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Perceiver AR scales to 65k context length.is dramatically reduced for the same amount of attention.

ranging from text language output to optical flow fields to audiovisual sequences to symbolic unordered sets.which enhanced the output of Perceiver to accommodate more than just classification.long-context autoregressive model.

the same team of Andrew Jaegle and colleagues that built Perceiver.The original Perceiver in fact brought improved efficiency over Transformers by performing attention on a latent representation of input.

DeepMind and Google Brains Perceiver AR architecture reduces the task of computing the combinatorial nature of inputs and outputs into a latent space.

Experts in the field say computing tasks are destined to get bigger and biggest because scale matters.but if you need to collaborate in a workgroup.

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