AAEON introduces two new embedded AI systems, BOXER-8653AI and BOXER-8623AI, powered by NVIDIA's Jetson Orin NX and Jetson Orin Nano, designed for discreet deployment with environmental resilience and connectivity options like four PoE/PSE LAN ports and USB 3.2 Gen 2 ports.
- Compact size and discreet deployment options make it suitable for a variety of indoor and outdoor settings
- Environmental resilience allows for operation in extreme temperatures, making it suitable for harsh environments
- Powerful AI inference performance and impressive GPU architecture make it ideal for applications that require fast analysis of large amounts of data
AAEON, a leading provider of embedded PC solutions, has just launched two new additions to its lineup of embedded AI systems. The BOXER-8653AI and BOXER-8623AI are powered by nVidia’s Jetson Orin NX and Jetson Orin Nano, respectively. These compact systems, measuring just 180 mm x 136 mm x 75 mm, are designed for discreet deployment and can be easily wall-mounted, making them perfect for indoor and outdoor settings like factories and parking lots.
One of the standout features of these systems is their environmental resilience. The BOXER-8653AI can operate in temperatures ranging from -15°C to 60°C, while the BOXER-8623AI can handle temperatures from -15°C to 65°C. Both systems support a 12 V ~ 24 V power input range via a 2-pin terminal block.
The BOXER-8653AI utilizes the powerful NVIDIA Jetson Orin NX module, offering up to 70 TOPS of AI inference performance. This makes it ideal for applications that require fast analysis of large amounts of data. On the other hand, the BOXER-8623AI makes use of the efficient NVIDIA Jetson Orin Nano module, capable of up to 40 TOPS. Both systems feature the impressive 1024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores.
One of the most notable features of these devices is their four PoE/PSE LAN ports. These ports not only allow for easy deployment of peripheral IP cameras but also simplify integration into existing applications without the need for separate electrical wiring. This is particularly useful for retrofitting the systems into existing architectures. Additionally, both systems have a Gigabit Ethernet port and various types of serial communication ports.
In terms of connectivity, both the BOXER-8653AI and BOXER-8623AI offer four USB 3.2 Gen 2 (Type-A) ports and an HDMI port for display output. They also provide expansion options such as support for 5G and Wi-Fi modules via M.2 slots. Storage is SSD-based, with NVMe available through the M.2 2280 M-Key slot, and there is even a SIM card slot for added functionality.
AAEON has a strong track record of providing industrial AI hardware solutions, particularly with the NVIDIA Jetson platform. As an Elite member of the NVIDIA Partner Network, AAEON continues to innovate and deliver embedded AI systems for various industries.
![AAEON’s BOXER-8653AI & BOXER-8623AI: Compact Powerhouses Elevate Vertical Market Possibilities](https://tpucdn.com/img/VmYMOSpJRoxuCXv9.jpg)
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Background Information
About AAEON: AAEON is a global leader in the design and manufacturing of advanced industrial and embedded computing solutions. With a strong focus on innovation and technology, AAEON provides a wide range of rugged and reliable hardware products tailored to meet the diverse needs of industries such as industrial automation, IoT (Internet of Things), edge computing, and AI (Artificial Intelligence).
About nVidia: NVIDIA has firmly established itself as a leader in the realm of client computing, continuously pushing the boundaries of innovation in graphics and AI technologies. With a deep commitment to enhancing user experiences, NVIDIA's client computing business focuses on delivering solutions that power everything from gaming and creative workloads to enterprise applications. for its GeForce graphics cards, the company has redefined high-performance gaming, setting industry standards for realistic visuals, fluid frame rates, and immersive experiences. Complementing its gaming expertise, NVIDIA's Quadro and NVIDIA RTX graphics cards cater to professionals in design, content creation, and scientific fields, enabling real-time ray tracing and AI-driven workflows that elevate productivity and creativity to unprecedented heights. By seamlessly integrating graphics, AI, and software, NVIDIA continues to shape the landscape of client computing, fostering innovation and immersive interactions in a rapidly evolving digital world.
Technology Explained
GPU: GPU stands for Graphics Processing Unit and is a specialized type of processor designed to handle graphics-intensive tasks. It is used in the computer industry to render images, videos, and 3D graphics. GPUs are used in gaming consoles, PCs, and mobile devices to provide a smooth and immersive gaming experience. They are also used in the medical field to create 3D models of organs and tissues, and in the automotive industry to create virtual prototypes of cars. GPUs are also used in the field of artificial intelligence to process large amounts of data and create complex models. GPUs are becoming increasingly important in the computer industry as they are able to process large amounts of data quickly and efficiently.
M.2: M.2, also known as Next Generation Form Factor (NGFF), is a computer expansion card format that is designed to replace the outdated mSATA standard. It is thinner and longer than mSATA, which gives it a much higher data transfer rate. The M.2 format measures 22mm in width and can measure up to 110mm in length. It uses the M-key and B-key connectors to interface with PC host systems, and can connect to both SATA III and PCIe for data transfer. Due to its small size, M.2 is often used for ultra-slim laptops and netbooks, as well as in embedded SSDs for tablets and other mobile devices. It is also becoming increasingly popular in the desktop computer industry, thanks to its compactness and fast transfer speeds. This makes M.2 ideal for gaming PCs, workstations, and other demanding applications that require high levels of data throughput.
NVMe: Non-Volatile Memory Express (NVMe) is a newly developed technology that has been gaining traction in the computer industry. This technology is a standard interface which allows for high-speed storage and retrieval of data from solid state drives (SSDs). NVMe is designed to increase the speed of data transfers in storage systems by enabling a direct connection to PCI Express (PCIe) bus, resulting in significantly faster access times compared to traditional interface protocols such SSDs. NVMe is particularly useful for applications that require lightning-fast access to large amounts of high-value data. NVMe-based SSDs are being widely adopted in the computer industry and are being employed to power data centers, high-end workstations, and gaming machines to support lightning-fast data processing and retrieval, which unlocks possibilities for machine learning, real-time analytics, edge computing, and other cutting-edge applications. NVMe is proving to be an invaluable tool in the field of computing, offering immense
SSD: A Solid State Drive (SSD) is a modern data storage device that employs flash memory technology to store data electronically. Unlike traditional hard disk drives (HDDs), SSDs have no moving parts, resulting in significantly faster read and write speeds. This leads to quicker boot times, faster application loading, and smoother overall system performance. SSDs are known for their durability, shock resistance, and energy efficiency, making them ideal for laptops, ultrabooks, and other portable devices. They come in various form factors, including 2.5-inch, M.2, and PCIe cards, and are favored for their reliability, quiet operation, and reduced heat generation
Tensor Cores: Tensor Cores are a type of specialized hardware designed to accelerate deep learning and AI applications. They are used in the computer industry to speed up the training of deep learning models and to enable faster inference. Tensor Cores are capable of performing matrix operations at a much faster rate than traditional CPUs, allowing for faster training and inference of deep learning models. This technology is used in a variety of applications, including image recognition, natural language processing, and autonomous driving. Tensor Cores are also used in the gaming industry to improve the performance of games and to enable more realistic graphics.
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