The computer components market and the video game industry are on the verge of a revolutionary transformation caused by the unprecedented development of artificial intelligence.
The advent of the AI era requires computer hardware manufacturers to deliver unmatched hardware performance while maintaining energy efficiency and reliability.
AI processors: a revolutionary trend of the future
Neural processing units (NPUs) are at the forefront of today’s computer revolution. They are capable of performing more than 40 trillion operations per second, enabling complex AI workloads to be processed locally. Transferring information processing to a local platform provides increased security, reduces dependence on cloud servers, and minimises the risk of data leaks.
One of the leading manufacturers is Intel, which has introduced the Intel Core Ultra (Meteor Lake and Lunar Lake) processor line with a built-in neural processor. The presence of an NPU speeds up AI task processing without putting additional strain on the main chip and graphics processor.
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Apple is integrating the Neural Engine into its Apple Silicon series of processors. It is designed to accelerate the local execution of AI operations and machine learning tasks.
The transition to PCs with neural processors is gaining popularity among premium commercial users and gamers who frequently upgrade for better performance. However, experts predict that computers with artificial intelligence will become the dominant devices in the PC sector by 2030 and completely change the entire ecosystem.
AI graphics cards: a revolution in graphics and visualisation
The rapid onset of the artificial intelligence era is driving innovation in graphics processors. A striking example is NVIDIA’s tensor cores, which are found in all of the brand’s gaming graphics cards, such as the GeForce RTX 4090 GAMING X or RTX 4070 Ti.
NVIDIA Tensor cores are designed specifically to perform resource-intensive matrix multiplications and additions. They have delivered a huge increase in performance, improved visual quality, and offered new opportunities and prospects for a wide range of users.
Thanks to tensor cores, AI-based upscaling technologies in gaming have become possible – DLSS from NVIDIA, FSR from AMD, XeSS from Intel, and others. Artificial intelligence allows low-resolution graphic content to be instantly converted into high-quality images.
The pioneer in this field is NVIDIA DLSS technology – intelligent scaling with high-quality rendering of fine details and noise removal from the image. With its advent, native high-resolution graphics rendering, which requires enormous computing resources, is becoming a thing of the past. NVIDIA DLSS 3.5 technology adds intermediate frame generation, which has significantly increased frame rates without compromising image quality.
Neural Radiance Fields (NeRF) rendering technologies based on artificial intelligence have become an important part of the gaming and graphic design industry. With NeRF, you can create realistic 3D scenes that take lighting into account, including transparent and reflective materials.
The importance of AI upscaling and rendering technologies for gaming cannot be overstated. They have become a truly revolutionary development, delivering high performance and realistic visual effects through neural networks rather than by directly increasing computing power.
AI in the production of computer components
Artificial intelligence technologies have become an integral part of the process of creating processors, printed circuit boards, and other electronic components. Not so long ago, designing electronics was a laborious and time-consuming process, but AI has radically changed this paradigm.
Neural networks are used to research and find the most efficient chip configurations based on specified criteria for performance, power consumption, and cost-effectiveness. AI can model and test equipment designs much faster than engineers, speeding up the design process. It is capable of generating the optimal layout of electronic components, predicting performance bottlenecks, and much more.
AI is already being used by many manufacturers to create chips. For example, NVIDIA uses the ChipNeMo artificial intelligence system in the design process for its graphics processors. The neural system has enabled the corporation’s designers and engineers to optimise various aspects of chip design. ChipNeMo can answer general questions about chip design, analyse error reports, create scripts for design automation tools, perform logical modelling, and more.
