With the continued progress of AI technology in recent years, there has been greater deployment of AI in a variety of business fields. Despite demand for greater levels of automation, the most common means of creating AI models still involve painstaking, manual work by specialized AI engineers. Moreover, because the process of building new AI models continues to rely on trial and error, it demands significant man hours, often leading to delays in field deployment.
Leveraging proprietary time-series data analysis technology developed by Fujitsu Laboratories that utilizes improved topological data analysis (TDA)(1), Fujitsu and Inria project-team DataShape have now developed a new technology to automatically create AI models that can detect anomalies by extracting the necessary information from time-series data. Time-series data, which can include sensor data from IoT devices or biological data, such as heart rates and brain waves, consists of information of a wide range of types with complicated interconnections. This means that time-series data is often subject to severe volatility, making it difficult to discern when meaningful patterns or anomalies occur in the data.
This technology enables any software engineer to easily create AI categorization and anomaly detection models for time-series data, while also reducing the man hours required to one hundredth that of previous methods. This will ultimately help to accelerate the deployment of new AI models in a variety of business fields, allowing even engineers with no specialized training to create anomaly detection models.
This newly developed technology has been incorporated into GUDHI, an open source TDA library developed by Inria, and will be available for users globally for free from March 16. This will not only promote the use of AI in companies, research institutions, and other organizations--it will also enable the creation of AI models for a variety of use cases as feedback from those organizations is reflected in ongoing technology improvements. Fujitsu Laboratories will continue to refine this approach as one of the core technologies supporting its Fujitsu Human Centric AI Zinrai portfolio of solutions.
This technology will be presented at the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020), an international conference on machine learning that will be held in Palermo, Italy, from June 3-5.
