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Iterated Amplification

Edited by Ben Pace, Bird Concept last updated 17th Jul 2020

Iterated Amplification is an approach to AI alignment, spearheaded by Paul Christiano. In this setup, we build powerful, aligned ML systems through a process of initially building weak aligned AIs, and recursively using each new AI to build a slightly smarter and still aligned AI. 

See also: Factored cognition. 

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Posts tagged Iterated Amplification
48Iterated Distillation and Amplification
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Ajeya Cotra
7y
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14
128Paul's research agenda FAQ
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zhukeepa
7y
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74
124Challenges to Christiano’s capability amplification proposal
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Eliezer Yudkowsky
7y
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54
75A guide to Iterated Amplification & Debate
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Rafael Harth
5y
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12
15HCH and Adversarial Questions
David Udell
4y
7
33AlphaGo Zero and capability amplification
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paulfchristiano
7y
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23
138Debate update: Obfuscated arguments problem
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Beth Barnes
5y
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24
120My Understanding of Paul Christiano's Iterated Amplification AI Safety Research Agenda
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Chi Nguyen
5y
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20
220An overview of 11 proposals for building safe advanced AI
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evhub
5y
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37
127My Overview of the AI Alignment Landscape: A Bird's Eye View
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Neel Nanda
4y
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9
103Writeup: Progress on AI Safety via Debate
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Beth Barnes, paulfchristiano
5y
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18
60Garrabrant and Shah on human modeling in AGI
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Rob Bensinger
4y
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10
60Prize for probable problems
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paulfchristiano
8y
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63
57Corrigibility
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paulfchristiano
7y
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8
45Factored Cognition
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stuhlmueller
7y
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6
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