Four short links: 6 February 2017
NPC AI, Deep Learning Math Proofs, Amazon Antitrust, and Code is Law
- Building Character AI Through Machine Learning — NPCs that learn from/imitate humans. (via Greg Borenstein)
- Network-Guided Proof Search — We give experimental evidence that with a hybrid, two-phase approach, deep-learning-based guidance can significantly reduce the average number of proof search steps while increasing the number of theorems proved.
- Amazon’s Antitrust Paradox — This Note maps out facets of Amazon’s dominance. Doing so enables us to make sense of its business strategy, illuminates anticompetitive aspects of Amazon’s structure and conduct, and underscores deficiencies in current doctrine. The Note closes by considering two potential regimes for addressing Amazon’s power: restoring traditional antitrust and competition policy principles or applying common carrier obligations and duties. Fascinating overview of the American conception of antitrust.
- FBI’s RAP-BACK Program — software encodes “guilty before trial.” employers enrolled in federal and state Rap Back programs receive ongoing, real-time notifications and updates about their employees’ run-ins with law enforcement, including arrests at protests and charges that do not end up in convictions.
