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Larry Page's 2007 prediction that AI would rely on massive computation rather than clever algorithms, comparing DNA to 600MB of compressed data.
Stephen Wolfram visits the archive of Gottfried Leibniz, exploring his notes and connecting Leibniz's 17th-century ideas about systematization of knowledge to modern computational concepts like Mathematica and Wolfram|Alpha.
This paper introduces state commitment learning, a training objective that teaches language models to distinguish temporary computation tokens from persistent state tokens. The authors propose Counterfactual Erasure RL (CERL) and the Erasure Dependence Protocol, showing improvements across math, logic, science QA, and tool-use tasks without sacrificing accuracy.
This article provides a proof that Jira's automation features are Turing-complete by implementing a Minsky register machine using Jira issues and automation rules.