by Greg Simpson

The year of Alexa and the coming decade of A.I.

Jan 30, 2017
AnalyticsArtificial Intelligence

CES was all abuzz about Alexa and Davos was talking about the impact of the advancements of artificial intelligence

I mentioned in a blog last year that we are at the dawn of a new age of artificial intelligence (A.I.). And 2017 certainly is the beginning of a world that is rapidly embracing A.I. The halls at CES were filled with talking devices, many powered by the same presence, Alexa, Amazon’s slowly evolving virtual assistant. There were several conversations about the impact the impending robot revolution would have on our lives, jobs and future occupations. IDC predicts that spending on A.I. will grow from $8 billion to $47 billion by 2020. This is a seismic shift. Computer chips are being redesigned to work like the human brain. The World Economic Forum at Davos had a lot to say about A.I. and its impact on humanity’s future, calling cyber-physical systems (A.I. and robots) the Fourth Industrial Revolution.

We are already seeing some big impacts from A.I. At Davos, Sergey Brin was quoted as saying “I didn’t see A.I. coming,” but fortunately, thanks to Google’s innovative culture, it happened anyway. In November of 2016, Google Translate switched over from phrase-based translation, where words and phrases are translated somewhat independently, to Google Neural Machine Translation, enabling an entire sentence to be considered in the translation, yielding significant improvements. Neural nets are back, and the forces that A.I. and robotics can unleash in the marketplace are dramatic. Over at IBM, Watson is helping doctors improve outcomes. The discussion of I.A. (or intelligence augmentation) instead of A.I. paints a future where cyber intelligence and human intelligence work together. No doctor can ingest the thousands of research papers churned out each day in the medical field, but a computer can. There is tremendous interest and investment underway to capitalize on this new age. In my October blog post, “A.I. Strikes Back,” I talked about the forces that are coming together to make A.I. possible, but I didn’t say a lot about what you should do.

Here’s my list for what you, as an IT leader, need to do to prepare for the age of A.I.

1. Educate yourself. This is the first step in handling any disruptive force. If you don’t know what you are up against, it is hard to win. You need to be able to sort the hype from the heart of the matter, and to do this you need some basic understanding of the beast. Do you have a fundamental understanding of machine learning and how it’s already being used in your industry? The reality is that machine learning has been around for years and is in use in many areas today, it’s just getting faster — and much smarter. Take some time to learn a little about what this Fourth Industrial Revolution is all about.

2. Identify a thought leader to help you shape your company’s involvement in the A.I. movement. Is this fundamental to your work? How does it impact your strategic plan? How many resources should you devote to it? Consider David Kenny’s comments at Davos. Kenny, the chief of IBM Watson, pointed out that this isn’t just an extension of your IT efforts, this is “fundamental to the most important decisions that you make. Anyone in your company who makes important decisions will need to understand this viscerally.” So, first you need a basic understanding, and then you need a thought leader to lead your company into this new age.

3. Data. You need data. Lots of data. Many of the initial A.I. efforts leverage machine learning. In the case of machine learning, having lots of data is a competitive advantage. One of the reasons Tesla is well positioned for the autonomous car market is simply because it has so much data. Instead of collecting data from a small number of specially equipped vehicles, Tesla collects data from every mass market car it has produced since October of 2014. Google collected 1.5 million miles of self-driving data in six years. Tesla collected 47 million miles in six months. The ability to use large amounts of data to train and test your predictive models is a significant advantage when it comes to artificial intelligence. So get your “data office” in line, build your data lake, and prepare. Hire people with the skills and understanding of how to bring your industry data to fruition for the purposes of the A.I. revolution. Artificial intelligence and analytics are both about making your business smarter.

security code big data cyberespionage byte Gerd Altmann / Pixabay

4. Begin. First-mover advantages are huge during industrial revolutions. Ford had a significant first-mover advantage when it introduced the assembly line for large-scale production of automobiles in the second industrial revolution. Intel created the world’s first microprocessor in 1971 for the third industrial revolution, and today it dominates the market.

First-mover isn’t a guarantee, there were several search engines before Google, and Netscape couldn’t compete with Internet Explorer when Microsoft entered the browser market, but the first-mover advantage can give you a significant head start in a competitive marketplace. To begin, you need an agile culture. I say agile culture because I’m not talking exclusively about agile software development, I’m talking about a culture that enables innovation. Minimally viable products, delivered with minimally viable governance systems with the speed necessary to arrive at the first-mover position ahead of all your other competitors. (You also need an agile software development culture, but that isn’t sufficient by itself.)

These sound like simple steps. Learn, pull in a big thinker, get your data in shape and begin. However, lots of companies that think they already understand their markets don’t have a good understanding of their data, and they’re very slow to start new disruptive journeys. Don’t be one of those companies. Begin your journey into the age of artificial intelligence now.