Interconnect. (source: Pixabay)

In this episode of the Data Show, I speak with Naveen Rao, VP and GM of the Artificial Intelligence Products Group at Intel. In an earlier episode, we learned that scaling current deep learning models requires innovations in both software and hardware. Through his startup Nervana (since acquired by Intel), Rao has been at the forefront of building a next generation platform for deep learning and AI.

I wanted to get his thoughts on what the future infrastructure for machine learning would look like. At least for now, we’re seeing a variety of approaches, and many companies are using heterogeneous processors (even specialized ones) and proprietary interconnects for deep learning. Nvidia and Intel Nervana are set to release processors that excel at both training and inference, but as Rao pointed out, at large-scale there are many considerations—including utilization, power consumption, and convenience—that come into play.

Here is a partial list of the items we discussed:

  • Deep learning in comparison to other machine learning algorithms

  • Key features and the current status of Intel Nervana’s Lake Crest technology

  • Deep learning frameworks and related software tools including Nervana Graph.

  • Building next-generation hardware and software components for deep learning

  • An overview of the major AI initiatives within Intel (including the establishment of a new AI Research Lab that Rao is leading)

Related resources: