Fujitsu Laboratories Ltd. today announced the development of “Wide Learning,” a machine learning technology capable of accurate judgements even when operators cannot obtain the volume of data necessary for training. AI is now often used to leverage data in a variety of fields, but the accuracy of AI may be impacted in cases where the volume of data to be analyzed is small or imbalanced. Fujitsu’s Wide Learning technology enables judgements to be reached more accurately than was previously possible, and learning is achieved uniformly, no matter which hypothesis is examined, even when the data is imbalanced. It achieves this by first extracting hypotheses with a high degree of importance, having made a large set of hypotheses formed by all of the combinations of data items, and then by controlling for the degree of impact of each respective hypothesis based on the overlapping relationships of the hypotheses. Moreover, because the hypotheses are recorded as logical expressions, humans can also understand the reasoning behind a judgement. Fujitsu’s new Wide Learning technology allows for the use of AI even in areas such as healthcare and marketing, where the data needed to make judgements is scarce, supporting operations and promoting the automation of work processes using AI.