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Photo by Hyundai Motor Group on Unsplash When we learn from labeled data, we call it supervisedlearning. When we learn by grouping similar items, we call it clustering. When we learn by observing rewards or gains, we call it reinforcement learning.
Transformers made self-supervisedlearning possible, and AI jumped to warp speed,” said NVIDIA founder and CEO Jensen Huang in his keynote address this week at GTC. Transformers are in many cases replacing convolutional and recurrent neural networks (CNNs and RNNs), the most popular types of deep learning models just five years ago.
And in fact the big breakthrough in “deep learning” that occurred around 2011 was associated with the discovery that in some sense it can be easier to do (at least approximate) minimization when there are lots of weights involved than when there are fairly few. There’s the raw corpus of examples of language.
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