Introduction
Machine Learning (ML) applications are a prominent part of our daily lives, e.g. autonomous vehicles, customer service chatbots, or autocompletion features in our email clients. For the past decade, “deep learning” has captured the publics’ imagination and a great deal of Canadian institutional investment in ML. Yet, deep learning is not directly applicable in a wide variety of settings, and nobody really knows what is next “beyond deep learning” or how to get there. Our aim is to not only explore what deep learning and other prominent methodologies can do for us, but also to look into other novel methodologies that can take us “beyond deep learning”. By exploiting our intellectual diversity, the BDL consortium focuses on developing fundamentally new ML methodologies to solve key challenges in ML, and its applications.
Vision
The Beyond Deep Learning (BDL) Cosortium aims to be a high impact research and training network focused on AI and its applications collaborating closely with industry and academia Preparing us for what’s to come beyond deep learning
Current Activities
The Beyond Deep Learning program promotes the cross-pollination of ideas among students, faculty members and industry through a series of activities:
- Various reading groups focused on machine learning (industrial members are invited to join these discussions)
- Promotion of opportunities (from government, industry) to our community of faculty members, students and industry through communication tools such as slack and a mailing list
- Machine learning focused seminars
- Two network events per year to showcase research activities at UBC, and discuss areas of collaboration within the community (including a hackathon focused on industrial problems)
- Training workshops and activities organized throughout the year