"Why do we compute? The natural answer is: to gain information (which we did not previously have)!"

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• Information increase in computation arises from data reduction and making implicit information explicit, not logical increase.claim0.777
  Author's proposed resolution to the information increase paradox: computation gains utility through extraction and filtering, not creation of logically new content.
• Making information explicit—extracting normal forms from computation.claim0.767
• Computation is a game of empowerment and, therefore, the investment in opening the design process remains a critical challenge for contemporary architecture.claim0.760
  Final normative claim: computation’s nature as a game demands architectural openness, a challenge yet to be met.
• The process to design for is not stability or predictability, but promoting natural processesclaim0.760
  Key design philosophy of the talk, rejecting engineered stability in favor of dynamic, process-driven restoration.
• it creates a ‘we’; what we are doing, for example, whether our behaviours are coordinated or not, becomes a relevant variable.quote0.759
  Illustrates how non-separable functions shift identity to the collective level.
• "It is certainly very hard, and perhaps impossible, for mere humans to anticipate and rule out in advance all the disastrous ways the machine could choose to achieve a specified objective."quote0.753
  Russell's statement opening Section 2 articulating the core motivation for the Contemplative AI approach
• Much of the usefulness of computation lies in data reduction—removing the haystack to leave the needleclaim0.752
  Normal forms are exponentially large; computing them makes explicit only necessary information while discarding most input data, explaining apparent information increase.
• Why do human beings devote so much time and effort to the acquisition of knowledge?question0.749
  First of Berlyne's (1954) framing questions; answered by curiosity as expected free energy minimization (novelty)