Training data is the lifeblood of AI. Without it, computers couldn’t be trained to see, speak, or perform any intelligent functions. Yet, so much of the training data used today is difficult to obtain and low-quality, ultimately resulting in algorithms that don’t work as desired and exhibit strong cases of bias. As more and more businesses develop their own machine learning algorithms, how can they ensure that their training data is high-quality and well-rounded while being delivered in a secure way? In this rapid fire session, learn how top organizations obtain superior quality training data without compromising privacy or security — and how it’s possible to make positive social impact along the way.
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