Charting a path to a more sustainable AI future
IBM Research’s AIU family of prototype chip designs point the way to a future where AI computation is more efficient, less power hungry, and more capable.
IBM Research’s AIU family of prototype chip designs point the way to a future where AI computation is more efficient, less power hungry, and more capable.
The way the world computes is shifting. We’ve long relied on computers for many aspects of our lives and work, but over the last decade, the world has seen an explosion in demand for AI applications.
AI model sizes are growing exponentially, but the hardware to train and run these behemoth models in the cloud (or on edge devices like smartphones and sensors) hasn’t advanced nearly as quickly. AI software generally requires a great deal of power and memory, and the computer chip designs of yesterday are not adequately suited to handle the demands of modern AI systems. Even the most powerful chips of today are primarily designed for handling lots of simple tasks at once, or being extremely effective at one type of task, like rendering graphics. To lower latency and increase chip speeds, the memory and processing units need to be closer than ever before.
It’s why for years now, IBM Research has been exploring what the future of AI devices looks like. In 2019, it founded the AI Hardware Center, a global research hub headquartered in Albany, New York, where IBM works with academia and industry partners across the globe to uncover new ways to make running AI models easier and more energy efficient.
