be used to enter mass production of the company’s processor Hailo-8 Deep Learning chip during 2020. Today the company employs approximately 80 employees.

Since its inception in February 2017, Hailo had raised $88 million. Following the last investment round, it begins to recruit 30-40 new employees for its research and development and support department, as well as offshore stuff for new offices in Europe, Japan and the US, to be opened in 2020. The company’s Hailo-8 processor is a dedicated Neural Networks processor aimed to implement inference functions on edge devices in Automotive and Industrial applications.

“We look forward to combining Hailo’s solution with our cutting-edge industrial technology as an important piece of the puzzle to drive the digital transformation of industries,” said Kurt Kaltenegger, Head of ABB Technology Ventures. Hiroto Sugahara, General Manager of Corporate Technology Division, NEC Corporation, said that Hailo’s technology will help NEC,  “to dive  deeper into the intelligent video analytics market. We look forward to incorporating Hailo’s technology into our next generation edge-based products.”

CEO, Orr Danon: A novel architecture to enable fast and power saving implementation of Neural Networks
CEO, Orr Danon: A novel architecture to enable fast and power saving implementation of Neural Networks

The Company’s co-founder and CEO, Orr Danon, told Techtime Hailo-8 chip presents a novel architecture to enable fast and power saving implementation of Neural Networks. “We identified that in during the processing of inference, there are differences in the behavior of the different layers in the neural network. Our solution provides the exact resources needed in each layer.

“In contrast, our competitors, who use solutions such as GPU processors, allocate to each and every layer the same level of resources. Our development software learns the specific problem of each application, characterizes it, and give the chip instructions on how to manage the resources of each layer in an optimal method.”

According to Hailo, its processor reaches up to 26 Tera Operations Per Second (TOPS) and 3 TOPS per Watt. It will meet the strict ISO 26262 ASIL-B as well as the AEC Q 100 Grade 2 standards. Hailo-8 is comprised of four main components: an Image Signal Processor to improves the image arriving from the sensor before its transfer for processing by the neural network core, an H.264 encoder that handles the video stream, an ARM-M4 processor to manages the chip, and the neural network core itself.

This neural network is comprised of a flexible matrix of software-configurable processing, controls, computational resources and memory units. “Hailo’s Deep Learning chip is a real game changer in industries such as automotive, industry 4.0, robotics, smart cities, and more,” said Hailo Chairman Zohar Zisapel, “A new age of AI chips means a new age of computing capabilities at the edge.”