The Myth of Artificial Intelligence
Why Computers Can’t Think the Way We Do
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Narrated by:
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Perry Daniels
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By:
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Erik J. Larson
About this listen
Futurists insist that AI will soon eclipse the capacities of the most gifted human mind. What hope do we have against superintelligent machines? But we aren't really on the path to developing intelligent machines. In fact, we don't even know where that path might be.
Erik Larson takes us on a tour of the landscape of AI to show how far we are from superintelligence and what it would take to get there. Ever since Alan Turing, AI enthusiasts have equated artificial intelligence with human intelligence. This is a profound mistake. AI works on inductive reasoning, crunching data sets to predict outcomes. But humans don't correlate data sets: We make conjectures informed by context and experience. Human intelligence is a web of best guesses, given what we know about the world. We haven't a clue how to program this kind of intuitive reasoning, known as abduction. Yet it is the heart of common sense. That's why Alexa can't understand what you are asking and why AI can only take us so far.
Larson argues that AI hype is both bad science and bad for science. A culture of invention thrives on exploring unknowns, not overselling existing methods. Inductive AI will continue to improve at narrow tasks, but if we want to make real progress, we will need to start by more fully appreciating the only true intelligence we know - our own.
©2021 Erik J. Larson (P)2021 TantorBalanced take without all the hype
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but the innocently ignorant conscious cognosentient being is not a global/ empirical collective consensus but a dogma driven hive when innovation seems conducive and lucrative to a hierarchy bereft of intelligence and reason.
A.I. Acute Ignorance unfolding.
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outdated and negative
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Hype versus realiteit: er is een groot verschil tussen wat AI-systemen kunnen doen en wat mensen denken dat ze al doen of gaan doen.
Mogelijk onderschatten van recente vooruitgang Sinds publicatie (2021) zijn er significante sprongen voorwaarts geweest, vooral met LLMs en multimodale modellen, mogelijk deels Larson’s kritiek verouderd.
Niet alles van wat men hoort over AI en AGI is feitelijk; veel zit in verwachtingen, mythes en analogieën.
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Talks about one AI unable to learn multiple tasks but deep mind used alpha zero algorithm for both go and chess.
Talks about not being able to pass the Turning test but chatgpt has done this.
Didn't gain anything useful from the book.
wrong
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