After the Nobel Prize in physics went to John J. Hopfield and Geoffrey E. Hinton "for foundational discoveries and inventions that enable machine learning with artificial neural networks", many asked why a prize for physics has gone to computer scientists for what is also an achievement in computer science. 在约翰·霍普菲尔德和杰弗里·辛顿因“为推动利用人工神经网络进行机器学习作出的基础性发现和发明”获得诺贝尔物理学奖后，许多人发问，为什么物理学奖授予了计算机学家，且其成就也属于计算机科学领域。 Even Hinton, a winner of the 2018 Turing Award and one of the "godfathers of AI", was himself "extremely surprised" at receiving the call telling him he had got the Nobel in physics, while the other recipient Hopfield said "It was just astounding." 就连2018年图灵奖得主、“人工智能教父”之一的辛顿，在接到瑞典皇家科学院的电话时，也直呼“没有想到”。另一位获奖者霍普菲尔德则说：“这简直令人震惊。” Actually, the artificial neural network research has a lot to do with physics. Most notably, Hopfield replicated the functioning of the human brain by using the self-rotation of single molecules as if they were neurons and linking them together into a network, which is what the famous Hopfield neural network is about. In the process, Hopfield used two physical equations. Similarly, Hinton made Hopfield's approach the basis for a more sophisticated artificial neural network called the Boltzmann machine, which can catch and correct computational errors.其实，人工神经网络研究与物理学有很大关系。最值得注意的是，霍普菲尔德利用单分子自旋复制了人脑的功能，把它们当作神经元，并把它们连接成一个网络，这就是著名的“霍普菲尔德神经网络”。在这个过程中，霍普菲尔德使用了两个物理方程。同样，辛顿将霍普菲尔德的方法作为一种更复杂的人工神经网络的基础，这种人工神经网络被称为玻尔兹曼机，它可以捕捉和纠正计算错误。 The two steps have helped in forming a net that can act like a human brain and compute. The neural networks today can learn from their own mistakes and constantly improve, thus being able to solve complicated problems for humanity. For example, the Large Language Model that's the basis of the various GPT technologies people use today dates back to the early days when Hopfield and Hinton formed and improved their network.这两项成果帮助形成了可以像人脑一样进行计算的网络。如今的神经网络可以从自己的错误中学习并不断改进，从而能够为人类解决复杂的问题。例如，作为当今人们使用的各种GPT技术基础的大语言模型，就可以追溯到早期霍普菲尔德和辛顿形成和改进人工神经网络的时候。 Instead of weakening the role of physics, that the Nobel Prize in Physics goes to neural network achievements strengthens it by revealing to the world the role physics, or fundamental science as a whole, plays in sharpening technology. Physics studies the rules followed by particles and the universe and paves the way for modern technologies. That is why there is much to thank physicists for the milestones modern computer science has crossed. 诺贝尔物理学奖授予神经网络成就，并不是削弱物理学的作用，而是通过向世界揭示物理学或整个基础科学在提高技术方面的作用来加强其地位。物理学研究粒子和宇宙所遵循的规则，并为现代技术铺平道路。这就是现代计算机科学所跨越的里程碑要感谢物理学家的原因。 neural adj. 神经的 astounding adj. 令人震惊的 replicate v. 复制，重复