Month: September 2017

Great time at ComTech Forum: Deep Learning

We had a great time at the Telecom Council’s ComTech Forum on Deep Learning. We met some great people and had some fun conversations about the cost, time and complexity of delivering huge impact with deep-learning. We heard a lot about the state of data-science in the Telecom, Media and Entertainment industry from tech leaders

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If AI has the power to transform all industries, why hasn’t it?

There is a ton of noise about AI today. A quick search on Google for “Artificial Intelligence” returned 82M results and almost 4M news stories. Bloomberg reported this week that mentions of AI in earnings transcripts has risen from less than 60 in 2016 to over 250 in just Q1 of this year! In a

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Training an army of Wilburs and Orvilles the (W)right way.

There is an enormous corpus of articles, blogs, discussions, and posts around the subject of the AI/machine learning/deep learning supply and demand problem. I do not think anyone doubts or questions the fact that there is a deficit of scientists. Most of the disagreements are around the scale of the deficit, what that supply and demand

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Making Assumptions – Musings from a Silicon Valley Data Scientist

The following article discusses one of the many things that I have learned as a data scientist. It does not involve any popular new methods or deep learning and perhaps does not sound as cool. It is something much more primary, but absolutely crucial to any scientist’s career. Whenever a problem is given to someone, and their

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A change is coming to AI.

I will try to make this article concise and to the point. As I reflect on everything I want to say about this topic that goal quickly seems unachievable, but here I go. Data science is my passion. I have been doing it and machine learning for well over a decade across a dozen different

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