Session Overview

We need to collect ever-larger amounts of data! Why? Because we might find patterns of behavior in our macro world –people, environment, upper atmosphere, and deep oceans- and in our micro world – disease vectors, the heart of the matter (currently quarks), and so on. Once we have filled the big data silos, we will not only find patterns of (hidden) behavior but we will be able to make machines learn the behavior and mimic the operations performed by clever humans in the macro and micro world. Then we have a disaster created, say, by greed, and all the systems that have discovered and learned the behavior of the ‘market’ failed to work costing trillions of dollars, yes and euros: We find that there was yet another pattern of behavior we had failed to discover and learn – the market sentiment was what we had missed so the claim goes. Oh, dear. A race is on to collect qualitative sentiment data -words, gestures, and voice intonation of the traders and bankers - on top of collecting terra bytes of quantitative high-frequency trading data- and then trying to unravel and learn how the two data sets will be fused to make a decision. Data fusion will be the next challenge after the statistical machine learning folks have cleared the deep learning stable. I will talk about my experience of sentiment analysis and data fusion and will sprinkle my talk magical dust of artificial intelligence.


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    Needles in a Haystack: Big Data and Bigger Promises?

    • Abstract & Bio

    • Needles in a Haystack: Big Data and Bigger Promises?


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