Fujitsu Laboratories has developed what it believes to be the world’s first AI technology that accurately captures essential features, including the distribution and probability of high-dimensional data in order to improve the accuracy of AI detection and judgment.

High-dimensional data, which includes communications networks access data, types of medical data, and images remain difficult to process due to its complexity, making it a challenge to obtain the characteristics of the target data.

Until now, this made it necessary to use techniques to reduce the dimensions of the input data using deep learning, at times causing the AI to make incorrect judgments.

Fujitsu has combined deep learning technology with its expertise in image compression technology, cultivated over many years, to develop an AI technology that makes it possible to optimize the processing of high-dimensional data with deep learning technology, and to accurately extract data features.

It combines information theory used in image compression with deep learning, optimising the number of dimensions to be reduced in high-dimensional data and the distribution of the data after the dimension reduction by deep learning.

Akira Nakagawa, associate fellow of Fujitsu Laboratories comments: “This represents an important step to addressing one of the key challenges in the AI field in recent years: capturing the probability and distribution of data. We believe that this technology will contribute to performance improvements for AI, and we’re excited about the possibility of applying this knowledge to improve a variety of AI technologies.”