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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?
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?
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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11- titleCan Longer Sequences Help Take the Next Leap in AI? | SAIL Blog
- titleCan Longer Sequences Help Take the Next Leap in AI? | The Stanford AI Lab Blog
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en_US- og:descriptionDeep 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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- twitter:titleCan Longer Sequences Help Take the Next Leap in AI?
- twitter:descriptionWhy we think modeling longer sequences is exciting, and highlights of our recent work advancing this task.
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