Here at a16z, we treat “big data” and “machine learning” as connected activities. People have been talking about the need for more ‘analysis’ and insight in big data, which is obviously important, because we’ve been in the ‘collection’ phase with big data until now. But the innovation in the big data world that I’m most excited about is the ‘prediction’ phase — the ability to process the information we’ve collected, learn patterns, and predict unknowns based on what we’ve already seen.
Machine learning is to big data as human learning is to life experience: We interpolate and extrapolate from past experiences to deal with unfamiliar situations. Machine learning with big data will duplicate this behavior, at massive scales.
Where business intelligence before was about past aggregates (“How many red shoes have we sold in Kentucky?”), it will now demand predictive insights (“How many red shoes will we sell in Kentucky?”). An important…
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