Will AI Ever Understand Language Like Humans?

The Joy of Why

Steven Strogatz, Janna Levin and Quanta Magazine

Science, Life Sciences

4.9 • 577 Ratings

🗓️ 1 May 2025

⏱️ 42 minutes

🔗️ Recording | iTunes | RSS

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Summary

Large language models (LLMs) are becoming increasingly more impressive at creating human-like text and answering questions, but whether they can understand the meaning of the words they generate is a hotly debated issue. A big challenge is that LLMs are black boxes; they can make predictions and decisions on the order of words, but they cannot communicate the reasons for doing so.

Ellie Pavlick at Brown University is building models that could help understand how LLMs process language compared with humans. In this episode of The Joy of Why, Pavlick discusses what we know and don’t know about LLM language processing, how their processes differ from humans, and how understanding LLMs better could also help us better appreciate our own capacity for knowledge and creativity.

Transcript

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0:00.0	I'm Jana Levin.
0:06.0	And I'm Steve Strogetz.
0:08.0	And this is The Joy of Why, a podcast from Quantum Magazine, exploring some of the biggest
0:13.4	unanswered questions in math and science today.
0:19.7	Steve, hi.
0:20.7	Hey, hi.
0:22.3	Hey, Jana. How's it going?
0:28.7	Good. I wanted to tell you about this conversation I had about AI and large language models.
0:29.3	Okay.
0:32.6	Have you been thinking about AI a lot right now? Is it on your mind?
0:37.1	Sure. It can't resist. It's fun playing with it. And now my interest is piqued. Well, it's interesting because
0:38.1	Quanta actually just published a whole series of articles about AI to kind of fill in some of the
0:42.7	blanks that are out there in the conversation, right? Because we're kind of going over the same
0:45.7	material a lot. Will they replace our jobs? And what does it mean for creative fields? But there's
0:50.5	this almost neuroscience of AI.
0:58.2	How do you understand what your AI is doing?
1:00.9	And that really surprised me.
1:03.7	You would think, well, you built the thing.
1:06.6	How come you don't know what it's doing?
1:08.6	But that's kind of like saying I had a child.
1:12.8	That doesn't mean you have transparency into their mind.
1:18.1	Right. This feels like a real frontier question because we keep hearing AI's referred to as black boxes.
	...

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