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Complexity Explorers Krakow - Computer Science & Philosophy

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Inspiration for Complexity Explorers Krakow. The group is set up for learning and discussing anything related to an intersection of Philosophy and Computer Science.
We aim to explore a wide range of topics including Complexity Theory, Systems Thinking, Computability, Emergence, Physics, Analytical Philosophy.

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Complexity Explorers Krakow - Computer Science & Philosophy

  1. 1. Inspiration for the group Complexity Explorers Kraków Marcin Stępień @marcinstepien Kraków 2018-09-26
  2. 2. src: www.adamwalanus.pl/2016/chaitin/160519-1804-19.jpg
  3. 3. src: infoshare.pl/news/one,66,248,1,central-eastern-europe-developer-landscape-2017-a-report-by-stack-overflow.html 33K programmers in Kraków
  4. 4. Quantum Completeness Free Will Emergence Consciousness Kolmogorov complexity Computability Descarte’s teleology Causality
  5. 5. Complexity Algorithmic Information Theory Systems Theory Computational Complexity
  6. 6. Format
  7. 7. discoveries models simulations experiments physical/numerical/thought questions opinions statements influence >
  8. 8. Work of Kurt Gödel Alan Turing John Von Neumann Claude Elwood Shannon Marvin Minsky Andriej Kołmogorow Roger Penrose Daniel C. Dennett Gregory Chaitin Seth Lloyd Scott Aaronson Max Tegmark Stephen Wolfram Paul Davies Leonard Susskind ...
  9. 9. Examples Artificial Intelligence ❏ It takes Physics to explain why Deep Learning is so effective ❏ R. Penrose’s view on computability limits of AI ❏ Next generations of Turing Tests
  10. 10. Artificial Intelligence ❏ It takes Physics to explain why Deep Learning is so effective ❏ R. Penrose’s view on computability limits of AI ❏ Next generations of Turing Tests Computability ❏ How (not) to understand Gödel’s Incompleteness Theorems I & II ❏ What is uncomputable
  11. 11. Artificial Intelligence ❏ It takes Physics to explain why Deep Learning is so effective ❏ R. Penrose’s view on computability limits of AI ❏ Next generations of Turing Tests Computability ❏ How (not) to understand Gödel’s Incompleteness Theorems I & II ❏ What is uncomputable Algorithmic Information Theory ❏ Limited Complexity of Biology ❏ What causes the Complexity ❏ Omega number
  12. 12. Artificial Intelligence ❏ It takes Physics to explain why Deep Learning is so effective ❏ R. Penrose’s view on computability limits of AI ❏ Next generations of Turing Tests Computability ❏ How (not) to understand Gödel’s Incompleteness Theorems I & II ❏ What is uncomputable Computational Complexity ❏ Why Philosophers Should Care About Computational Complexity (S. Aronsson) Algorithmic Information Theory ❏ Limited Complexity of Biology ❏ What causes the Complexity ❏ Omega number
  13. 13. Algorithms & Creativity ❏ Busy Beaver
  14. 14. Algorithms & Creativity ❏ Busy Beaver Mathematical Creativity ❏ Is Mathematics mechanical or is it creative? ❏ Is Mathematics invented or discovered?
  15. 15. Algorithms & Creativity ❏ Busy Beaver Mathematical Creativity ❏ Is Mathematics mechanical or is it creative? ❏ Is Mathematics invented or discovered? Evolution, Emergence ❏ Competence without Comprehension (D. Dennett) ❏ How Descarte’s Teleology skewed our way of thinking ❏ Emergentism ❏ Reductionism vs Holism
  16. 16. Algorithms & Creativity ❏ Busy Beaver Mathematical Creativity ❏ Is Mathematics mechanical or is it creative? ❏ Is Mathematics invented or discovered? Evolution, Emergence ❏ Competence without Comprehension (D. Dennett) ❏ How Descarte’s Teleology skewed our way of thinking ❏ Emergentism ❏ Reductionism vs Holism
  17. 17. CS in Physics ❏ How much Information do we need to describe the Universe? ❏ Holographic principle as an compression algorithm ❏ Computational capacity of the Universe
  18. 18. CS in Physics ❏ How much Information do we need to describe the Universe? ❏ Holographic principle as an compression algorithm ❏ Computational capacity of the Universe Physics of Information ❏ Origins of Complexity in the Universe ❏ Is Information the foundation of Reality? ❏ Sources of information entropy ❏ Black Hole Information Paradox
  19. 19. Thank you

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