Sam Schmidt didn’t need a steering wheel to manage a 152 mph pace at the Indianapolis Motor Speedway in May. He just tilted his head, and technology did the rest.
The winning Indy Car driver and team owner is a quadriplegic, the result of a 2000 Orlando Speedway crash. Working with automotive engineers and medical professionals, Schmidt transformed a 2016 Chevrolet Corvette into a semi-autonomous motorcar (called SAM for short). SAM responds to Schmidt’s head and eye movements through lightning-fast advanced computing technologies so he can pursue his passion: racing.
The SAM car is possible thanks to massive amounts of data, advanced technologies like analytics, and affordable, big computing power. You can toss around buzzwords like “big data” and “IoT” all day, but affordable data storage and big computing are what make the real difference.
Big computing has only been within our grasp for a few years. Let’s break it down: As recently as 1961, microprocessors as we know them didn’t exist. Computing was carried out with a bunch of vacuum tubes and transistors. Back then a gigaflop cost $8.3 trillion in today’s money. Today, a gigaflop costs about 4 cents. A gigabyte of storage in 1960 cost the equivalent of $28.9 million in 2016 dollars. The cost of storing a gigabyte today? Right around 2 cents.
We get caught up in the big data hype. The truth is, storage costs plummeted while computational prices dropped even more dramatically. Now anybody can take on big computational challenges because the associated costs are no longer an obstacle.
It’s hard to believe NASA sent Apollo astronauts to the moon using less computing power than the average family car contains today, but it’s true. So imagine what redesigned algorithms, parallel processing, lightweight message passing and in-memory computations can achieve. Daunting computing problems that once took all day are now completed in minutes. That’s barely enough time to grab a cup of coffee and get back to your desk. Fifty years ago, we knew what we needed to make machine learning and cognitive computing part of everyday life but we couldn’t afford it. Now we can.
When you add up big data + big computing + advanced analytics + machine learning + IoT, you arrive at a technological state where computing can genuinely enhance people’s lives. Machines can now “think” in ways that open the door to new human experiences and achievements. That’s what’s really exciting.
Ladies and gentlemen, start your engines.
For IT organizations, your first move is modernizing your playbook to prepare for reaping the rewards of big computing. That includes its offspring: machine learning, artificial intelligence and cognitive computing. There are a number of elements to address:
Develop your talent. The organization must understand basic analytics to see the possibilities. Bring your IT team up to speed with classes and training so they can support your data scientists. An IT team that supports data scientists and understands the many ways data will need to be organized is way ahead in the race.
Govern your data. Data rules should rev up access to data rather than constrain it. To win this race, everybody needs swift, managed access to necessary data.
Become an explorer. Invest in analytic sandboxes that accommodate large-scale cluster computing. An exploratory playground helps your data scientists look deep into the data to discover previously hidden patterns and insights.
Embrace failure. Your team needs to know that it’s OK to try something new and fail. What’s key is failing fast, learning from it, then rising up to try something new. Many IT projects don’t readily show value. But the return on your big computing and analytics investment can add real numbers to the top and bottom lines fast. Keep trying until you find the winning combination for your organization.
In June, Schmidt and his SAM car competed in the 94th Pike’s Peak International Hill Climb. He made it about halfway up the 12.42 mile, 156-hairpin-turn course before weather conditions stopped the race. In late September, Schmidt’s home state of Nevada issued him the nation’s first autonomous vehicle restricted driver’s license.
Sam Schmidt regained his independence by harnessing the power of technology. His work with the SAM car opens the door to anyone struggling with physical challenges to independently take the road again. Imagine what that level of big computing could do for your organization’s journey.
It boils down to this: Do you want to be in Sam Schmidt’s lane, putting innovation and advanced computing to work in a way that makes a significant human difference? Or, do you want to play it safe in the far right lane and eat dust? The computing horsepower you need today is here for you. Start your engines, and drive.
Keith Collins is an executive vice president and CIO at SAS. He is passionate about delivering on the promise of big data and big analytics. Except for a stint in sales, he directed research and development at SAS for most of his career, including 13 years as CTO. His latest charter is to redefine the role of IT from tactical to strategic and to accelerate SAS into the cloud.
Collins holds a degree in in computer science from North Carolina State University and is a founding member of the NC State computer science department's strategic advisory board. In 2003, the university named him a distinguished engineering alumnus. Collins also serves as an adviser for Bull City Venture Partners and is a patron of the North Carolina Museum of Natural Sciences.
The opinions expressed in this blog are those of Keith Collins and do not necessarily represent those of IDG Communications Inc. or its parent, subsidiary or affiliated companies.