Published posthumously in 1953, 'Philosophical Investigations' is a seminal work by Ludwig Wittgenstein that challenges many of the ideas presented in his earlier work, 'Tractatus Logico-Philosophicus'. The book is divided into two parts and consists of short observations or 'remarks' that delve into topics such as the theory of language, language games, meaning, symbols, concepts, and categories. Wittgenstein argues that the meaning of a word is derived from its use within the context of a language-game, rejecting the idea that words gain meaning by referencing objects or mental representations. He emphasizes the importance of understanding language as a tool for communication and social interaction, rather than as a system for representing objective reality[2][4][5].
In 'So You've Been Publicly Shamed', Jon Ronson delves into the phenomenon of online shaming and its historical antecedents. The book features interviews with individuals who have been subjected to intense public shaming, including Jonah Lehrer, a journalist who plagiarized quotes, and a woman who was shamed for a tweet at an airport. Ronson also speaks with practitioners of modern public humiliation and examines the immediate and long-term consequences of such shaming. The book raises questions about righteousness, reputation, and conformity in the context of social media and its impact on individuals and society[2][3][4].
Sir Arthur Eddington's "The Philosophy of Physical Science" is a classic work exploring the relationship between physics and philosophy. Eddington delves into the fundamental concepts of physics, examining the nature of space, time, and causality. He challenges traditional interpretations of scientific knowledge, emphasizing the role of observation and the limitations of human perception. Eddington's work is known for its insightful discussions on the nature of scientific laws and their relationship to reality. He explores the philosophical implications of relativity and quantum mechanics, offering a unique perspective on the nature of the universe. The book remains a significant contribution to the philosophy of science, inspiring further discussions on the limits of scientific knowledge and the role of interpretation in scientific understanding.
Please note that in this interview Dr. Lampinen was expressing his personal opinions and they do not necessarily represent those of DeepMind.
Patreon: https://www.patreon.com/mlst
Discord: https://discord.gg/ESrGqhf5CB
YT version: https://youtu.be/yPMtSXXn4OY
Dr. Andrew Lampinen is a Senior Research Scientist at DeepMind, and he thinks that symbols are subjective in the relativistic sense. Dr. Lampinen completed his PhD in Cognitive Psychology at Stanford University. His background is in mathematics, physics, and machine learning. Andrew has said that his research interests are in cognitive flexibililty and generalization, and how these abilities are enabled by factors like language, memory, and embodiment. Andrew with his coauthors has just released a paper called symbolic behaviour in artificial intelligence. Andrew lead in the paper by saying the human ability to use symbols has yet to be replicated in machines. He thinks that one of the key areas to bridge the gap here is considering how symbol meaning is established, and he strongly believes it is the symbol users themselves who agree upon the symbol meaning, And that the use of symbols entails behaviours which coalesce agreements about their meaning. Which in plain English means that symbols are defined by behaviours rather than their content.
[00:00:00] Intro to Andrew and Symbolic Behaviour paper
[00:07:01] Semantics underpins the unreasonable effectiveness of symbols
[00:12:56] The Depth of Subjectivity
[00:21:03] Walid Saba - universal cognitive templates
[00:27:47] Insufficiently Darwinian
[00:30:52] Discovered vs invented
[00:34:19] Does language have primacy
[00:35:59] Research directions
[00:39:43] Comparison to BenG OpenCog and human compatible AI
[00:42:53] Aligning AI with our culture
[00:47:55] Do we need to model the worst aspects of human behaviour?
[00:50:57] Fairness
[00:54:24] Memorisatation on LLMs
[01:00:38] Wason selection task
[01:03:45] Would an Andrew hashtable robot be intelligent?
Dr. Andrew Lampinen
https://lampinen.github.io/
https://twitter.com/AndrewLampinen
Symbolic Behaviour in Artificial Intelligence
https://arxiv.org/abs/2102.03406
Imitating Interactive Intelligence
https://arxiv.org/abs/2012.05672
https://www.deepmind.com/publications/imitating-interactive-intelligence
Impact of Pretraining Term Frequencies on Few-Shot Reasoning [Yasaman Razeghi]
https://arxiv.org/abs/2202.07206
Big bench dataset
https://github.com/google/BIG-bench
Teaching Autoregressive Language Models Complex Tasks By Demonstration [Recchia]
https://arxiv.org/pdf/2109.02102.pdf
Wason selection task
https://en.wikipedia.org/wiki/Wason_selection_task
Gary Lupyan
https://psych.wisc.edu/staff/lupyan-gary/
Machine Learning Street Talk (MLST) 
