"If your dad would just wear a space suit, I could monitor him." It's not often that a random joke leads to the creation of a company, but that's exactly what happened with Ejenta, a digital health startup. Maarten Sierhuis, a NASA alum, had made the comment to Rachna Dhamija, a tech veteran and his future cofounder. Both were dealing with aging parents who had health issues. Sierhuis had spent 12 years as a senior research scientist at NASA, where he used sensors and artificial intelligence (AI) to monitor astronauts in space.

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.

LONDON – Guided by cameras and radars, and negotiating traffic and roundabouts, a self-driving Nissan car took to the streets of London on Monday for the Japanese company's first European tests of an autonomous vehicle. Traveling at up to 50 mph (80 kph) and moving from local streets to a major multilane road, the modified Nissan LEAF electric car showcased the kind of technology many hope to be the future of travel. Britain has been wooing developers of autonomous vehicles, hoping to grab a slice of an industry it estimates could be worth £900 billion ($1.1 trillion) worldwide by 2025. It also recently announced changes to allow for a single insurance policy to cover motorists driving conventionally and in autonomous mode, as it tries to get regulations in place to encourage the uptake of driverless cars from 2020. Britain's flexible approach to testing autonomous vehicles helped Nissan pick London for its first European tests, the director of its research center in Silicon Valley told Reuters. "It's not everywhere in Europe that we can go and drive on the road," Maarten Sierhuis said.

LOS ANGELES – Automakers intending to develop driverless cars need to work as much on software design as mechanical engineering, according to the researcher leading Nissan Motor Co.'s automated-vehicle program. Making cars that are "deliberative" in assessing road conditions, rather than just reactive, requires artificial intelligence, said Maarten Sierhuis, director of Nissan's Silicon Valley research center in Sunnyvale, California. Nissan, which aims to sell vehicles that can drive themselves by 2020 or sooner, is developing software to read and filter sensor data much as a human brain does, he said. "What the auto industry has to come to is a shift from thinking about the car as a physical, mechanical system," Sierhuis said in an interview Tuesday at the Automated Vehicles Symposium in San Francisco. "Autonomy, autonomous systems, is about understanding how humans do that, and then replicating it with software."

Engineering autonomy into cars will not necessarily mean engineering out enjoyment. An autonomous vehicle, capable of driving completely by itself, is nascent technology, and as such can be nerve-racking. But when the sci-fi overtones die down, what is left is a deeply tested artificial intelligence system that is much like a human driver – only safer. There are many vehicles on the road that already incorporate some level of autonomy. Nissan's current Safety Shield tech suite incorporates systems such as adaptive cruise control – which can slow down or speed up a vehicle automatically by using sensors to determine to the location of other vehicles around it – and a 360-degree camera-view function.

Nissan is the latest in a now long line of automobile companies to go public with plans -- sketchy as they may be -- for autonomous cars. The Japanese company will begin testing driverless cars in Japan and put them into commercial operation by 2020, according to Carlos Ghosn, who spoke at the Consumer Electronics Show in Las Vegas on Thursday. He is chairman and chief executive of Nissan, chairman and CEO of Renault and chairman of Mitsubushi. The only substantial difference between Nissan's announced plans and those of Ford, FCA, General Motors, Audi, Mercedes-Benz and several other companies is a plan to put "humans in the loop" based on technology developed at NASA. The director of the Nissan Research Center in Silicon Valley, Maarten Sierhuis, said human "mobility managers" will intervene if an autonomous car encounters a situation it can't handle, like having to cross a double yellow line when a lane is blocked.

"I mean, look at this." He points to a photo of road construction at an intersection in Sunnyvale, California, near Nissan's Silicon Valley research center, which Sierhuis runs. A worker holds a "Slow" sign. It's the sort of seemingly unremarkable situation that can trigger convulsions in the brain of an autonomous vehicle. "There is so much cognition that you need here," Sierhuis says.