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In Designing AI
Data Science, Big Data, Machine Learning, Deep Learning, Neural Networks, Artificial Intelligence … so many buzz words to choose from, yet Gartner reports that “85% of Fortune 500 organizations will be
In Designing AI
Traditional enterprises are getting disrupted by the newcomers at an unprecedented speed. What is their competitive advantage? In the world, where the barriers to entry are continually decreasing, the speed
In Designing AI
Ever since enterprises started to digitize, they have been capturing large sets of data. Today, they are using that data to discover insights which drive new profits and revenue opportunities.
In Designing AI
Building a scalable machine learning solution takes a lot of up-front solution architecture. It’s easy to process more and more data, but how do you do that while still
In Designing AI
“Consider this figure: $136 billion per year. That’s the research firm IDC’s estimate of the size of the big data market, worldwide, in 2016. This figure should surprise no one with an
In Designing AI
In the ideal world, we will have enough training data and large enough neural nets for computers to be able to provide us all the insights we need. In the
In Designing AI
Enterprise Artificial Intelligence is starting to affect every industry we know. Algorithms that are becoming deeply embedded in the back-end; analyzing data, finding patterns, creating powerful knowledge graphs that power search
In Designing AI
During the digitization process, most of the knowledge is lost, and it is nearly impossible to recapture the lost knowledge using existing data alone. Often, the input of an individual
In Designing AI
Today, many machine learning algorithms are based on patterns and statistics. That means that without a lot of training data these algorithms are not that intelligent or effective. People often