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Back in the 1980s, John Hopfield and Geoffrey Hinton set the stage for today's artificial intelligence by using physics to identify patterns in information.
早在20世纪80年代，约翰·霍普菲尔德和杰弗里·辛顿就利用物理学来识别信息中的模式，为今天的人工智能奠定了基础。
Their work now allows machines to mimic learning and remembering, functions that were previously thought to be the sole province of organic brains.
现在，他们的研究使机器能够模仿学习和记忆，而这些功能在以前被认为是生物大脑的专属领域。
At a tech conference last year, Hinton emphasized the differences are smaller than you might think.
在去年的一次科技会议上，辛顿强调，这种差异比你想象的要小得多。
"We're just a machine. We're a wonderful, incredibly complicated machine, but we're just a big neural net. And there's no reason why an artificial neural net shouldn't be able to do everything we can do."
“我们只是一台机器。我们是一台奇妙的、极其复杂的机器，但我们只是一个巨大的神经网络。没有理由说人工神经网络不能做我们能做的一切。”
Modern artificial neural networks are structured on the two recipients' groundbreaking ideas in the field of statistical physics.
现代人工神经网络是基于这两位获奖者在统计物理学领域的开创性思想建立的。
Their models allow machines to start making apparently intuitive leaps through association or identifying similar elements in systems like humans can.
他们的模型让机器开始像人类一样，通过联想或识别系统中的相似元素，实现明显的直觉飞跃。
That's radically changed, for instance, cancer diagnosis.
这从根本上改变了，例如，癌症诊断。
"You can train an artificial neural network on which are known to be tumors images that you know this is a problem, you train the network, and then it can become very fast and efficient at finding this in images.
“你可以通过一个已知是肿瘤的图像来训练人工神经网络，你知道这是个问题，你训练网络，然后它可以变得非常快速和有效地在图像中发现问题所在。
And it can work much more quickly or it assists the doctor and be much more certain in the diagnosis."
它可以更快地工作，或者帮助医生更确定诊断。”
And medical imaging is just one area where the research has had a huge impact.
医学成像只是该研究产生巨大影响的一个领域。
AI now also plays key roles in fields as diverse as large language models, particle physics, atmospheric and climate modeling, and predicting the structure of proteins.
如今，人工智能在大型语言模型、粒子物理、大气和气候建模以及预测蛋白质结构等领域也发挥着关键作用。
The Physics Prize this year goes for research that has changed and continues to change the world as we know it.
今年的诺贝尔物理学奖，属于这个已经、并将持续改变我们所知世界的研究。
