AI Takeoff

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Deku-shrub (-13) /* Soft takeoff */
Deku-shrub (+43/-2) /* Hard takeoff */
Deku-shrub (+84/-2) /* Soft takeoff */
Deku-shrub (+7/-6) /* Soft takeoff */

The feasibility of hard takeoff has been addressed by Hugo de Garis, Eliezer Yudkowsky, Ben Goertzel, Nick Bostrom, and Michael Anissimov. It is widely agreed that a hard takeoff is something to be avoided due to the risks. Yudkowsky points out several possibilities that would make a hard takeoff more likely than a soft takeoff such as the existence of large resources overhangs or the fact that small improvements seem to have a large impact in a mind's general intelligence (i.e.: the small genetic difference between humans and chimps lead to huge increases in capability). [3].

AI Takeoff refers to the process of an artificial general intelligenceArtificial General Intelligence going from a certain threshold of capability (often discussed as "human human-level") to being super-intelligent and capable enough to control the fate of civilization.

There has been much debate about whether AI takeoff is more likely to be slow vs fast, i.e., "slowsoft" orvs "fasthard".

See also: AI Timelines, Seed AI, Singularity, Intelligence explosion, Recursive self-improvement

Soft takeoff

A soft takeoff refers to an AGI that would self-improve over a period of years or decades. This could be due to either the learning algorithm being too demanding for the hardware or because the AI relies on experiencing feedback from the real-world that would have to be played out in real-time. Possible methods that could deliver a soft takeoff, by slowly building on human-level intelligence, are Whole brain emulation, Biological Cognitive Enhancement, and software-based strong AGI [1]. By maintaining control of the AGI's ascent it should be easier for a Friendly AI to emerge.

Vernor Vinge, Hans Moravec and have all expressed the view that soft takeoff is preferable to a hard takeoff as it would be both safer and easier to engineer.

Hard takeoff

A hard takeoff (or an AI going "FOOM" [2]) refers to AGI expansion in a matter of minutes, days, or months. It is a fast, abruptly, local increase in capability. This scenario is widely considered much more precarious, as this involves an AGI rapidly ascending in power without human control. This may result in unexpected or undesired behavior (i.e. Unfriendly AI). It is one of the main ideas supporting the Intelligence explosion hypothesis.

The feasibility of hard takeoff has been addressed by Hugo de Garis, Eliezer Yudkowsky, Ben Goertzel, Nick Bostrom, and Michael Anissimov. It is widely agreed that a hard takeoff is something to be avoided due to the risks. Yudkowsky points out several possibilities that would make a hard takeoff more likely than a soft takeoff such as the existence of large resources overhangs or the fact that small improvements seem to have a large impact in a mind's general intelligence (i.e.:small genetic difference between humans and chimps lead to huge increases in capability).3

Notable posts

External links

References

  1. http://www.aleph.se/andart/archives/2010/10/why_early_singularities_are_softer.html
  2. http://lesswrong.com/lw/63t/requirements_for_ai_to_go_foom/
  3. http://lesswrong.com/lw/wf/hard_takeoff/

AI takeoff is sometimes casually referred to as AI FOOM.

AI takeoffTakeoff refers to the process of an artificial general intelligence going from a point incertain threshold of capability (often discussed as "human level") to being super-intelligent and capable enough to control the future where Artificial General Intelligence becomes considerably powerful, probably through Recursive self-improvement. This will lead to an increase in intelligence, and willfate of civilization.

There has been much debate about whether AI takeoff is more likely lead to an increase in computing power and other resources. The speed at which an AGI powers may expand is usually split into “soft” and “hard” takeoff scenarios.

Soft takeoff

A soft takeoff refers to an AGI that would self-improve over a period of years or decades. This could be due to either the learning algorithm being too demanding for the hardware or because the AI relies on experiencing feedback from the real-world that would have to be played out in real time. Possible methods that could deliver a soft takeoff, by slowly building on human-level intelligence, are Whole brain emulation, Biological Cognitive Enhancement and software based strong AGI.1 By maintaining control of the AGI's ascent it should be easier for a Friendly AI to emerge.

Vernor Vinge, Hans Moravec and have all expressed the view that soft takeoff is preferable to a hard takeoff as it would be both safer and easier to engineer.

Hard takeoff

A hard takeoff (or an AI going "FOOM"2) refers to AGI expansion in a matter of minutes, days,"slow" or months. It is a fast, abruptly, local increase in capability. This scenario is widely considered much more precarious, as this involves an AGI rapidly ascending in power without human control. This may result in unexpected or undesired behavior (i.e. Unfriendly AI)"fast". It is one of the main ideas supporting the Intelligence explosion hypothesis.

The feasibility of hard takeoff has been addressed by Hugo de Garis, Eliezer Yudkowsky, Ben Goertzel, Nick Bostrom and Michael Anissimov. It is widely agreed that a hard takeoff is something to be avoided due to the risks. Yudkowsky points out several possibilities that would make a hard takeoff more likely than a soft takeoff such as the existence of large resources overhangs or the fact that small improvements seems to have a large impact in a mind's general intelligence (i.e.:small genetic difference between humans and chimps lead to huge increases in capability).3

Blog posts

External links

See Also

References


  1. http://www.aleph.se/andart/archives/2010/10/why_early_singularities_are_softer.html
  2. http://lesswrong.com/lw/63t/requirements_for_ai_to_go_foom/
  3. http://lesswrong.com/lw/wf/hard_takeoff/

Vernor Vinge, Hans Moravec and Ray Kurzweil have all expressed the view that soft takeoff is preferable to a hard takeoff as it would be both safer and easier to engineer.

The feasibility of hard takeoff has been addressed by Hugo de Garis, Eliezer Yudkowsky, Ben Goertzel, Nick Bostrom and Michael Anissimov. It is widely agreed that a hard takeoff is something to be avoided due to the risks. Yudkowsky points out several possibilities that would make a hard takeoff more likely than a soft takeoff such as the existence of large resources overhangs or the fact that small improvements seems to have a large impact in a mind's general intelligence (i.e.:small genetic difference between humans and chimps lead to huge increases in capability).13.


  1. http://www.aleph.se/andart/archives/2010/10/why_early_singularities_are_softer.html
  2. http://lesswrong.com/lw/63t/requirements_for_ai_to_go_foom/
  3. http://lesswrong.com/lw/wf/hard_takeoff/

The feasibility of hard takeoff has been addressed by Hugo de Garis, Eliezer Yudkowsky, Ben Goertzel, Nick Bostrom and Michael Anissimov. It is widely agreed that a hard takeoff is something to be avoided due to the risks. Yudkowsky points out several possibilities that would make a hard takeoff more likely than a soft takeoff such as the existence of large resources overhangs or the fact that small improvements seems to have a large impact in a mind's general intelligence (i.e.:small genetic difference between humans and chimps lead to huge increases in capability)21.


  1. 1http://www.aleph.se/andart/archives/2010/10/why_early_singularities_are_softer.html
  2. http://lesswrong.com/lw/63t/requirements_for_ai_to_go_foom/

A soft takeoff refers to an AGI that would self-improve over a period of years or decades. This could be due to either the learning algorithm being too demanding for the hardware or because the AI relies on experiencing feedback from the real-world that would have to be played out in real time. Possible methods that could deliver a soft takeoff, by slowly building on human-level intelligence, are Whole brain emulation, Biological Cognitive Enhancement and software based strong AGI AGI.1. By maintaining control of the AGI's ascent it should be easier for a Friendly AI to emerge.

A hard takeoff (or an AI going "FOOM"12) refers to AGI expansion in a matter of minutes, days, or months. It is a fast, abruptly, local increase in capability. This scenario is widely considered much more precarious, as this involves an AGI rapidly ascending in power without human control. This may result in unexpected or undesired behavior (i.e. Unfriendly AI). It is one of the main ideas supporting the Intelligence explosion hypothesis.


  1. 1
  2. http://lesswrong.com/lw/63t/requirements_for_ai_to_go_foom/
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