This is part of a series of virtual visits with NCSA thought leaders on current topics impacting the field of high-performance computing.
NCSA Director Bill Gropp on ‘Different Approaches to AI’
A lot of the news covering artificial intelligence stems from the efforts being made in the commercial sector. Whether it’s well-known chatbots and large language models like ChatGPT or legacy tech companies like Google and Microsoft investing heavily in AI development, the public’s awareness of this field of industry continues to grow.
But what about academic research into AI?
NCSA’s AI strategy
At NCSA, we’ve approached AI on a couple of different levels. The easiest one is building on our long-term leadership in providing computing resources for the nation. It started with Delta where we recognized there was an unmet need for GPU resources quite broadly – not just in AI, but also in high-performance computing. We did see the growing interest in AI, but the design of Delta predated the emergence of these large language models. So at that point, the computing demands of AI were growing, but they had not exploded the way they have since we proposed Delta.
As the demand grew, we realized that there was going to be an increasing need for GPUs at all scales – in scales that are beyond what anything but the very largest systems can provide, but also at more modest levels where a lot of research is done. That led us to propose DeltaAI and to configure that machine more for AI work than for HPC work. We also realized there was an opportunity to look at the application of AI, so we established the Center for AI Innovation, which really looks at the translational use of AI and research in how you use AI in various tasks.
To read the whole article – click HERE.