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Nature of AI

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

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AI Control

Examples of early action on risks

Details Discussion There are many current efforts to mitigate risks from artificial intelligence. We might learn something about the likelihood of these efforts influencing AI risk by looking at similar past efforts. To this end, we are interested here

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Selected Citations

This page is a non-exhaustive collection of places where AI Impacts’ work has been cited. AI Timelines Muehlhauser, Luke. 2015. “What Do We Know about AI Timelines?” Open Philanthropy Project. (archive) Muehlhauser, Luke. 2015. “What should we


Error in Armstrong and Sotala 2012

Can AI researchers say anything useful about when strong AI will arrive? Back in 2012, Stuart Armstrong and Kaj Sotala weighed in on this question in a paper called ‘How We’re Predicting AI—or Failing To‘. They looked


Metasurvey: predict the predictors

As I mentioned earlier, we’ve been making a survey for AI researchers. The survey asks when AI will be able to do things like build a lego kit according to the instructions, be a surgeon, or radically accelerate global technological development. It also asks


Concrete AI tasks bleg

We’re making a survey. I hope to write soon about our general methods and plans, so anyone kind enough to criticize them has the chance. Before that though, we have a different request: we want a list of concrete tasks that AI can’t do yet,


Mysteries of global hardware

This blog post summarizes recent research on our Global Computing Capacity page. See that page for full citations and detailed reasoning. We recently investigated this intriguing puzzle: FLOPS (then) apparently performed by all of the world’s computing hardware: 3 x 1022 – 3

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AI Timelines

Global computing capacity

Computing capacity worldwide was probably around 2 x 1020 – 1.5 x 1021 FLOPS, at around the end of 2015. Support We are not aware of recent, plausible estimates for hardware capacity. Vipul Naik estimated global hardware capacity in February


Recently at AI Impacts

We’ve been working on a few longer term projects lately, so here’s an update in the absence of regular page additions. New researchers Stephanie Zolayvar and John Salvatier have recently joined us, to try out research here. Stephanie

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Featured Articles

AI Risk Terminology

AI timeline – an expectation about how much time will lapse before important AI events, especially the advent of human-level AI or a similar milestone. The term can also refer to the actual periods of time (which are not yet