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Brett Winton: 人们自信地说神经网络将无法做到 X。 然而,在某些数据集大小/计算/模型深度阈值下,模型突然和出乎意料地证明了能力(在他们之前没有表现出任何趋势改进的事情上。)https://t.co/cekPpuLTa3 引用@_jasonwei 的推文: 新的调查报告!我们讨论大型语言模型的“紧急能力”。 新兴能力仅存在于足够大的模型中,因此无法简单地通过从较小模型中推断出比例曲线来预测它们。 arxiv.org/abs/2206.07682 ?⬇️ https://t.co/CNiExpxjD1

Posted on 2022-06-17

原推:People confidently state that neural nets will not be able to do X.

And yet at certain dataset-size/compute/model-depth thresholds models prove suddenly and unexpectedly capable (of things where they hadn’t shown any previous trend improvement.) https://t.co/cekPpuLTa3

Quoted tweet from @_jasonwei:

New survey paper! We discuss “emergent abilities” of large language models.

Emergent abilities are only present in sufficiently large models, and thus they would not have been predicted simply by extrapolating the scaling curve from smaller models.

arxiv.org/abs/2206.07682

?⬇️ https://t.co/CNiExpxjD1

https://twitter.com/wintonARK/status/1537487274350243840

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