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https://ai.stanford.edu/blog/longer-sequences-next-leap-ai

Can Longer Sequences Help Take the Next Leap in AI?

Deep learning has revolutionized machine learning. To a first approximation, deeper has been better. However, there is another dimension to scale these models: the size of the input. Even the world’s most impressive models can only process long-form content by dismembering it into isolated, disconnected chunks of a few hundred words to fit their length requirements.



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Can Longer Sequences Help Take the Next Leap in AI?

https://ai.stanford.edu/blog/longer-sequences-next-leap-ai

Deep learning has revolutionized machine learning. To a first approximation, deeper has been better. However, there is another dimension to scale these models: the size of the input. Even the world’s most impressive models can only process long-form content by dismembering it into isolated, disconnected chunks of a few hundred words to fit their length requirements.



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https://ai.stanford.edu/blog/longer-sequences-next-leap-ai

Can Longer Sequences Help Take the Next Leap in AI?

Deep learning has revolutionized machine learning. To a first approximation, deeper has been better. However, there is another dimension to scale these models: the size of the input. Even the world’s most impressive models can only process long-form content by dismembering it into isolated, disconnected chunks of a few hundred words to fit their length requirements.

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      Deep learning has revolutionized machine learning. To a first approximation, deeper has been better. However, there is another dimension to scale these models: the size of the input. Even the world’s most impressive models can only process long-form content by dismembering it into isolated, disconnected chunks of a few hundred words to fit their length requirements.
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      Can Longer Sequences Help Take the Next Leap in AI?
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      Why we think modeling longer sequences is exciting, and highlights of our recent work advancing this task.
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