When it comes to chips, automakers are all-in. That is, the silicon variety and not those with which you can gamble away a fortune, something auto companies are loathe to do. Traditionally, the risks auto manufacturers undertake are carefully calculated and always rooted in the world of profit and market share. As they look to the future, their chips are increasingly riding on ‘green’ and ‘connectivity.’

Key to this is Silicon Valley, which for decades has been synonymous with the high tech world of consumer electronics, encompassing everything from computers and cellphones to software and apps. Today this storied list has expanded in important and unexpected ways to include technology that’s at the heart of the auto industry’s future. It’s here that auto manufacturers have forged strategic alliances with Silicon Valley icons like Google and Apple, plus noted tech companies like NVIDIA and an array of Silicon Valley start-ups that promise to bring new and exciting functionality to our vehicles.

Striking alliances with tech companies is an important direction for an industry that has been entrenched in its own world for well over a century. It’s so important, in fact, that many auto manufacturers have gone beyond just alliances, establishing dedicated research and development centers in Silicon Valley to tap the undeniable expertise here. We have seen surprising moves in recent times, like Toyota’s short-lived alliance with Tesla to develop the excellent, though quite expensive, battery electric RAV4 crossover a few years back. Sometimes things work out, sometimes not. But ventures like this are important to the journey as a future unfolds that will certainly find advanced electronics playing a major role in the cars we drive, or perhaps, to cars that drive themselves.

This is happening already with an increasingly sophisticated array of on-board electronics incorporated into new car models. As you might expect, much of this is showing up in higher-end vehicles first as technology costs are absorbed into the price of aspirational vehicles already expected to command a higher point of entry. As technology costs decrease, advanced systems like these tend to move down-market to more affordable vehicles. We’re already seeing this happening in real time.

In addition to the on-board systems we tend to take for granted today – such as navigation, back-up display, satellite radio, and Bluetooth cellphone integration – there’s a new generation of sought-after features that use a vehicle’s integrated cameras and sensors to perform wondrous tasks. Adaptive cruise control that automatically maintains a safe distance from the car ahead is one of these.

Beyond that is the latest generation of such systems with a stop-and-go function capable of automating the boring task of driving in urban gridlock. Lane minder systems that warn if you stray outside your lane are being enhanced with automated features that nudge you back where you belong. Automated parking is yet another popular feature in electronics-rich models. This is just the start as technologies like pedestrian avoidance systems make their way into new models, plus technology that automatically brakes or slows your car at intersections if another vehicle comes into your path.

All this is coming together to make our vehicles more fuel efficient, convenient, and safer as we drive toward a more connected future. Strap in because big changes are ahead.

Illustrating once again that technologies proved on the race track ultimately trickle down to production cars, NVIDIA is applying its artificial intelligence (AI) prowess to driverless electric race cars that will compete next year in the FIA Formula-e Roborace Championship series. Being used is NVIDIA’s DRIVE PX2 graphics processing unit (GPU) that has the computing power of 150 MacBook Pros and is the size of a lunchbox.

Ten teams will compete with identical driverless cars in the series’ one hour races. Teams will develop their own real-time computing algorithms and artificial intelligence technologies to gain a competitive edge as they strive to beat their competition.

 

As the auto industry rushes headlong into autonomous vehicles and technologies there are some important learning curves ahead. Google admitted as much when one of its self-driving cars was involved in a mild fender-bender with a bus…not necessarily the fault of the self-driving Google car, but no doubt caused by reacting to an unfolding situation in ways different than a human driver would react. Humans understand that mass-heavy buses do not always yield right-of-way. On-board computers wouldn’t necessarily know this unless taught.

Teaching autonomous cars how to anticipate the actions of human drivers in varying real-world scenarios is critical, and this kind of deep learning is data-intensive. This is being addressed by many companies including video game-notable NVIDIA, which works with automakers on advanced electronics systems.

The company’s new DRIVE PX-2 graphics processing unit (GPU), the world’s first in-car artificial intelligence supercomputer, aims to provide 360-degree situational awareness and facilitate the deep learning required for cars to sense their surroundings and navigate autonomously, using processing power equivalent to that of 150 MacBook Pros. DRIVE PX-2 delivers up to 24 trillion deep learning operations per second, over 10 times more computational horsepower than the previous-generation product.

It’s a dangerous world out there with road debris, varying weather conditions, and unpredictable drivers. These are just some of the challenges as autonomous cars use artificial intelligence to drive better than humans. Unlike video games, there are real consequences on the road and supercomputer power like this will help keep autonomous drivers…um, passengers...safe.