DeepMind Perceiver and Perceiver IO | Paper Explained @TheAIEpiphany
DeepMind Perceiver and Perceiver IO | Paper Explained  @TheAIEpiphany
Uploaded September 2021 | Updated September 2026, 1 week ago
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In this video I cover:
* Perceiver (Perceiver: General Perception with Iterative Attention)
* Perceiver IO (Perceiver IO: A General Architecture for Structured Inputs & Outputs)

The goal was to create a modality-agnostic, general perception architecture that could work on images, videos, audio, text, etc. alike.

The main idea is to use the cross-attention module as a bottleneck layer that will map the input modality data into the latent space - this way we avoid the quadratic curse of transformers. After that powerful latent transformers are used to refine the representation - rinse and repeat.

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βœ… Perceiver: arxiv.org/abs/2103.03206
βœ… Perceiver IO: arxiv.org/abs/2107.14795
βœ… Code: github.com/deepmind/deepmind-research/tree/master/perceiver
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⌚️ Timetable:
00:00 Intro
02:00 Perceiver architecture explained
05:40 Comparison with Facebook DETR model
07:05 Comparison to RNNs
08:35 Algorithmic complexity of Perceiver
10:35 Positional encodings and permutation equivariance
12:00 Results - ImageNet
14:35 Pixel permutation robustness
17:40 Attention visualized
20:20 Results - AudioSet
23:30 Results - Point Cloud
25:00 Perceiver IO
26:15 Decoder explained in depth (main contribution)
28:45 GLUE results (BERT baseline)
29:50 Outro

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#perceiver #perceiverio #deepmind
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DeepMind Perceiver and Perceiver IO | Paper Explained

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