TBNAI
Why Leibniz Couldn't Find the Mind Inside the Mill (Joscha Bach)
Publication: Machine Learning Street Talk (MLST)
Author: Machine Learning Street Talk (MLST)
Source published: 02/11/2026, 04:43:47 UTC
Briefing created: 02/11/2026, 06:30:37 UTC
Based on the episode description, not a full transcript. Source evidence retrieved 02/11/2026, 04:58:24 UTC.
Briefings
Joscha Bach argues consciousness is a biological learning algorithm, proposing machines could discover it via self-organizing learning. He critiques Leibniz's mill for its explanatory gap and challenges the idea of a Turing test, citing Gödel's limits on formal systems. The episode explores whether minds and consciousness converge, referencing Anil Seth's biological naturalism and Michael Levin's morphogenesis theory.
Key points
- Bach proposes consciousness is a biological learning algorithm, suggesting machines might discover it through self-organizing learning processes.
- The episode challenges the existence of a Turing test for consciousness and questions whether minds and consciousness converge, citing Gödel's limits on formal systems.
Context
This podcast explores the Machine Consciousness Hypothesis, contrasting it with traditional views like Leibniz's mill and Anil Seth's biological naturalism. It addresses the explanatory gap between mind and machine and the limits of formal systems.
Limitations
Evidence is limited to the podcast transcript and cited references. Specific dates for the podcast episode are not provided, and the research program's full scope is not fully detailed in the source.
Generated by Bittrees-hosted qwen35-2b sha256:aaf42c8b7c3c on 02/11/2026, 06:30:37 UTC. Based on publisher-provided feed evidence; may not cover the full original article. Check the source for details.
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