Nvidia, the prominent player in the artificial intelligence (AI) industry, is further emphasizing its capabilities in consumer graphics processing units (GPUs) for “local” AI applications. These GPUs have traditionally been used for gaming purposes; however, Nvidia has enhanced its latest graphics cards, such as the RTX 4060 Super, RTX 4070 Ti Super, and RTX 4080 Super, to cater to AI models without relying on cloud infrastructure.
The demand for Nvidia’s enterprise GPUs, which are priced in the tens of thousands of dollars and are commonly used in systems with multiple GPUs working in tandem, played a significant role in driving Nvidia’s sales and boosting its market value to over $1 trillion.
While gaming remains the primary focus of the new consumer-level graphics chips, Nvidia claims that they are also capable of efficiently handling AI applications. For instance, the RTX 4080 Super is said to generate AI video content 150% faster than its predecessor. Additionally, software enhancements recently developed by Nvidia are expected to improve language model processing speeds by up to five times.
Nvidia foresees the emergence of new AI applications in the coming year and anticipates that the increased processing power offered by its GPUs will serve as a catalyst. Microsoft is expected to release Windows 12, a version of their operating system that can take full advantage of AI chips, further accelerating AI development.
Moreover, Nvidia is actively exploring various AI use cases. In collaboration with Adobe, the company is utilizing its new chip to generate images through Adobe Photoshop’s Firefly generator and enable background removal during video calls. Furthermore, Nvidia is developing tools that allow game developers to incorporate generative AI, such as dialogue generation for nonplayable characters, into their titles.
Nvidia’s recent chip announcements demonstrate their intention to compete with Intel, AMD, and Qualcomm in the local AI space, indicating a shift from their past focus on server GPUs. This move aligns with the industry’s exploration of more efficient ways to deploy AI, with “AI PCs” equipped with specialized components for machine learning emerging as a potential solution.
By expanding their consumer GPUs’ capabilities and promoting local AI models alongside cloud-based solutions, Nvidia aims to provide flexibility for AI developers and users, allowing them to choose the most suitable approach for their specific requirements.
The source of the article is from the blog foodnext.nl