Category Archives: Machine Learning

Mike Gualtieri: How to Make AI Happen Without Getting Fired

Mike Gualtieri from Forrester Research offers 8 tips on how to make AI happen without getting fired. These tips are based on his discussions with enterprise data scientists and enterprise leaders who embarked on machine learning and AI projects in … Continue reading

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Is Your Insurance Business Missing a Critical Decision Window When it Comes to AI?

Yesterday Craig Bedell from IBM’s Global Insurance Industry Leadership Team wrote: “I believe most insurance companies have hit a critical point in time with regards to their investments in analytics, innovation and even AI, where business leaders are measuring more … Continue reading

Posted in Business Analytics, Business Processes, Decision Modeling, Insurance Industry, Machine Learning | Leave a comment

The ML Surprise

Peter Norvig points to the ML “surprise” described in Josh Cogan’s article “The Surprising Truth About What it Takes to Build a Machine Learning Product“:  “Optimizing an ML algorithm takes much less relative effort, but collecting data, building infrastructure, and integration each take much more work. … Continue reading

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Data Decisioning

Data Decisioning was recently founded by Peter Schooff and John Morris, two veterans with decades of success in enterprise technology. Why? “What’s more important than data to today’s enterprise? The decisions a company makes based on that data will determine their success … Continue reading

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Google: Your Deep-Learning-Tools-for-Enterprises Startup Will Fail

Today Peter Norvig, the Research Director at Google, posted at LinkedIn: Whether you like it or not, selling enterprise tools for machine learning is really hard. Why? The industry is still fragmented, too many different components and moving parts without standardization, … Continue reading

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Adversarial Machine Learning

Machine learning techniques were originally designed for stationary and benign environments in which the training and test data are assumed to be generated from the same statistical distribution. However, when those models are implemented in the real world, the presence of … Continue reading

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Decision Optimization fueling growth in Energy and Utilities

Decision optimization and machine learning techniques are driving better resource planning and scheduling decisions at Energy & Utilities for a range of use cases like power generation planning, pricing optimization and more. Link

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