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Advanced Micro Devices Inc (AMD) on Tuesday, June 13, unveiled new details about an artificial intelligence (AI) chip that will challenge market leader Nvidia Corp.
California-based AMD said its most advanced graphics processing unit (GPU) for artificial intelligence, the MI300X, will launch in the third quarter, with mass production starting in the fourth quarter.
AMD’s announcement represents the biggest challenge for Nvidia, which currently dominates the AI chip market with over 80% market share. GPUs are chips used by firms like OpenAI to build advanced artificial intelligence programs like ChatGPT. They have parallel processing capabilities and are optimized for processing large amounts of data simultaneously, making them well-suited for tasks that require high-speed and efficient graphics processing.
AMD has announced that its latest MI300X chip and CDNA architecture has been specifically designed to meet the needs of large language models and advanced AI models. With a maximum memory capacity of 192GB, the MI300X allows you to host even larger AI models compared to other chips, such as the Nvidia H100 chip, which supports up to 120GB of memory.
AMD announced the Infinity architecture, which combines eight M1300X accelerators into a single system, mirroring similar systems from Nvidia and Google that combine eight or more GPUs for AI applications.
During a presentation to investors and analysts in San Francisco, AMD CEO Lisa Su emphasized that AI represents “the most significant and strategically important opportunity for the company’s long-term growth.”
“We are thinking that [рынок] AI accelerators for data centers will grow from about $30 billion this year at a compound annual growth rate of over 50% to over $150 billion in 2027.”
If developers and server makers embrace AMD’s “accelerator” AI chips as an alternative to Nvidia’s products, it could open up a significant untapped market for the chip maker. AMD, known for its mainstream computer processors, will benefit from this potential change in demand.
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While AMD hasn’t revealed specific pricing details, the move could potentially lead to price cuts for Nvidia GPUs, including models like the H100, which can start at $30,000 and up. Decreasing GPU prices can help reduce the overall costs associated with running resource-intensive Generative AI applications.