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Scoop.it!
Yann LeCun, machine learning pioneer and head of AI at Meta, lays out a vision for AIs that learn about the world more like humans in a new study. 
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Scoop.it!
"I think we should think of AI as the intellectual equivalent of a backhoe. It will be much better than us at a lot of things" Artificial intelligence is a booming industry in 2019 with lots of new technological advancements.
Juliette Decugis's insight:
It blows my mind to think the most widely used deep learning models were developed a little less than 40 years ago. Transformers (2017) do seem to be missing on the deep learning timeline...
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In a talk at UC Berkeley this Tuesday, Yann LeCun, one of the founding fathers of deep learning, discussed approaches for more generalizable and autonomous AI.
Current deep learning frameworks require error training to learn very specific tasks and often fail to generalize to even out of distribution input on the same task. Specifically with reinforcement learning, we need a model to "fail" hundreds of times for it to start learning.
As a potential lead away from specialized AI, LeCun proposes a novel architecture composed of five sub-models mirroring the different parts of our brain. Specifically, one of the modules would ressemble memory as a “world model module”. Instead of each model learning a representation of the wold specific to their task, this framework would maintain a world model usable across tasks by different module.
See full paper: https://openreview.net/pdf?id=BZ5a1r-kVsf