Other AMD hardware components for AI include its “Genoa” EPYC processors for servers, Alveo accelerators for inference-optimized solutions, and embedded Versal AI Core series. The MI300 is now being sampled with selected large customers, and general shipments are set to begin in this year’s second half. Designed for both supercomputing HPC and AI workloads, the device is unusual in that it contains both a CPU and GPU. That will include optimized libraries, models and frameworks spanning all of the company’s compute engines.ĪMD is also offering a wide range of AI hardware products for everything from mobile devices to powerful servers.įor data center customers, AMD’s most exciting hardware product is its Instinct MI300 Accelerator. This new AI group will focus mainly on strengthening AMD’s AI software ecosystem. He was previously general manager of AMD’s adaptive and embedded products group, which recently reported record first-quarter revenue of $1.6 billion, a year-on-year increase of 163%. For one, the company has consolidated all its disparate AI activities into a single group that will be led by Victor Peng. 1 strategic priority.”Īnd AMD is doing a lot more than just talking about AI. During the company’s recent first-quarter earnings call, CEO Lisa Su said, “We’re very excited about our opportunity in AI. This virtual explosion has gotten the attention of mainstream tech providers such as AMD. And 7 in 10 are experimenting with or otherwise exploring the technology. In the same survey, nearly 1 in 5 respondents already have generative AI in either pilot or production mode. In a new Gartner poll of 2,500 executive leaders, nearly half the respondents said all the publicity around ChatGPT has prompted their organizations to increase their AI spending. OpenAI, ChatGPT’s developer, says the system has thus far processed approximately 300 billion words from over a million conversations. Since then, it has attracted more than 100 million users who now generate some 10 million queries a day. In just the first week after its launch, ChatGPT gained over a million users. Take ChatGPT, the AI chatbot built on a large language model. For good reason: AI training is technically demanding.īut now the focus has shifted onto large language model (LLM) inferencing and generative AI. The seemingly overnight adoption of generative AI systems such as ChatGPT is transforming the tech industry.Ī year ago, AI tech suppliers focused mainly on providing systems for training.
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