Search Results for “human range” – Page 7

2016 Expert Survey on Progress in AI

Published June 2016; last substantial update before Oct 2017 The 2016 Expert Survey on Progress in AI is a survey of machine learning researchers that Katja Grace and John Salvatier of AI Impacts ran in

Conversation with Tom Griffiths

Participants Professor Tom Griffiths, Director of the Computational Cognitive Science Lab and the Institute of Cognitive and Brain Sciences at the University of California, Berkeley. Finan Adamson, AI Impacts. Note: These notes were

What if you turned the world’s hardware into AI minds?

By Katja Grace, 4 September 2016 In a classic ‘AI takes over the world’ scenario, one of the first things an emerging superintelligence wants to do is steal most of the world’s computing hardware and repurpose it to running the AI’s

Sources of advantage for digital agents over biological agents

Artificial agents should have several advantages over humans. Details The following is an excerpt from Superintelligence (Bostrom, 2014), reproduced with permission. It outlines ten advantages Bostrom expects digital intelligences to have over human intelligences. Sources of advantage for digital intelligence Minor

Friendly AI as a global public good

By Katja Grace, 8 August 2016 A public good, in the economic sense, can be (roughly) characterized as a desirable good that is likely to be undersupplied, or not supplied at all, by private companies.

Costs of extinction risk mitigation

We very roughly estimate that the annual cost of reducing the probability of human extinction by 0.01% is within the range of $1.1 billion to $3.5 trillion. Introduction This article is intended to be usable

Returns to scale in research

When universities or university departments produce research outputs—such as published papers—they sometimes experience increasing returns to scale, sometimes constant returns to scale, and sometimes decreasing returns to scale. At the level of nations however, R&D

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Search Results for human range