Tag Archives: Danko

What is the definition of AI?

March 5, 2018

Finally, here we are. After four posts discussing the differences between machine learning and AI, and demonstrating that AI can live without machine learning (and vice versa), the time has come to define AI. Easy, right? Not necessarily… Let us first point out that there is no committee to decide which products constitute an AI… Read More »

AI without machine learning

February 26, 2018

Previously, we explained how machine learning can have its own life and doesn’t need to be a part of AI. Here, we want to explain something that may surprise you: it is possible to build AI without machine learning. “A car with no engine!?” you may cry. Analogies are made to be broken. There are… 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 »

When big data becomes vast, what’s your data dropping strategy?

January 30, 2018

When big data technology is pitched, it’s often said that this is the best way to store all your data. The idea is that you will not use an expansive database, but commodity hardware that is expandable at a low cost, and runs on open source software. Therefore, you would create a data lake to… 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 »

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 »

Is the Turing test still relevant? How about Turing time?

November 14, 2017

If you’ve found your way to this blog, I have no doubt you’re aware of Alan Turing. In 1950, the father of modern computer science created a test designed to determine a machine’s ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. Turing described his test as “The Imitation Game”… Read More »