是不是没隐私了？  
  
【 在 chongmingle (北大青鸟) 的大作中提到: 】
:  新版本的windows已经搭载copilot，以后AI能力决定了系统的好用程度，关键是大模型进化速度太快了，大量学习用户的操作行为会越来越好用，苹果最强的护城河操作系统要被AI攻破了。。。
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FROM 61.135.30.*

这好像是google的护城河
要打败apple就要打败iPhone，那就不是一个简单的AI就能解决的

【 在 chongmingle 的大作中提到: 】
: 新版本的windows已经搭载copilot，以后AI能力决定了系统的好用程度，关键是大模型进化速度太快了，大量学习用户的操作行为会越来越好用，苹果最强的护城河操作系统要被AI攻破了。。。
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FROM 222.129.7.*

每次问siri导航到某个地址，siri总要确认一下您要找的是xxxx吗？我说是，就去那里。siri又问：去哪里？  气煞我也，简直是智障
  
【 在 chongmingle (北大青鸟) 的大作中提到: 】
:  新版本的windows已经搭载copilot，以后AI能力决定了系统的好用程度，关键是大模型进化速度太快了，大量学习用户的操作行为会越来越好用，苹果最强的护城河操作系统要被AI攻破了。。。
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FROM 180.138.111.*

Apple's neural engine and Nvidia's Tensor Cores are both designed to accelerate AI workloads, but they work in different ways and are optimized for different types of tasks.

Apple's neural engine is a dedicated block of hardware within the M series chips that is specifically designed to accelerate machine learning tasks on Apple devices. It uses Apple's own machine learning frameworks and libraries to perform tasks such as image recognition, natural language processing, and other AI-related tasks.

Nvidia's Tensor Cores, on the other hand, are specialized hardware units within Nvidia's GPUs that are designed to perform matrix operations, which are a fundamental building block of many AI and deep learning algorithms. Tensor Cores can accelerate these operations by performing many calculations in parallel, allowing for faster training and inference of AI models.

In summary, while both Apple's neural engine and Nvidia's Tensor Cores are designed to accelerate AI workloads, they work in different ways and are optimized for different types of tasks. Is there anything else you would like to know?

看上去基本上是一样的，估计是算力上的差别，软件层面上也有不同。

【 在 beaver 的大作中提到: 】
: 问个问题，苹果的芯片号称什么智能单元，那个处理器，跟黄仁勋的用于人工智能的芯片的主要区别是什么？
: 都说是智能智能的，是一回事么？
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FROM 222.129.7.*

是的

【 在 beaver 的大作中提到: 】
: 额，这是AI回答我的么
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FROM 222.129.7.*