Machine Learning Thursdays: Living in the Age of Machine Learning
The hype machinery is kicking into high gear with all types of vendors touting offerings, and even leadership, in the emerging markets for machine learning and Artificial Intelligence, or AI. According to VentureScanner.com over 1700 companies have raised over $13 billion of investment—all bidding for dominance in this new world.
The big vendors want in on the action too. Salesforce claims it’s Einstein delivers ‘AI for Everyone’ (does E = AI2?!). IBM has been positioning Watson as the AI solution for business—accidentally leaving the door open for a more astute Sherlock to steal the show.
AI: A Doomsday or Polyanna View?
Journalists, writers, filmmakers, and even the average “Joe blogger” have been sharing their visions of what a machine learning and AI future hold. Debates about the end of work caused by robots are all over Twitter—hashtag #Robocalypse.
In fact, the fear of evil robots ruling the world is so common, it’s a popular theme in the movies, too. Each sequel in the Terminator series seemed to add a new line of machines (T-800, T-1000, T-X) that were more evil and powerful than the previous. Even more scary to me are the ones that catch us off guard, evolving on their own without our knowing, like HAL in 2001: A Space Odyssey or Ava in Ex Machina.
Others are much more optimistic. Think Wall-E. This adorable tin can, with a crush on fellow robot EVE, makes a perfect playmate for our kids (Disney really is genius with merchandising). And who doesn’t want to upgrade their Roomba for Rosie the Robot Maid from The Jetsons?! Good-bye laundry, dishes, vacuuming, mopping floors, and scrubbing every nook and cranny. Sounds like utopia to me!
Real Life Applications Right Now
The benefits of machine learning and AI are not just futuristic. The emerging self-driving car is a great example. I must freely confess that I’m quite jealous of people who own a Tesla with its self-driving features. Wasn’t it every 1980s kid’s dream to own KITT from Knight Rider? I think it’s amazing how the Tesla in this Youtube video predicts (and avoids) the accident seconds beforehand— listen for the warning beep from the Tesla then start counting.
The applications of machine learning to business are far and wide. Improving the customer engagement from brand management, campaign performance, and individual account management. Overseeing the operation of manufacturing processes, logistics, and supply chains. Managing cash flow, financial risk, and quarterly close. That doesn’t even capture the tip of the ice berg.
Machine Learning and Artificial Intelligence Defined
But what is machine learning? Tom Mitchel, in his book Machine Learning, provides an elegantly simple definition:
“The field of machine learning is concerned with the question of how to construct computer programs that automatically improve with experience.”
And what is artificial intelligence? According to Merriam-Webster dictionary:
“1: a branch of computer science dealing with the simulation of intelligent behavior in computers. 2: the capability of a machine to imitate intelligence human behavior.”
The two terms are interrelated and yet also distinct. Machine Learning speaks to an element of ‘intelligent’ evolution (i.e. learning) while AI solutions tend to mimic additional human cognitive capabilities beyond learning such as seeing, conversing, walking, driving.
Welcome to Machine Learning Thursdays
To develop a deeper understanding of machine learning and artificial intelligence will require us to move beyond simple definitions into use cases, customer case studies, product and technology explorations, and emerging trends. However, we need to begin somewhere. And so today marks a line in the sand—a start line—for a weekly journey through this new blog series, Machine Learning Thursdays.
Be sure to join us on this weekly exploration of the hottest field in the industry.
You can catch up on all our previous blogs about machine learning, artificial intelligence, and predictive analytics on our Thursday series page.