The seemingly overnight adoption of generative AI systems such as ChatGPT is transforming the tech industry.
A year ago, AI tech suppliers focused mainly on providing systems for training. For good reason: AI training is technically demanding.
But now the focus has shifted onto large language model (LLM) inferencing and generative AI.
Take ChatGPT, the AI chatbot built on a large language model. In just the first week after its launch, ChatGPT gained over a million users. Since then, it has attracted more than 100 million users who now generate some 10 million queries a day. OpenAI, ChatGPT’s developer, says the system has thus far processed approximately 300 billion words from over a million conversations.
It's not all fun and games, either. 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.
In the same survey, nearly 1 in 5 respondents already have generative AI in either pilot or production mode. And 7 in 10 are experimenting with or otherwise exploring the technology.
This virtual explosion has gotten the attention of mainstream tech providers such as AMD. During the company’s recent first-quarter earnings call, CEO Lisa Su said, “We’re very excited about our opportunity in AI. This is our No. 1 strategic priority.”
And AMD is doing a lot more than just talking about AI. For one, the company has consolidated all its disparate AI activities into a single group that will be led by Victor Peng. 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%.
This new AI group will focus mainly on strengthening AMD’s AI software ecosystem. That will include optimized libraries, models and frameworks spanning all of the company’s compute engines.
Hardware for AI
AMD is also offering a wide range of AI hardware products for everything from mobile devices to powerful servers.
For data center customers, AMD’s most exciting hardware product is its Instinct MI300 Accelerator. Designed for both supercomputing HPC and AI workloads, the device is unusual in that it contains both a CPU and GPU. The MI300 is now being sampled with selected large customers, and general shipments are set to begin in this year’s second half.
Several of AMD’s key partners are offering important AI products, too. That includes Supermicro. It now offers Universal GPU systems powered by AMD Instinct MI250 accelerator and optional EPYC CPUs.
These systems include the Supermicro AS 4124GQ-TNMI server. It’s powered by dual AMD EPYC 7003 Series processors and up to four AMD Instinct MI250 accelerators.
Help for AI developers
AMD has also made important moves on the developer front. Also during its Q1 earnings call, AMD announced expanded capabilities for developers to build robust AI solutions leveraging its products.
The moves include new updates to PyTorch 2.0. This open-source framework now offers native support for ROCm software and the latest TensorFlow-ZenDNN plug-in, which enables neural-network inferencing on AMD EPYC CPUs.
ROCm is an open software platform allowing researchers to tap the power of AMD Instinct accelerators to drive scientific discoveries. The latest version, ROCm 5.0, supports major machine learning (ML) frameworks, including TensorFlow and PyTorch. This helps users accelerate AI workloads.
Just the start
Busy as AMD and Supermicro have been with AI products, you should expect even more. As Gartner VP Francis Karamouzis says, “The generative AI frenzy shows no sign of abating.”
That sentiment gained support from AMD’s Su during the company’s Q1 earnings call.
“It’s a multiyear journey,” Su said in response to an analyst’s question about AI. “This is the beginning for what we think is a significant market opportunity for the next 3 to 5 years.”
- Review AMD’s Q1:23 earnings (includes a link to the earnings webcast)