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Optimization of supply chain operations has become an imperative, as organizations grapple with customer demands, unpredictable events, and spiraling costs. On top of these persistent challenges, complexities are magnified by the myriad of tools required to manage everything from workforce schedules to resource allocation. To meet competitive demands, business decisio…

Leveraging analytics from insight to artificial intelligence (AI), business leaders can make sense of their rapidly-growing piles of data to improve their operations. Here are some tips for using analytics to create a measurable business impact. #1: Put the decision before the data With a decision-first strategy you define the business objective first, then determin…

On the face of it, no one should be more bitter about AI than Chess Grandmaster Garry Kasparov. In 1997, he took part in the most well-publicized man-machine contest of the 20th century, a chess match against IBM’s Deep Blue supercomputer. When Deep Blue won, it was a defining moment for artificial intelligence, the Watson / Jeopardy moment of its day. But Kasparov s…

Analytics — including machine learning and manufacturing optimization —is taking off in the auto industry, and has the potential to go much further. That was my main message in an interview I gave recently to reporter Megan Lampinen of Automotive World in the UK. As I noted there, analytics plays a part in many parts of the automotive industry lifecycle, all the way…

The possibilities of artificial intelligence are endless. AI helps businesses create tremendous efficiencies through automation, while enhancing an organizations ability to make more effective business decisions. However, it’s no surprise that companies are beginning to be held accountable for the outcomes of their AI-based decisions. From the proliferation of fake ne…

5 Best Practices for Connecting Data and Analytics to Business Process The need for competitive advantage sees companies increasingly turning to analytics to operationalize their data. Leveraging analytics from insight to artificial intelligence (AI), business leaders can make sense of their rapidly-growing piles of data to improve operations. Benjamin Baer shares 5…

Machine Learning is defined to be ‘super-human’, but how do we deal with mistakes and errors when the stakes become higher? Using a neural network model to detect fraud has tremendous benefit in keeping fraud under control and the cost of a false positive (blocked legitimate transaction) is low. But as we start looking to machine learning to drive our cars, perform su…

One of the machine learning mistakes was the tragic death of Elaine Herzberg in Tempe, Arizona by UBER’s self-driving car. Initially there was a focus on the fact that machine learning made an error, but in fact, the answer was even more unsatisfying: the algorithm did detect the pedestrian but the car was programed to be less sensitive to potential false positives, c…

Why Is Explainable AI Important? Do you want decisions around made by algorithms that you cannot understand, and perhaps their creators don’t understand? While many are not worried about the rise of Skynet (the dangerous AI system in the Terminator films), some are concerned about the rise of machine learning algorithms that are not used responsibly. Explainability i…

One of the landmark moments in the history of AI came 21 years ago, when Chess Grandmaster Garry Kasparov beat IBM supercomputer Deep Blue — and then was beaten by it. How did this change the future of artificial intelligence? Did it spell the end of the human race as thinkers and competitors? As a researcher and practitioner in machine learning, I know that each ac…