Artificial intelligence increasingly makes its presence felt in various aspects of our lives. It’s unsurprising that tech companies are eager to integrate AI into their products, aiming to leverage the technology’s buzz. The trend is pervasive, from motherboards that utilize AI to optimize CPU performance to new webcams featuring AI deep-learning tech.
Companies are under pressure to incorporate AI into their offerings, often with minimal real value to consumers. This is particularly evident in marketing the latest generation of CPUs by companies like Intel, AMD, and Qualcomm. These products deliver impressive performance improvements, with higher performance scores, better efficiency, broader connectivity, lower latencies, and substantial power savings.
However, adding AI features often adds little to no value. New CPUs have neural processing units (NPUs) that accelerate low-level AI operations. These NPUs are included in low-powered laptops, yet the AI features they enable are mostly cloud-based services.
AI hype in latest CPUs
This renders the CPU’s AI capabilities relatively insignificant. AI tasks demand parallel processing performance that CPUs simply can’t match, as evidenced by the starkly higher performance of GPUs in AI benchmarks.
For instance, they use UL’s Procyon benchmark suite to test computer vision inference; an Intel Core i9-14900K scores around 50, while an AMD Ryzen 9 7900X scores 56. In stark contrast, a GPU can score 2,123 on the same test. This massive performance disparity illustrates that AI workloads are better suited to GPUs, underscored by Elon Musk’s installation of 100,000 Nvidia H100 GPUs in xAI’s latest AI training system.
Most popular AI tools today require cloud computing to function effectively, including large language models (LLMs) and advanced AI features in software like Adobe Photoshop. Running these tools on local machines is impractical due to their immense processing power and storage requirements. Exceptions exist, such as localized upscaling and super-sampling technologies like Nvidia’s DLSS and Intel’s XeSS, demonstrating effective localized AI applications.
Yet, despite this, we continue to see a surge in AI-powered laptops and chips, much of which amounts to marketing hype rather than substantial innovation.
Rashan is a seasoned technology journalist and visionary leader serving as the Editor-in-Chief of DevX.com, a leading online publication focused on software development, programming languages, and emerging technologies. With his deep expertise in the tech industry and her passion for empowering developers, Rashan has transformed DevX.com into a vibrant hub of knowledge and innovation. Reach out to Rashan at [email protected]
