Trends to watch: How shifts in data structure and volume demand new approaches to AI compute
Demand for AI compute is doubling every three months. Taking full advantage of data means using more of it, leading to larger, increasingly complex models with billions of hyperparameters requiring massive clusters of compute nodes, all while meeting ever-stricter latency and power requirements. Tingwei Huang explains how the way we compute AI has to be completely rethought so it can evolve to meet the promise of global business transformation.
What you'll learn
- Learn how volume and complexity in data shifts algorithmic development
- Discover how current ways of computing are being rethought to keep up with these demands
- Take a look at new AI chips that are designed specifically for the next wave of AI
Tingwei Huang is a lead architect on Intel’s newest AI chips that are tackling this shifting data landscape.
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