The Philosophy of Machine Thinking: From Turing to Modern LLMs
By
mapehe
If you only eat one bagel today, this is the bagel.
Summary
The article explores the philosophical question of whether machines can truly think, tracing the debate back to foundational thinkers like Alan Turing, John von Neumann, and Claude Shannon in the 1950s. It examines how large language models (LLMs) operate through bottom-up pattern recognition rather than human-like top-down reasoning, arguing that while they mimic understanding, they don't truly think like humans. The piece positions AI as a tool for human-AI collaboration rather than replacement, emphasizing that the future lies in leveraging AI's capabilities while recognizing its fundamental differences from human cognition.
Key quotes
· 4 pulledI propose to consider the question, 'Can machines think?'
chess is generally considered to require 'thinking' for skilful play; a solution of this problem will force us either to admit
LLMs mimic understanding but think bottom-up, unlike humans
the future is human–AI collaboration, not replacement
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