While true Artificial General Intelligence is still far away, in the short term we can augment machine learning with ‘general’ capabilities and features. Unlike most AI/ML, general intelligence should not require tailoring to specific problems. Instead, it learns continuously from interactions with a world, developing an internal representation by exploring and exploiting what it already knows. Algorithms with general intelligence features are applicable to a wider range of problems and tasks.
June 2019: PhD candidate Shuai begins an APR internship with us to deliver a Proof of Concept with Melbourne Health.
Mar 2019: Recruiting a recent Australian PhD grad., or candidate, for paid internship in ML for healthcare. Read more
Feb 2019: Co-supervising a Masters project (Self-organising neural architectures) with the Faculty of IT at Monash University