Next Word Prediction Is More Complex Than You Think

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In order to do next word prediction, you might have to acquire quite sophisticated capacities that you might not fully grasp by just focusing on the next word prediction learning objective. It's more complicated because what we mean when we bring in the terms intelligence and consciousness is these are very loaded, complicated, multifaceted terms. So having this nuanced middle view between an inflationary interpretation of what these moles can do and the deflationary idea that they only do an expert prediction and nothing else is very tricky.

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.

[The above introduction was artificially generated by ChatGPT.]

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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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