At the this week, Intel is presenting a body of research on the computing transformation being driven by data that is increasingly distributed across the edge, the core, and endpoints. Several of the studies Intel will present explore techniques for higher-level intelligence and energy-efficient performance, both at the edge and across network and cloud systems.

Digital binary AI accelerator

In power and resource-constrained edge devices where low-precision outputs are acceptable for some applications, analog binary neural networks (BNNs) are coming into use as an alternative to higher-precision, more computationally demanding and memory-intensive AI algorithms. However, analog BNNs tend to have lower prediction accuracy, as they’re less tolerant of variability and noise.

An Intel-authored paper describes a potential solution in a digital BNN chip, a 10-nanometer

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