March 2, 2018
Artificial Intelligence (AI) is one of those big trends that’s going to change everything. If we don’t use it or change with it, we’ll get run over by those that do. AI is an essential strategy consideration for future dominance in our verticals. It’s also a way to attract and keep key strategic partners because you’re in a position to collect data and insight they want. AI is a step beyond converting data into actionable knowledge because we’re taking some of the human review and action out of the process. Data Analytics based on Big Data is great and a necessary foundation, but now we’re talking Machine Learning, Cognitive Computing (thinking computers), Self-Learning, Heuristic, or Deep-Learning.
For example, in conventional robotics you have to program each step and movement. The machine is only as smart as you are and how successful you are at telling it what to do. But with a self-learning or deep-learning robot, the robot learns like a human child. There are rules of what not to do (e.g., I can’t move through solid walls), but it can then learn by watching and doing. By doing so, the robot infers additional rules (e.g., I have to lift harder for heavier objects).
Google Photos can, for instance, learn by observation. It sees photos from different angles and times (even years apart) and understands when photos are of the same person. So much for anonymity. Google Home and Amazon’s Alexa are learning to hear “natural language” with all our range of pronunciation, accents, and slang. It’s no longer necessary to use more structured queries limited to strict rules like SQL (Structured Query Language). Both Google Home and Alexa are still learning. They’re not perfect. But, like the 3-year old child, they’ll get better and smarter with more examples (data) and time (practice).
Artificial Intelligence is one reason the company with the biggest data mountain wins the future in particular verticals. You need massive amounts of data (Big Data) to provide the range, statistical power, and more behind Data Analytics and AI.
An algorithm is great. That’s a fancy name for the rules and relationships between rules. An algorithm is how we mathematically model the real world and make predictions. But even if someone else comes up with a better algorithm, they need your data to make it work. That means data mountains have value. Increasingly with AI, the computers will be building and testing algorithms (rules and relationships between rules) on their own.
We need to think about starting on building these data mountains with our Cloud Applications and Internet-of-Things (IoT) offerings. Data becomes an enterprise value multiplier. It can enable predictive failure analysis, new insights into quality and value, and more. The results are competitive advantage, higher margins, new value chains, and new business lines for those who lead their verticals.
We don’t have to be Alphabet (Google), Amazon, Apple, Facebook, IBM, or Microsoft to benefit from AI. In fact, we’ll be using tools from those companies to succeed in our verticals. But we need to know this is where the future is going, incorporate it into our planning, and prepare. Data Architecture and Data Aggregation are now essential considerations. Cloud-based Applications and IoT help gather the data and can deliver shorter-term tactical wins, but they’re also part of a longer-term strategy.
