Friday, May 29, 2020
Waterloo-based Inductiv Inc., an AI start-up that uses machine learning to automate the task of identifying and correcting errors in data, has been bought by tech giant Apple.
Inductiv’s technology is based on HoloClean, an open-source statistical inference engine that uses artificial intelligence to identify and correct errors and omissions in data. This next generation of machine learning techniques to clean data began in 2017 as a collaborative academic project led by Cheriton School of Computer Science Professor Ihab Ilyas, and his colleagues Professors Theodoros Rekatsinas at the University of Wisconsin-Madison and Christopher Ré at Stanford University.
Ihab Ilyas is a professor in the Cheriton School of Computer Science’s Data Systems Group and the NSERC-Thomson Reuters Research Chair on data quality at the University of Waterloo. His main research focuses on the areas of big data and database systems, with special interest in data quality and integration, managing uncertain data, machine learning for data curation, and information extraction.
According to a recent report by Bloomberg, Apple’s purchase of Inductiv is the second such acquisition in as many months aimed at improving the data used in Siri, a virtual assistant that’s part of Apple’s operating systems for its range of devices from iPhones, iPads and Apple Watches to Macs and Apple TV.
Clean and accurate data are critical components for successful machine learning, a type of artificial intelligence that helps software improve with minimal human intervention. Inductiv’s technology automates the process of correcting errors in data, allowing insights to be gained from real-world data, which is often noisy, incomplete and erroneous.
Inductiv was cofounded in 2019 by Professor Ilyas, a faculty member of the Data Systems Group who also served as Inductiv’s CEO, along with his collaborators Professors Rekatsinas and Ré. Inductiv’s engineering team was Professor Ilyas’s graduate students Mina Farid, Omar Attia, Joshua McGrath and Ryan Clancy from the Cheriton School of Computer Science.
In a recent interview on CS-Can/Info-Can’s website about his approach to building systems based on problem-driven research, Professor Ilyas said that “working with industry gives us access to problems that nobody else has, data and resources we don’t have. And in a research setting, we can explore it quickly. It might be normal for a non-academic entrepreneur to solve problems, but it’s important for an academic to know they’re solving someone’s problem.”
The University of Waterloo’s generous intellectual property policy, where the invention belongs to its inventor, has been instrumental in fostering entrepreneurial spirit for start-ups to become established and flourish.
Professor Ilyas also cofounded Tamr, a start-up focusing on large-scale data integration and cleaning, based in Boston, Massachusetts. He holds the Thomson Reuters-funded Research Chair in Data Cleaning from Theory to Practice at the University of Waterloo. He’s a blogger with O’Reilly and Towards Data Science, and gives lectures at industrial and academic conferences.
