Tomorrow is Already Here and So Is AI

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People think about AI as something that’s coming or a future reality to watch, but AI already benefits our lives in ways we might not realize. It’s not part of some futuristic world that’s yet to come, it’s here now.

When it comes to discussing AI, I like this perspective from IBM Chief Executive Virginia (Ginni) Rometty, who said:


AI – It’s been around longer than you think

You need to head way back in time to Alan Turing’s Bombe machine (designed in 1939 to decipher Enigma machine messages during WWII) to find some of the early technology at the foundation of the machine learning concepts of today. Author Isaac Asimov (who wrote iRobot) published the Three Laws of Robotics in 1950. Fast forward past IBM’s Deep Blue defeat of Garry Kasparov in chess in 1996, the Roomba that started self-cleaning homes in 2002, and Honda’s ASIMO robot (unveiled in 2000) that delivered trays in a restaurant in 2005, and you start to see that artificial intelligence and machine learning technologies have been around for a long time.

It’s tempting to think that “recommendation engines” – those handy algorithms that help us add more items to our shopping cart and expand the retailer’s share of our wallet – are new but they date back more than a decade. Remember when TiVo suggested shows to watch?

Amazon reported that 35% of its revenues in 2006 came from cross selling or upselling thanks to those recommendation engines, and McKinsey estimates cross selling efforts increase sales by and we all know they work!

But even with all these common examples of AI and machine learning at work in our daily lives, a HubSpot survey found 63% of people aren’t actually aware they use artificial intelligence technologies now.

AI in the Real World

AI is so much more than chatbots and recommendation engines. It’s helping to improve lives in so many ways today, not in some distant future:

Tailored Medicine: Five years ago Bryce Olson believed he was going to die from Stage 4 pancreatic cancer. After trying the standard, well-known treatments, he learned about genomics and the work at Intel. He told his doctor to “sequence me” and was able to identify the differences between his normal DNA and his tumor’s DNA to drive a more effective treatment that succeeded in clearing his cancer. Unfortunately, he’s had a recurrence, so Olson is once again leveraging AI to fight his next battle. Bryce inspires me and everyone at Intel with his perseverance and passion – we are all rooting for him to win the fight once more.

Scoring Big Gains: Sports are driven by data and have been since long before Billy Beane attempted to assemble a competitive Oakland As team in 2002 based on statistical analysis not scouting reports and intuition. (If you aren’t familiar with this story, I highly recommend reading Moneyball by Michael Lewis). This year, the Orlando Magic announced it will be the first NBA team to use AI to analyze college players’ videos to streamline decisions on who to draft and who to pass on.

Wearable technology is also often cited as an AI application that’s helping fine tune player performance and reduce injuries. And, NASCAR is using cameras and AI to identify racing infractions. I’ve no doubt we will see more officiating and coaching applications for AI and machine vision in the very near future.

Digging Up Efficiency: Self-driving tractors and software solutions in the cloud help cattle producers know how much their cows need to eat, when, and if they’re showing early signs of sickness so they can be treated before it gets serious (or impacts the rest of the herd) are just two examples of how AI is changing agriculture. Here’s another:

NatureFresh Farms uses cameras, sensors and AI to look at plants in the greenhouse and predict when their produce will be ready for harvest. They have AI-enabled software to help optimize nutrition for vegetables across their 185 acres of greenhouses, and use smart building technology to automatically open windows, close curtains or turn on fans to maintain optimal growing conditions and reduce energy use. They’ve reduced labor, increased yields and more efficiently managed their harvest to sell product according to real-time data about yields, eliminating guesswork.

Better Quality Controls: With parts racing by on assembly lines around the world, quality control testing usually involves items being pulled off the line and tested. During the test, the line was still running so defective parts could get through. It’s an ideal application for AI, cameras and sensors to can detect minute flaws, like they’re doing at AUDI.

Blueline is also working with parts manufacturers to eliminate manual inspections in favor of more accurate and rapid quality testing using AI to ensure every part meets specifications; reducing recalls and improving safety.

AI Under Control

We can’t and shouldn’t talk about AI without looking at the privacy and ethical considerations that come into play when businesses and governments have access to so much information. As my colleague Melvin Greer notes we can’t advance AI without ensuring ethical, privacy, and values-based frameworks are in place. Melvin has also helped author Intel’s AI Policy Initiative to ensure our POV is influencing strategic AI efforts in the US Federal Government.

With those protections in place, and a healthy system of checks and balances to continue to hold companies accountable, future applications for AI to improve our world and our lives are undeniable … and chances are you’re already interacting with AI more often than you realize.


Published on Categories Big Data and Analytics, Business Intelligence, High Performance Computing, Internet of Things, IT Leadership, IT ManagementTags , , ,
Rachel Mushahwar

About Rachel Mushahwar
