4.8 • 4.4K Ratings
🗓️ 20 March 2023
⏱️ 118 minutes
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Welcome to another episode of Sean Carroll's Mindscape. Today, we're joined by Raphaël Millière, a philosopher and cognitive scientist at Columbia University. We'll be exploring the fascinating topic of how artificial intelligence thinks and processes information. As AI becomes increasingly prevalent in our daily lives, it's important to understand the mechanisms behind its decision-making processes. What are the algorithms and models that underpin AI, and how do they differ from human thought processes? How do machines learn from data, and what are the limitations of this learning? These are just some of the questions we'll be exploring in this episode. Raphaël will be sharing insights from his work in cognitive science, and discussing the latest developments in this rapidly evolving field. So join us as we dive into the mind of artificial intelligence and explore how it thinks.
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Raphaël Millière received a DPhil in philosophy from the University of Oxford. He is currently a Presidential Scholar in Society and Neuroscience at the Center for Science and Society, and a Lecturer in the Philosophy Department at Columbia University. He also writes and organizes events aimed at a broader audience, including a recent workshop on The Challenge of Compositionality for Artificial Intelligence.
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0:00.0 | Hello, everyone. Welcome to the Mindscape podcast. I'm your host, Sean Carroll. You may have noticed artificial intelligence is in the news these days. |
0:08.6 | AI has something has been around for a long time. Been very popular as a pursuit since the 1960s. |
0:14.4 | We've seen a blowing up of progress in this field. There's a whole bunch of jargon that gets thrown around, right? |
0:22.2 | Deep learning, machine learning, neural networks, these days, stable diffusion algorithms for vision. |
0:29.2 | Image recognition systems. And especially a lot of interest has been recently focused on large language models. |
0:37.2 | Basically in practice, they're like super chatbots, right? You can open up a dialogue and you can talk to the large language model. |
0:46.2 | You can ask it questions. And they're amazingly effective at sounding human and giving information. |
0:53.2 | As I said recently in an Ask Me Anything episode, they're not perfect. You know that someone asked about me and the large language model. |
1:02.2 | I forgot which one it was, but there's chat GPT most recently GPT for and a bunch of competitors there from Bing, Google and so forth. |
1:10.2 | But anyway, this one sort of got very basic facts about me in my life hilariously wrong as a factual error. |
1:17.2 | Okay, that's something that maybe can be fixed, right? Maybe you just train the model and it gets better and better and eventually the factual errors go away. |
1:26.2 | What seems to be clear is that the progress has been very rapid and the changes that will come from this will be profound. |
1:35.2 | So there's many questions to ask. There's the question about how does it all work? There's the questions, how will this affect society? What use will we get out of these AI programs? |
1:46.2 | What are the dangers that are there that come along with super intelligent artificial intelligence? |
1:53.2 | But there's also the question of how much thinking and understanding is really going on. |
2:00.2 | The almost philosophical question of when will we get to the point where something that we think of as an AI program, a large language model, is truly thinking. |
2:11.2 | Is truly sentient if you want to put it that way, even conscious, conscious, right? |
2:17.2 | And probably the answer is it depends. It depends on exactly what you mean by that, how to operationalize it and so forth. |
2:25.2 | But that's what we're going to be talking about today, you know, less on those other questions I talked about and more on to what extent are AI's thinking, sentient. |
2:37.2 | What does it mean even to ask those questions? Our guest is Rafael Millier, who is trained as a philosopher, is a scholar in society and neuroscience at Columbia. |
2:47.2 | And he thinks about the philosophy of artificial intelligence, cognitive science and mind in a very knowledgeable way. |
2:55.2 | He's not just saying, well, you know, AI could be this could be this. He knows what a large language model is and how it works. |
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