Tag Archives: artificial intelligence

Defining a Successful AI Strategy for 2018: Key Thoughts from a Data Scientist

February 21, 2018

As the hype around AI continues, building and executing on an AI strategy that supports market competitiveness will be top of mind for executives. The AI pilots are complete, yet executives are still grappling with what AI means for their organisations. As the use cases develop and capabilities emerge, businesses will look to defining an… Read More »

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 »

Who cares if unsupervised machine learning is supervised learning in disguise?

January 11, 2018

Previously, we saw how unsupervised learning actually has built-in supervision, albeit hidden from the user. In this post we will see how supervised and unsupervised learning algorithms share more in common than the textbooks would suggest. As a matter of fact, both classes can use identical equations for creating mathematical models of the data, and… Read More »

Teradata is on a Mission! And, 2017 was a Big Step Forward

January 1, 2018

Momentum — it’s easy to see when it is high, but hard to quantify. But at Teradata, we are in the business of quantifying. So when I look back at a very busy 2017 and think about how far we’ve come in our transformation as a company, I take pride in knowing that the numbers… 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 »

Q&A with Sri Raghavan: The Future of AI for Enterprises

December 14, 2017

Sri Raghavan, senior global product marketing manager at Teradata, answered a few questions on algorithms, bias detection and the maturity of enterprises using AI. As data analytics progresses, do you think there will be significant progress in the sophistication of algorithms? It’s not so much that one algorithm is going to make a difference in… 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 »