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English(EN) Terence Tao @ tao : The math behind today’s LLMs is actually simple. Training and running them mostly uses linear algebra, matrix multiplication, and a bit of c

Terence Tao:大语言模型数学很简单,它们的成功才是谜团

著名数学家 Terence Tao 解释说,当前大语言模型 (LLMs) 的底层数学主要涉及线性代数和矩阵乘法,这些概念对本科生来说是容易理解的。他强调,真正的谜团不在于构建这些模型的机制,而在于理解为什么它们在不同任务上的表现会不可预测地变化。Tao 将这种不可预测性归因于现实世界数据的复杂性,这些数据部分结构化、部分随机,而当前的数学框架难以完全模拟。 AI

影响 解释了大语言模型简单的数学机制与其不可预测的涌现行为之间的差距。

排序理由 来自一位著名数学家的观点文章,讨论了大语言模型的理论基础和当前局限性。

在 Mastodon — fosstodon.org 阅读 →

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Terence Tao:大语言模型数学很简单,它们的成功才是谜团

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来自一位著名数学家的观点文章,讨论了大语言模型的理论基础和当前局限性。
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报道来源 [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    Terence Tao @ tao : 当今大语言模型的数学原理其实很简单。训练和运行它们主要使用线性代数、矩阵乘法以及一点点 c

    Terence Tao @ tao : The math behind today’s LLMs is actually simple. Training and running them mostly uses linear algebra, matrix multiplication, and a bit of calculus, material an undergraduate can handle. We understand how to build and operate these models. The real mystery is …