Tag Archives: AI

What is machine learning?

February 12, 2018

Every useful machine – from advanced AI through to the humble toaster – has to possess ‘knowledge’ about the world in which it operates. For example, within the design of a household toaster, much knowledge about the world must have already been implemented. This is implicit knowledge. The toaster ‘knows’ what electrical voltage is available… Read More »

Wait, machine learning and artificial intelligence aren’t the same thing?

February 5, 2018

Everybody seems to be talking about artificial intelligence and machine learning. Ever since Spielberg’s 2001 movie A.I. Artificial Intelligence, the abbreviation AI has been readily recognizable. News outlets have recently carried headlines such as, “AI in your car can brake faster than you”, or “Police use AI to predict crime”, or similar flashy statements. But… Read More »

Creativity and Critical Thinking in the Age of Enterprise AI

January 16, 2018

What, if anything, should worry us about artificial intelligence today? Is it the worry that it will take over jobs around the world? Most definitely not. The fact of the matter is that what AI has gotten very good at solving for certain problem sets, however it still lacks overall knowledge of context to the… Read More »

Three Implications of AI for the Enterprise

January 4, 2018

From self-driving cars to photo recognition, AI is becoming an increasing presence not just in our headlines, but also in our lives. Yet depending on the business problem and data involved, there are challenges to applying AI in an enterprise context. Enterprise AI is a different game with different rules. Some of the differences, which… Read More »

Is it Too Late for Your Business to Win the Race to AI?

December 19, 2017

Artificial intelligence feels like it’s in the middle of an arms race — in the boardroom at least. Over the last few months, nearly every executive I’ve talked to, be it in banking, telco, manufacturing or many other industries, has talked up AI, machine learning and deep learning as “must-have” technologies. And while Teradata’s latest… Read More »

Supervised learning in disguise: the truth about unsupervised learning

December 12, 2017

One of the first lessons you’ll receive in machine learning is that there are two broad categories: supervised and unsupervised learning. Supervised learning is usually explained as the one to which you provide the correct answers, training data, and the machine learns the patterns to apply to new data. Unsupervised learning is (apparently) where the… Read More »

Built like Blockchain? Creating a Foundation for Trusting AI Models

December 6, 2017

What is my AI model doing? That question is critically important to companies today — especially in heavily regulated industries. Banks need to clearly tell their customers and regulators why they blocked someone’s request for more credit or why a certain transaction triggered a fraud warning. But finding out the answer isn’t always immediately obvious.… Read More »

The 13 rules for measuring the Turing time of your AI

November 27, 2017

Last time we discussed how the Turing test, flawed as it is, still holds some relevance for AI development – especially when it comes to intelligent assistant applications. For more on that, read more here. However, consistently measuring the test is a methodological problem, as it focuses on psychological measurements. Because a human makes the… Read More »

Building Trust in AI: How to Get Buy in for the Black Box

November 21, 2017

Maybe it’s something innate to human nature, or maybe we’ve all seen one too many sci-fi movies (I’m looking at you Hal and 2001: A Space Odyssey), but people tend to view new technology skeptically. This is especially true when it comes to technology that makes recommendations or tells us how to do something. A… Read More »