Spike: The Virus vs. The People - the Inside Story provides a detailed account of the COVID-19 pandemic's early stages, focusing on the UK's response and the challenges faced by scientists and policymakers. The book offers insights into the scientific and political decisions made during the pandemic, questioning whether the UK government truly followed scientific advice. It also reflects on broader issues such as global health inequalities and the rapid development of vaccines.
This book by Douglas Hofstadter is a comprehensive and interdisciplinary work that explores the interrelated ideas of Kurt Gödel, M.C. Escher, and Johann Sebastian Bach. It delves into concepts such as self-reference, recursion, and the limits of formal systems, particularly through Gödel's Incompleteness Theorem. The book uses dialogues between fictional characters, including Achilles and the Tortoise, to intuitively present complex ideas before they are formally explained. It covers a wide range of topics including cognitive science, artificial intelligence, number theory, and the philosophy of mind, aiming to understand how consciousness and intelligence emerge from formal systems[2][4][5].
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Aran Nayebi is an Assistant Professor at Carnegie Mellon University in the Machine Learning Department. He was there in the early days of using convolutional neural networks to explain how our brains perform object recognition, and since then he's a had a whirlwind trajectory through different AI architectures and algorithms and how they relate to biological architectures and algorithms, so we touch on some of what he has studied in that regard. But he also recently started his own lab, at CMU, and he has plans to integrate much of what he has learned to eventually develop autonomous agents that perform the tasks we want them to perform in similar at least ways that our brains perform them. So we discuss his ongoing plans to reverse-engineer our intelligence to build useful cognitive architectures of that sort.
We also discuss Aran's suggestion that, at least in the NeuroAI world, the Turing test needs to be updated to include some measure of similarity of the internal representations used to achieve the various tasks the models perform. By internal representations, as we discuss, he means the population-level activity in the neural networks, not the mental representations philosophy of mind often refers to, or other philosophical notions of the term representation.
0:00 - Intro
5:24 - Background
20:46 - Building embodied agents
33:00 - Adaptability
49:25 - Marr's levels
54:12 - Sensorimotor loop and intrinsic goals
1:00:05 - NeuroAI Turing Test
1:18:18 - Representations
1:28:18 - How to know what to measure
1:32:56 - AI safety
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