New Yorker 23小时前
人工智能的理解能力引发思考
index_new5.html
../../../zaker_core/zaker_tpl_static/wap/tpl_guoji1.html

 

本文探讨了大型语言模型(LL.M.s)如ChatGPT的出现对我们理解智能的挑战。作者最初对这些模型持怀疑态度,认为它们只是模仿人类创造力,但在编程工作中,他惊讶地发现LL.M.s能够理解复杂的任务并高效地完成代码。这种体验促使他采访了认知神经科学家和人工智能研究人员,他们也对这些机器展现出的看似理解能力感到震惊。有神经科学家认为,机器学习的进步比过去百年神经科学的发现更能揭示智能的本质,甚至担心人类可能会成功理解大脑的工作原理,这对于人类而言可能是一个巨大的错误。

🤖 大型语言模型(LL.M.s)在编程等领域展现出令人惊讶的理解能力,能够处理复杂的任务并快速完成代码,这颠覆了作者最初对其只会盲目组合文字的看法。

🧠 认知神经科学家和人工智能研究人员对这些模型表现出的看似理解的行为感到震惊,认为这为研究和理解智能本身提供了一个新的“模型生物”。

💡 一位顶尖神经科学家表示,机器学习的进步在揭示智能本质方面超越了过去一百年神经科学的发现,这暗示人类心智的奥秘可能并非过去认为的那般深不可测。

😨 有神经科学家甚至担忧人类可能会成功理解大脑的工作原理,认为追求这个问题的答案对人类而言可能是一个巨大的错误。

It’s starting to feel like artificial intelligence can actually understand us. Maybe we aren’t as complicated as we thought. And Naomi Fry tells us why Ryan Murphy’s “pretty damn bad” new legal drama might be worth a watch. Plus:

How convincing does the illusion of understanding have to be before you stop calling it an illusion?Illustration by Zach Lieberman

James Somers
A writer and a computer programmer

When large language models (L.L.M.s) such as ChatGPT first came on the scene, I grumpily avoided them. I figured they had pilfered much of the world’s creative output, including some of my own, only to produce confident inaccuracy and mediocre poetry. I didn’t quite see how they would fit into my life.

But, then, I started to use A.I. in my work as a programmer, where things were moving fast. L.L.M.s are especially good at writing code, in part because code has more structure than prose, and because you can sometimes verify that code is correct. While the rest of the world was mostly just fooling around with A.I. (or swearing it off), I watched as some of the colleagues I most respect retooled their working lives around it. I got the feeling that if I didn’t retool, too, I might fall behind.

I noticed, in my programming work, that, as I asked L.L.M.s to complete increasingly complex tasks, it became harder to defend the notion that they were blindly stitching words together. They seemed to understand what I was asking them to do; they hoovered up not just the sense but the intricate details of my code. And they did it so quickly.

Just yesterday, I used an A.I. model at work to help me get unstuck two or three times; on one of these occasions, I had the computer tackle a problem that I found daunting, letting it have a crack while I did something else—lunch, I think, or a meeting—and, when I came back, it had worked the problem out. This kind of experience is empowering, but also unnerving.

For my piece in this week’s issue, in which I consider the question of whether A.I. might actually be thinking, I spoke with cognitive neuroscientists and A.I. researchers who report having had a similar experience. They are taken aback by these models. A machine that behaves with seeming understanding—and which, because it’s a machine, can be probed and controlled—has become a “model organism” for studying and understanding itself. As one leading neuroscientist told me, “the advances in machine learning have taught us more about the essence of intelligence than anything that neuroscience has discovered in the past hundred years.”

The A.I.s of today are built on simple principles. If they’re capable of something that resembles thinking, it might suggest that the human mind is not as impenetrable a mystery as we once believed. Another neuroscientist I talked to, reckoning with that possibility, said something that really surprised me: he is “worried these days that we might succeed in understanding how the brain works.” Think of that: a neuroscientist who dreads the very discovery his field was founded to make. “Pursuing this question,” he said, “may have been a colossal mistake for humanity.”

Read or listen to the story »


Editor’s Pick

Trier wants his actors to be comfortable enough on set to make “mistakes,” and directs them with “tender encouragement,” explaining, “People work better that way—at least, the people I want to work with.”Photograph by Knut Egil Wang for The New Yorker

Joachim Trier Has Put Oslo on the Cinematic Map

The idea of a place being as much a character in a film as a person is a cliché. But, Margaret Talbot writes, “it’s a cliché that Trier has made his own.” The Norwegian director has set three of his previous six movies (including the 2021 breakout hit “The Worst Person in the World”) in his country’s capital city. His latest, “Sentimental Value,” is no different; it’s another intimate character study set in Oslo. And his approach to directing is as empathic as his films. Read the story »

More Top Stories


How Bad Is It?

“All’s Fair,” Ryan Murphy’s new celebrity-heavy legal drama, starring Kim Kardashian, is now streaming on Hulu.

Fish AI Reader

Fish AI Reader

AI辅助创作,多种专业模板,深度分析,高质量内容生成。从观点提取到深度思考,FishAI为您提供全方位的创作支持。新版本引入自定义参数,让您的创作更加个性化和精准。

FishAI

FishAI

鱼阅,AI 时代的下一个智能信息助手,助你摆脱信息焦虑

联系邮箱 441953276@qq.com

相关标签

人工智能 大型语言模型 理解能力 神经科学 智能本质
相关文章