Preview Mode Links will not work in preview mode

Fluidity

This is a nonfiction audiobook narrated by Matt Arnold with the permission of the author, David Chapman. Full text at: https://meaningness.com

You can support the podcast and get episodes a week early, by supporting the Patreon: https://www.patreon.com/m/fluidityaudiobooks

Original music by Kevin MacLeod. https://incompetech.com/music/

Artwork on this webpage is by Barry Gohn. https://www.deviantart.com/bzgbg

Search for "Fluidity" on Apple Podcasts, Spotify, Amazon Music, Deezer, Gaana, Player.FM, the Radio.com mobile app, and RadioPublic.

Oct 16, 2024

Few AI experiments constitute meaningful tests of hypotheses. As a branch of machine learning research, AI science has concentrated on black box investigation of training time phenomena. The best of this work is has been scientifically excellent. However, the hypotheses tested are mainly irrelevant to user and societal...


Sep 8, 2024

Do AI As Science And Engineering Instead - We’ve seen that current AI practice leads to technologies that are expensive, difficult to apply in real-world situations, and inherently unsafe. Neglected scientific and engineering investigations can bring better understanding of the risks of current AI technology, and...


Aug 25, 2024

Current AI results from experimental variation of mechanisms, unguided by theoretical principles. That has produced systems that can do amazing things. On the other hand, they are extremely error-prone and therefore unsafe. Backpropaganda, a collection of misleading ways of talking about “neural networks,”...


Aug 11, 2024

The conclusion of this chapter.
 
So-called “neural networks” are extremely expensive, poorly understood, unfixably unreliable, deceptive, data hungry, and inherently limited in capabilities. In short: they are bad. 


Sayash Kapoor and Arvind...


Jul 21, 2024

This begins "Gradient Dissent", the companion material to "Better Without AI". The neural network and GPT technologies that power current artificial intelligence are exceptionally error prone, deceptive, poorly understood, and dangerous. They are widely used without adequate safeguards in situations where they...