Starting from 2023, the IT sector has shifted its focus towards artificial intelligence (AI). This transition was greatly facilitated by OpenAI and the widespread accessibility of GPT-3, in addition to the extensive utilization of large language models (LLMs) that had previously lacked sufficient performance and accuracy for practical use, particularly in business settings.
The availability of hardware optimized for accelerating AI workloads played a crucial role in driving this shift towards AI in the industry. Solution integrators (SIs)are also exploring how to achieve commercial AI applications that cover more scenarios. Can the cost of AI solutions be reduced? What types of AI solutions might users be willing to pay for? What are some noteworthy AI technology trends? This article will provide you with some insights.
Everyone is buzzing about the “AI PC,” according to Intel: an AI PC is simply a new computer with components that are specifically designed to run powerful AI-accelerated software (more on that in a sec) with great performance and quality. Without these components, AI workloads are very slow or may not run at all.
"AI PC includes a system that comes with a Neural Processing Unit (NPU), the latest CPUs and GPUs, and access to Copilot. It will also need to have the new Copilot key that Microsoft announced earlier this year."
—— Microsoft
"An AI PC is simply a new computer with components that are specifically designed to run powerful AI-accelerated software (more on that in a sec) with great performance and quality. Without these components, AI workloads are very slow or may not run at all."
—— Intel
This requirement means that some laptops, like Asus’ new ROG Zephyrus, have already shipped with Intel’s new Core Ultra chips and aren’t technically AI PCs in the eyes of Microsoft’s strict requirements because they don’t have a Copilot key. But they’re still AI PCs in Intel’s eyes.
The main difference between an AI PC and cloud server AI lies in where the AI processing occurs.
With an AI PC, the processing is done locally on the device itself, while cloud server AI involves sending data to remote servers for processing.
Image: The difference between an Local AI and Cloud service AI
Although the concept of AI is popular today, it all relies on the "cloud," which not only brings issues of network speed and cost but also raises concerns about data security and privacy. In the future, people will not only use public AI but also private AI, and the best platform for deploying private AI is PCs and smartphones.
AI PC provides a powerful, secure, and efficient platform for running AI applications locally, offering advantages in terms of privacy, speed, customization, and cost-effectiveness.
Efficiency: An AI PC, equipped with specialized hardware like CPUs, NPUs (Neural Processing Units), and GPUs, can perform AI-related tasks more efficiently than traditional PCs. This efficiency is crucial for handling complex AI algorithms and applications.
Privacy and Security: By having AI capabilities on a local device like a PC, sensitive data and computations can be kept secure and private, reducing the risks associated with cloud-based AI solutions.
Offline Capabilities: AI PCs can function even without an internet connection, allowing them to operate in environments where connectivity may be limited or unreliable.
Real-time Processing: Local AI processing allows for real-time decision-making without relying on an internet connection, which is essential for applications where latency is a critical factor.
Customization: An AI PC can be customized to meet specific AI requirements, integrating tailored software and hardware components for optimized performance.
Cost Efficiency: While cloud-based AI services involve recurring costs for data storage and processing, an AI PC offers a one-time investment with potential long-term cost savings.
Retail: AI PC is being used to personalize the shopping experience, recommend products, and manage inventory.
Financial Institutuons: Automates tasks, boosts customer services through chatbots, detects fraud, optimizes investment, and predicts market trends.
Disease Diagnosis: AI can be used to analyze patient data and identify patterns that may indicate a disease. This can help doctors diagnose diseases earlier and more accurately.
Beside the application in retail and kiosks, AI PCs can also make people's life fand communication easier. For example, Intel and OmniBridge help break down communication barriers by using AI PCs to enable real-time conversations between people who use American Sign Language and those who speak English.
Intel's OmniBridge AI American Sign Language Translator | Video rights: Intel Business
Almost all tech giants, from NVIDIA, Intel, AMD, to Rockchip, have released plans about AI PC and upgrades in recent months. This created new demand, heated up competition, and is reshaping the landscape among the tech giants.
NVIDIA is expected to consolidate its leading role in the AI market landscape, with Jetson™, the premier platform for autonomous machines and embedded applications. Jetson modules are compact yet high-performance computers, complemented by the NVIDIA JetPack™ SDK for accelerated software development. Giada has released an AI PC (modeled LH85 NV) supporting the Jetson Orin module.
During the CES held in January this year, NVIDIA announced GeForce RTX™ SUPER desktop GPUs for supercharged generative AI performance, new AI laptops from every top manufacturer, and new NVIDIA RTX™-accelerated AI software and tools for both developers and consumers.
Intel released the Core Ultra processors, codenamed Meteor Lake, early in 2024.The Intel Core Ultra processors is the first to integrate a neural processing unit (NPU) for efficient AI acceleration and local inference on PCs. Meteor Lake is built using Intel's 4 nm process and uses its NPU as an AI accelerator. The Intel Core Ultra processor starts a new architecture branding that designates it as Intel's most powerful processor for PCs and servers that add AI boosts. In 2024, Giada will release its new AI PC adopting Intel Core Ultra processors, with a computing power of up to 34 TOPS.
According to Intel, 100 million AI PC powered by Intel will be deliver by the end of 2025. Intel has already collaborated with over 100 ISVs for AI PC platforms and aims to introduce more than 300 AI acceleration applications to the market by the end of 2024.
For AMD then, Vega is their chance to finally break into the machine learning market in a big way. The GPU isn’t just a high-end competitor, but it offers high performance FP16 and INT8 modes that earlier AMD GPU architectures lacked, and those modes are in turn immensely beneficial to machine learning performance.
Rockchip has released processors integrating NPU (Neural Network Processor), providing a one-stop Turnkey solution for AI artificial intelligence. The Giada D77 AI PC has emerged as a game-changer powered by the formidable Rockchip RK3588 chipset. Besides D77, Giada also has D76, powered by RK3568. RK3568 has a built-in independent NPU with 1TOPs computing power. It enables Giada DN76 to be used for lightweight AI applications.
Globally, AI PC sales would grow rapidly, from 13 million units in 2024 to 150 million units 2027, according to researcher Sigmaintell. The first year of AI PC shipments at scale would be 2024, and they were expected to be a mainstream choice by around 2025, With AI PC's influence, the global laptop market would rebound slightly with 3.2 percent growth expected in 2024, according to TrendForce.
In the era of AI PC, as we look towards the future, it becomes evident that the application of AI in intelligent scenarios will rely on edge computing devices at the terminal. Giada will keep on development of smarter edge computers. Welcome to contact us for more information.
Inquiry
Download
Technical Support
RMA
Events