Machine Learning is part of a broader conversation around Artificial Intelligence and related themes, which has recently begun to (re-)emerge from the labs and enter mainstream technology conversations. The terms are horribly abused, and mostly badly misunderstood, but there is clearly something afoot.
And with good reason. These tools and techniques offer us one viable means to extract value from growing volumes of data. Humans can’t classify millions (or billions) of images. But machines can be trained to recognise the patterns of interest – machines can learn – and then they can do it. Quickly, accurately (if properly trained), cheaply.
And now McKinsey has a useful piece in their online journal, McKinsey Quarterly, which tries to tell executives what they need to be aware of.
And if this looks like something your business needs to better understand, the inaugural Smart Data conference is in San Jose next month. It’s an evolution from the Semantic Technology conference series I mentioned in my blog post, above, and they always did a great job of combining the academic possibilities with business realities…
(Cross-posted @ Paul Miller)