What is an Edge AI PC? How Does it Benefit Edge Computing Deployments?

Introduction

As generative AI, large language models (LLMs), and AI copilots continue to revolutionize industries, the demand for high-performance computing at the edge has never been more critical. This surge in AI capabilities has paved the way for innovative solutions like the Copilot AI PC, enhancing productivity and efficiency across various sectors. At the forefront of this technological evolution is Edge AI, a crucial paradigm shift in harnessing the necessary computing power away from the cloud and closer to data generation for real-time processing and new business insights.

Edge AI PCs are specialized computing devices designed specifically for tasks like inference and training, incorporating powerful processors, GPUs, NPUs, and other accelerators to handle complex data processing and machine learning workloads directly at the source. This localized computing power is essential for applications in industrial automation, security, and surveillance, where the need for high computing power, energy efficiency, and robust security measures are paramount. 

Moreover, the integration of operational technology (OT) with AI at the edge introduces new security challenges. Traditionally isolated in environments like manufacturing plants, OT now requires enhanced security protocols to protect data without compromising data leaks or breaches. As AI continues to intertwine with OT, securing edge deployments becomes a critical aspect of maintaining operational integrity in these environments. 

Edge AI PCs are pivotal in addressing these challenges, ensuring that the computing power required for AI-driven decision-making is delivered reliably and securely, even in the most demanding industrial settings. 

2. Key Components of AI PCs 

The Role of Semiconductors in Edge AI PCs 

Semiconductors are the backbone of Edge AI PCs, driving the high performance and efficiency needed for AI tasks at the edge. Leading semiconductor vendors design specialized hardware for efficient AI on edge devices. They encompass a range of critical components, including CPUs, GPUs, NPUs, AI accelerators, and memory and storage solutions, each playing a unique role in enabling advanced AI capabilities with real-time processing local to the device and not reliant on the resources of the cloud.  

• Intel & AMD (CPU) enhance x86 semiconductors for high-performance processing while maintaining low TDP. 
• NVIDIA (GPU) pioneers AI acceleration for parallel computing with GPUs and ARM architecture 
• Hailo (TPU/NPU) offers low-power, small-form factor TPUs (AI accelerators)

What is the Central Processing Unit (CPU) 

The CPU is the brain of any computing system, and in AI PCs, it serves as the central hub for processing and managing complex tasks.

High-performance processors, such as Intel's 14th Gen Core™ processors, are designed to handle intensive computational workloads. These CPUs offer significant improvements in speed, efficiency, and multitasking capabilities, making them ideal for AI applications that require robust data processing and quick decision-making.

In rugged edge AI applications, choosing between ARM and x86 CPU architectures is a foundational step for everything else. X86 architecture prioritizes raw computational power for versatility while ARM architecture highlights power efficiency and low heat generation, both shaping the future of rugged edge computing. 

What is the Graphics Processing Unit (GPU) 

GPUs are essential for AI tasks due to their ability to perform parallel processing, which is crucial for handling large datasets and complex algorithms. In AI PCs, GPUs such as NVIDIA's RTX series or A100 Tensor Core GPUs accelerate the training and inference of machine learning models, significantly reducing the time required for these processes. These GPUs are especially effective in tasks like image recognition, natural language processing, and complex simulations. 

What is the Neural Processing Unit (NPU) 

An NPU is a new dedicated processor or processing unit on a larger SoC designed specifically for accelerating neural network operations and AI tasks for AI PCs. Unlike general-purpose CPUs and GPUs, NPUs such as Qualcomm's Snapdragon X Elite are optimized for data-driven parallel computing, making them highly efficient at processing massive multimedia data like videos and images and processing data for neural networks. 

Intel’s new Meteor Lake-U processor features the company’s first-ever NPU devoted to AI workloads, driving the AI PC trend along with Intel’s newly announced Copilot AI PC. With the NPU, Intel brings AI processing to the edge, ensuring real-time data processing in a low power consumption small form factor. 

What is the Tensor Processing Unit (TPU) 

TPUs (Tensor Processing Units), such as the Hailo AI Accelerator, play a critical role in enhancing the performance of AI PCs. These specialized processors are designed to handle the demanding computational tasks required for deep learning and AI inference, particularly at the edge. The Hailo AI Accelerator delivers high parallelism and energy efficiency, with capabilities of up to 26 TOPS, making it ideal for real-time decision-making in environments with limited space and power, such as industrial automation and edge devices. 

Memory and Storage

Fast and reliable memory and storage solutions are critical for the performance of AI PCs. High-speed memory, such as DDR5, ensures quick access to data, reducing latency and improving overall system responsiveness. Similarly, advanced storage solutions like NVMe provide rapid read and write speeds, essential for handling large volumes of data generated by AI applications. These components ensure that AI PCs can manage and process data efficiently, supporting the demanding requirements of edge AI deployments. 

3. How Edge AI PCs are Designed for Industrial and Edge Computing Deployments? 

What is Edge Computing? 

Edge computing refers to the practice of processing data closer to the source of data generation rather than relying solely on centralized cloud data centers. This approach reduces latency, increases processing speed, and enhances real-time decision-making capabilities required for AI inference, making it particularly valuable for applications requiring immediate responses, such as industrial automation and autonomous systems. 

Key Catalysts Shaping Edge Computing

Harnessing AI and ML in industrial settings 

The synergy between AI and edge computing is reshaping industries and paving way for new use cases from smart cities to autonomous vehicles. The adoption of AI technologies such as machine learning (ML) and deep learning has facilitated a shift from traditional deterministic and rule-based systems to probabilistic and goal-oriented automation. 

Enhancing Security with hardware-based solutions 

As hardware-based solutions become increasingly connected and digitized, ensuring the cybersecurity of hardware networks is paramount.  Industrial computers are implementing robust cybersecurity measures such as TPM 2.0 to protect against cyber threats such as malware, ransomware, and unauthorized access.   

The emergence of 5G infrastructure 

Hardware-based solutions integrate 5G technology to enable real-time data telematics and reliable communication between IoT devices for streamlined data transfer efficiency. As processing power shifts closer to data generation, industrial 5G-ready edge AI computers bridge new capabilities for machine intelligence and streamlined automation. Three major benefits of industrial 5G are the introduction of turnkey technologies such as eMMB, uRLLC, and mMTC to meet TSN (time-sensitive networking) requirements for lower latency and better machine to machine communication. 

The Rise of IT/OT Convergence

The rise of digital transformation and industry 4.0 technologies are starting to bridge the gap between computing, networking, and data management (IT) with real-time monitoring sensors, and perception systems (OT). It eliminates the mundane, unnecessary, and in some cases, inaccurate workload of transferring data from one system to another. This convergence allows for interoperability of each system to communicate with one another for real-time data analytics and actionable insights. Edge AI computers play a pivotal role in IT/OT convergence as they are the driving factors for low-latency communication between each system by consolidating various input and outputs for data processing, acquisition and telemetry.

What are some Key technologies for enabling edge computing? 

Low-TDP and Power-Efficient Semiconductor Processor Technology

Edge AI PCs utilize low Thermal Design Power (TDP) processors to ensure energy efficiency and minimal heat generation. These processors, such as those found in Intel's 14th Gen Core™ series, provide high performance without excessive power consumption, making them ideal for edge environments where power efficiency is crucial. 

Variety of I/O for IoT Sensor Connectivity

Edge AI PCs are equipped with a wide range of Input/Output (I/O) ports to connect various IoT sensors and devices. This flexibility allows seamless integration with different sensors and actuators, facilitating comprehensive data collection and processing at the edge. 

Ruggedization Features for Ultimate Reliability and Durability

Industrial edge deployments often occur in harsh environments where standard PCs may not survive. Edge AI PCs are designed with ruggedization features, including enhanced enclosures, shock and vibration resistance, and extended temperature range support, ensuring reliable operation in extreme conditions. 

Wireless Connectivity for Data Telemetry

Robust wireless connectivity options, such as Wi-Fi, Bluetooth, and 4G/5G, are essential for edge AI PCs to enable real-time data telemetry. These capabilities ensure continuous data flow and communication between devices, even in remote or mobile deployments. 

Hardware-Based Security and Data Encryption

Ensuring data security is paramount in edge computing deployments. Edge AI PCs incorporate hardware-based security features, including Trusted Platform Modules (TPM) 2.0 and secure boot processes, along with advanced data encryption technologies. These measures protect sensitive data from unauthorized access and cyber threats, maintaining the integrity and confidentiality of the information processed at the edge. 

4. Premio’s Rugged AI PC Solutions 

Premio has a rugged, comprehensive edge AI portfolio, featuring industrial computers, rugged computers, industrial IoT gateways, rugged fanless edge AI computers with discrete GPU, AI Accelerators, and NVIDIA Jetson solutions, combining robust hardware with cutting-edge technology, ensuring optimal performance in harsh and demanding conditions. 

x86 Intel AI Edge PCs

1. x86 CPU + GPU

Premio offers a wide portfolio of industrial GPU computers, from super rugged industrial computers RCO-6000 Series to semi-rugged BCO-6000-RPL, VCO-6000-RPL, and KCO-2000/3000 series. Premio also provides support for various GPUs from an entry-level NVIDA T1000 to high-performance NVIDIA RTX 4000 SFF. 

How Do These GPUs Align with the Needs of Rugged Embedded Systems?

• NVIDIA RTX A2000 

NVIDIA RTX A2000 is designed with a compact form factor and a 70W TDP, which suits environments with space constraints. The RTX A2000 has an 8 TFLOPS single-precision performance and is beneficial for applications such as image recognition and photo editing.

• NVIDIA T1000 

NVIDIA T1000 delivers 2.5 TFLOPS of single-precision performance, is a low-profile GPU with a focus on power efficiency. It only has 50W TDP and is valuable for mainstream embedded applications with limited power resources in rugged environments.

• NVIDIA RTX A4000 

NVIDIA RTX A4000 is a high-end GPU (19.2 TFLOPS) with a balance of performance and power efficiency for rugged applications. With a 140W TDP, it has the features of Ray Tracing and Tensor Cores for advanced graphics and AI processing tasks.

• NVIDIA RTX 4000 SFF 

NVIDIA RTX 4000 SFF is a high-end small form factor GPU (19.2 TFLOPS) purpose-built for space-constraint embedded systems. With a 70W TDP, it has advanced graphics and AI capabilities for applications like surveillance or image analysis.

• NVIDIA RTX 4070 

NVIDIA RTX 4070 is a high-performance GPU with 200W power consumption and 29 TFLOPS of single-precision performance, providing high performance for rugged applications with demanding graphics or computing workloads such as AI and machine learning.

Industrial GPU Computers

2. X86 CPU + TPU 

Premio is part of Hailo’s hardware partner ecosystem that brings advanced deep learning capabilities to a variety of edge computers with domain-specific performance acceleration.  At Premio, we support Hailo-8TM M.2 AI Accelerator. With a M.2 small form factor, Hailo-8 AI Accelerator can deliver up to 26 TOPS of AI performance with a 2.5W low TDP. 

Premio Compatibility with Hailo-8 M.2 AI Accelerators

3. NVIDIA Jetson Solutions

Premio is a part of NVIDIA Partner Network under the Embedded Compute Competency for the Jetson™ Ecosystem. The NVIDIA Jetson platform utilizes ARM-based system-on-module (SOM) design, features a high-performance CPU, powerful GPU for AI capabilities, and memory on the same module, enabling a wide range of applications. Premio’s JCO Series Rugged AI Edge PCs support NVIDIA Jetson Orin modules, providing a wide range of AI Performance in various mission-critical deployments of AI-powered robots for key industries in factory automation, medical imaging and diagnostics, public safety and security, intelligent transportation, and warehouse logistics. 

Premio Edge AI Solution Performance Chart 

5. Real-World Applications 

Security and Surveillance 

Premio's AI PCs significantly enhance security systems through real-time analytics and improved protection. A tier 1 security solution provider utilizes the rugged NVIDIA Jetson Edge AI computers in security applications. Premio’s JCO-3000-ORN-A is designed with an NVIDIA Jetson Orin NX/ Nano module, providing real-time video analytics capabilities that enable proactive threat detection and response. By leveraging balanced I/Os such as USB3 and LAN, security systems can connect high-speed cameras and detect suspicious activities, enhancing overall situational awareness. With the OOB (Out-of-Band) Remote Management module onboard, it enables 24/7 worry-free remote monitoring and management. >> Read the case study 

Industrial Automation

In industrial automation, Premio’s RCO-6000-CML series industrial GPU computers enhance in-line bottle inspection systems with AI edge inference. These rugged AI PCs perform real-time quality control, using advanced processors, robust GPUs, and extensive I/O capabilities to detect defects instantly. Automating inspections reduces manual effort, increases throughput, and ensures higher accuracy. The RCO-6000-CML's fanless design and high-speed connectivity enable reliable performance and efficient data processing in harsh environments, improving operational efficiency and productivity.  

Smart Cities and Transportation

In smart city and transportation applications, Premio’s RCO-6000-CML rugged AI Edge Inference Computers enhance transportation systems with their advanced NVR platform and EDGEBoost I/O & EDGEBoost Nodes features for maximized data storage. These rugged AI Inference PCs enable real-time license plate recognition, streamline middle-mile autonomous delivery trucks, and improve traffic management operation efficiency.  

Disaster Management 

Premio’s RCO-3000-KBL-U series is a rugged IoT gateway that can be deployed in a volatile outdoor environment inside a NEMA enclosure. With high-speed connectivity, the RCO-3000-KBL-U connects UHD cameras to the cloud for fire detection systems, ensuring fast, accurate data processing and transmission. Its rugged design supports operation in harsh environments, improving response times and minimizing potential damage. This solution highlights Premio’s role in advancing disaster management through robust edge computing technology. >> Read case study

Robotics 

Premio’s KCO-3000 Series is a semi-rugged industrial computer with optional GPU support. In this use case, it is equipped with a mATX coffee lake processor motherboard and NVIDIA A4000 GPU, providing a powerful hardware-based solution for a robot fry cook company. This partnership allowed the robotics company to streamline back-of-house operations, enhance food quality, and scale production, all while reducing reliance on manual labor and improving workplace safety. The rugged design and industrial-grade performance of the KCO-3000-CFL enabled the robotic system to handle demanding kitchen environments efficiently. 

6. Built Rugged. Built Ready – Industrial Grade Design for Premio Edge AI PCs

Premio’s robust portfolio of Edge AI PCs is unique for their ruggedness and reliability, scalability and flexibility, and security & safety certifications.  

Rugged Design  

Premio's Edge AI PCs are engineered with industrial-grade design to endure the harshest environments. Constructed from durable materials like aluminum and heavy-duty metal, these systems are built to withstand challenging conditions. Their shock resistance is compliant with IEC60068-2-27:2008 standards, designed to endure up to 50G half-sine shocks over 11 milliseconds, and adheres to the rigorous MIL-STD-810G Method 516.7 Procedure I for shock and package drop tests. For vibration resistance, they meet IEC60068-2-64:2008 standards, handling 5 Grms across a frequency range of 5 to 500 Hz for 0.5 hours per axis, and comply with MIL-STD-810G Method 514.7 Procedure I. 

These ruggedized computing systems also feature a wide temperature range, capable of operating in extremely cold to hot environments. They maintain low power consumption with high-performance x86 processors, such as the 12th/13th Gen Intel Core processors featuring a P/E core hybrid design with a 35W TDP processor, optimized for power efficiency. For edge gateway and IoT applications, the systems utilize Intel’s latest Atom x6425E or Intel N97 processors, with a maximum TDP of 12W for power-efficient multi-core processing. The NVIDIA Jetson Orin ruggedized systems (JCO Series) also showcase flexibility in power consumption, ranging from 7W to 60W depending on the specific module, including Jetson AGX Orin, Jetson Orin NX, and Jetson Orin Nano. 

In addition, thermal management for Premio’s Edge AI PCs is achieved through a fanless cooling design, incorporating copper heat pipes, thermal paste, heatsinks, and extruded aluminum cases with robust mechanical and compliance engineering for reliability. This design ensures efficient heat dissipation and maintains optimal performance without relying on fans, enhancing reliability and durability in harsh environmental challenges. 

Scalability and Flexibility

Premio offers a variety of performance levels and configurations to meet diverse application needs. Premio’s EDGEBoost Nodes and EDGEBoost I/O technologies allow for customization based on specific deployment requirements. This flexibility is crucial for adapting to different industrial and edge computing scenarios or workloads. 

EDGEBoost I/Os provide the latest in transformative technologies, providing maximum flexibility and compatibility with Premio industrial computing solutions. System integrators and OEMS can configure their industrial computer directly for their applications workloads with plug and play ease. 

EDGEBoost Nodes deliver an industrial-grade modular approach for accelerated computing performance at the rugged edge. When paired with Premio’s flagship RCO-6000 Series industrial computer, EDGEBoost Nodes enable powerful GPU real-time processing and high-speed NVMe storage performance purpose-built for resource-intensive machine learning and rugged edge AI workloads. 

Reliability and Safety Certifications  

Premio's commitment to quality is reflected in its adherence to world-class certifications such as CE, FCC, and UL, as well as specialized certifications such as EN50155, E-Mark for in-vehicle deployments. These certifications, combined with rigorous ISO-certified quality assurance processes, ensure that our Edge AI PCs deliver robust and reliable performance for industrial applications and deployments. UL-Listed 

For example, Premio’s portfolio of edge AI pcs are UL Listed under the UL 62368-1 safety standard. This specific standard is aligned with the IEC (International Electrotechnical Commission) standard and is region-specific to North American markets. 

Summary

With the proliferation of Generative AI, the growing demand for GPUs, and the rise of NPUs, the need for edge AI PCs is rapidly expanding. Premio meets this demand with a robust Edge AI product portfolio, offering AI performance ranging from 26 TOPS to 29 TFLOPS. Our solutions include x86 CPU+GPU, x86 CPU+TPU, and ARM-based NVIDIA Jetson systems, catering to a wide spectrum of AI computing needs. Whether for low-scale industrial IoT applications powered by the Hailo-8 or high-performance AI training using GPUs, Premio’s edge AI PCs empower customers to excel in mission-critical deployments like security and surveillance, disaster management, and robotics. 

Premio's expertise in delivering rugged, industrial-grade AI PCs ensures that businesses can leverage these cutting-edge technologies to optimize performance, efficiency, and reliability in even the most challenging environments. Discover how Premio’s rugged Edge AI PCs can help your business stay ahead of the curve. >> Explore our product offerings