Machine Learning at HPC User Forum: Drilling into Specific Use Cases

The 66th HPC User Forum held September 5-7, in Milwaukee, Wisconsin, at the elegant and historic Pfister Hotel, highlighting the 1893 Victorian décor and art of "The Grand Hotel Of The West," contrasted nicely with presentations on the latest trends in modern computing – deep learning, machine learning and AI. Over the course of two days of presentations, a couple common themes became obvious: First, that machine and deep learning are focused currently on specific rather than general use cases and second, that ML and DL need to be part of an integrated workflow to be effective. This was exemplified by Dr. Maarten Sierhuis from Nissan Research Facility Silicon Valley with his presentation "Technologies for Making Self-Driving Vehicles the Norm." The challenge that Nissan and other deep learning practitioners face is that current deep learning algorithms are programmed to learn to do one thing extremely well – the specific use case: image recognition of stop signs for example. Once an algorithm learns to recognize stop signs, the same amount of discrete learning must apply for every other road sign a vehicle may encounter.