Yoshua Bengio, considered one of the 'Godfathers of Artificial Intelligence' discusses Recurrent independent mechanisms, sample complexity, end-to-end adaptation, multivariate categorical MLP conditionals and more.

When summarising his talk, Professor Bengio gave three key points to keep in mind when ‘looking forward’

- We must build a world model which meta-learns causal effects in abstract space of causal variables. This requires a necessity to quickly adapt to change and generalize out-of-distribution by sparsely recombining modules

- The necessity to acquire knowledge and encourage exploratory behaviour

- The need to bridge the gap between the aforementioned system 1 and system 2 ways of thinking, with old neural networks and consciousness reasoning taken into account