AI accelerators empower edge devices to execute deep learning applications efficiently and effectively at full scale, leveraging an architecture that takes advantage of the fundamental properties of neural networks. These accelerators unlock new opportunities to harness real-time, power- efficient intelligence across various applications and industries, such as industrial automation, smart cities, automotive, security, and retail. AI accelerators like the Hailo-8 series are crucial because they provide a cost-effective way to equip edge devices with substantial computing power, enabling them to run AI tasks with high accuracy, low latency, and minimal power consumption.
Intelligent edge devices are seminal in factory and logistics automation, helping manufacturers streamline processes, save costs, and boost output without compromising on quality and safety. From smart line cameras for defect detection to autonomous robots navigating the factory floor, edge AI processing is pivotal in Industry 4.0 solutions. Tailored AI accelerators, designed for rugged environments and scalability, introduce powerful capabilities into industrial cameras and small form factor industrial PCs. Such accelerators provide low-latency, high-resolution, high-frame rate neural image processing at very high efficiency, and low power consumption.
These solutions can be used for a variety of industrial automation and machine vision tasks, to perform inspection and analysis for applications such as automated optical inspection (AOI), process control, machining, robot guidance, and more.
By utilizing high-resolution cameras and advanced image processing algorithms, AOI systems swiftly and accurately inspect and identify every manufactured component. The low latency, high throughput processing provided by accelerators, like our processors, removes analytics bottlenecks, enabling machines to run at full speed and maximum productivity and uptime without compromising on quality. Our customers are using these processors for multiple tasks including optical character recognition (OCR), sorting, pick & place, quality control, and more.
The processors are also used in autonomous guided vehicles and robots to perform tasks such as object detection and classification, route planning and navigation, obstacle avoidance and clearance, complex pattern recognition, and more, allowing machines to operate at full capacity without posing a risk to workers or manufacturing processes.
Hailo has been working closely with MVTec to develop a plugin that enables quick and easy integration of Hailo’s AI acceleration with MVTec HALCON. We already see several customers developing groundbreaking products based on the powerful deep learning inference capabilities enabled by this plugin.
As AI evolves rapidly and opens new opportunities for productivity enhancement through machine vision applications, we expect more advanced deep learning algorithms to be used for higher accuracy and faster detection.
We are developing AI accelerators that support any complex machine vision application required for manufacturing efficiency, because they already support the latest neural network models as well as vision transformers (ViT) which are the most novel and advanced vision algorithms. Looking into the not-so-distant future, we anticipate the emergence of generative AI at the edge, ushering in a host of novel opportunities, especially around Human-Machine Interfaces (HMI).
Currently, generative AI relies on distant cloud data centers for processing, posing challenges in terms of bandwidth, cost, and privacy. As companies develop diverse applications for generative AI, the cloud might become a bottleneck, especially in scenarios such as driver assistance, video conferencing, and security, where constant data transmission raises privacy concerns.
The solution lies in enabling devices to process generative AI at the edge. Beyond addressing connectivity and privacy challenges, edge AI reduces bandwidth demands and enhances application performance. This localized approach ensures high-performance, low-latency results, especially in applications like security, robotics, and machining, where cloud connections fall short.
