When 1+1=10
I've been working with AI for 30 years. Until recently, it always felt like we were using a sledge hammer on a carpet tack. But the time has finally arrived for all business leaders to take a look.
I first used AI to learn how to plan routes around a city. Google maps commoditized the same service 10 years later, but at the time we were developing a solution for transit planning, this was a new frontier. If we know how to do something, we program the computer to do it. If we don't know how to solve a problem, AI offers an approach to program the computer to learn how to solve it.
It turned out that there were simpler ways to solve our navigation problem, and simple is always best in software. The issue was that AI needs a lot of data to learn from.
And that's why AI and Big Data belong together. Separately, they intrigue engineers but have little commercial value. Without AI, Big Data is simply hoarding stuff in case it becomes useful one day. Without Big Data, AI is rarely the simplest solution to a problem.
But together, AI can search for value in Big Data. If there are useful patterns in there, 1+1=10!
Breakthroughs happen when technologies are combined—just look at the way the iPhone combined the latest in storage, touch, haptic design and materials.
When you use Siri, Alexa, Echo or Google Assistant, you're tapping into decades of speech recognition research with masses of data. (Thank you IBM—now speech recognition is also free.)
Make no mistake, there's a ways to go before this combo reaches the promise that the technology press would have us believe. But they'll travel that road together, and the valuable breakthroughs will hit the mainstream.
Don't wake up one day and find yourself disrupted
Whether or not you find this stuff exciting, you need to be aware of the trends and breakthroughs. Divide a sheet of paper with two vertical lines.
In column 1, list the chunks of data at your disposal today. Include data from inside and outside your business.
In column 2, place a check mark against the data that you use to record transactions.
In column 3, list the insights that each chunk of data provides you with. Then lists the insights that you wish you had.
Column 3 gives you a list to begin research into how AI could disrupt—or ignite—your business. The choice is yours.
( Btw, column 2 informs your research into blockchain, but that's another story.)
Here's what that might look like ...
(with thanks to Tom Wujec)
.. and if you missed these related articles, go back and take another look:
Great article. Genuine question - what was AI known as 30 years ago?
Great article, Graham. It's all about the transition from data -> information -> insights -> actions. The combination of Big Data and AI is exciting and holds so much promise. No wonder the data science profession is taking of fast!