#3808

Mentioned in 10 episodes

Perceptrons

Book • 2017

Mentioned by

Anil Ananthaswamy

Stephen Wolfram

Mentioned in 10 episodes

Mentioned by Balaji Srinivasan in discussion of perceptrons and neural networks.

Balaji Srinivasan: The Network State

Mentioned by

Anil Ananthaswamy

as a book by Marvin Minsky and Seymour Papert that analyzed machines that learn.

336 | Anil Ananthaswamy on the Mathematics of Neural Nets and AI

Mentioned by Marvin Minsky and Seymour Papert to demonstrate that single-layer neural networks can only compute linear functions.

Babbage: The science that built the AI revolution—part one

Mentioned as a book that assessed the limitations of the perceptron.

Artificial Intelligence – Part One – Deus ex machina

Mentioned by

Ray Kurzweil

as a book he co-authored with Seymour Papert, discussing perceptrons and neural networks.

Season 4, Episode 9: Ray Kurzweil, The Singularity is Nearer: When We Merge with AI

Mentioned by

Rodney Brooks

while discussing the history of neural networks and the impact of this book.

#217 – Rodney Brooks: Robotics

Mentioned by

Pedro Domingos

as a book that criticized the Perceptron.

#248 Pedro Domingos: How Connectionism Is Reshaping the Future of Machine Learning

Mentioned by

Stephen Wolfram

as a book arguing that perceptrons and neural nets can't do anything interesting.

The AI Expert: "Super AI Will Be Unstoppable!"– What’s Coming NEXT _ Stephen Wolfram

Mentioned by

Fábio Akita

when discussing the history of AI and the limitations of perceptrons.

MENTIRAM PRA VOCÊ SOBRE INTELIGÊNCIA ARTIFICIAL

Mentioned by

Alex

when discussing the limitations of single-layer neural networks and its contribution to the first AI winter.

Decoding Dreams, China's AI Surge, and Amazon's Origin Story

Mentioned by

Yann LeCun

to highlight its theoretical arguments about the limitations of perceptrons.

WTF is Artificial Intelligence Really? | Yann LeCun x Nikhil Kamath | People by WTF Ep #4

Mentioned in reference to Minsky's and Rosenblatt's work on perceptrons and its impact on neural networks.

David Eliot, "Artificially Intelligent: The Very Human Story of AI" (Aevo UTP, 2025)

Mentioned by

Mukesh Bansal

as a book that mathematically proved neural networks cannot solve certain problems.

An Introduction to Artificial Intelligence (AI) for Beginners | SparX by Mukesh Bansal

Mentioned by

Trey Lockerbie

as a book that hindered the belief that neural networks had any merit.

TIP348: Will Artificial Intelligence Take Over The World? w/ Cade Metz

Mentioned as the book co-authored by Minsky and Papert that analyzed perceptrons and impacted neural network research.

Anil Ananthaswamy, "Why Machines Learn: The Elegant Maths Behind Modern AI" (Dutton, 2024)

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