Apple has acquired machine-learning startup Inductiv to improve its Siri voice assistant, reports Bloomberg.
The engineering team from Waterloo, Ontario-based Inductiv joined Apple in recent weeks to work on Siri, machine learning and data science. Apple confirmed the deal, saying it “buys smaller technology companies from time to time and we generally do not discuss our purpose or plans.”
Infocan reports that Inductiv was started in 2019 by University of Waterloo professor Ihab Ilyas and some of his students, Theodoros Rekatsinas at the University of Wisconsin and Christopher Ré at Stanford University.
Inductiv makes use of a new wave of a modern machine learning platform for predictions on structured data. The team recognized a market gap beyond data integration and beyond data quality – the ability to understand how structured data is generated and scalable engines that can abstract much of it at once. The new methods abstract most data problems as predictions on structured data, including cleaning, missing value imputation, error detection and prediction.
Using AI, Inductiv is able to identify and correct errors in data. This is important for machine learning and improving software with less human intervention.
More details in the full report linked below.
Read More
The engineering team from Waterloo, Ontario-based Inductiv joined Apple in recent weeks to work on Siri, machine learning and data science. Apple confirmed the deal, saying it “buys smaller technology companies from time to time and we generally do not discuss our purpose or plans.”
Infocan reports that Inductiv was started in 2019 by University of Waterloo professor Ihab Ilyas and some of his students, Theodoros Rekatsinas at the University of Wisconsin and Christopher Ré at Stanford University.
Inductiv makes use of a new wave of a modern machine learning platform for predictions on structured data. The team recognized a market gap beyond data integration and beyond data quality – the ability to understand how structured data is generated and scalable engines that can abstract much of it at once. The new methods abstract most data problems as predictions on structured data, including cleaning, missing value imputation, error detection and prediction.
Using AI, Inductiv is able to identify and correct errors in data. This is important for machine learning and improving software with less human intervention.
More details in the full report linked below.
Read More