Hard Takeoff

Extracted Attributes

• Core Mechanism

  Recursive self-improvement and local capability leaps

• Alternative Name

  FOOM

• Contrasting Model

  Soft Takeoff / S-curve Model

• Time Horizon (Robotics Context)

  Within a decade

• Time Horizon (Theoretical AI Context)

  Minutes, hours, days, or months

Timeline

• I. J. Good introduces the intelligence explosion model, establishing the theoretical framework for a hard takeoff. (Source: undefined)

  1965-01-01

• Gopal P. Sarma publishes 'Brief Notes on Hard Takeoff, Value Alignment, and Coherent Extrapolated Volition' on arXiv. (Source: undefined)

  2017-04-12

• 1X plans the launch of NEO, a bipedal robot designed as a platform for AI foundation models leading toward embodied AGI. (Source: undefined)

  2026-01-01

Technological singularity

The technological singularity, often simply called the singularity, is a hypothetical event in which technological growth accelerates beyond human control, producing unpredictable changes in human civilization. According to the most popular version of the singularity hypothesis, I. J. Good's intelligence explosion model of 1965, an upgradable intelligent agent could eventually enter a positive feedback loop of successive self-improvement cycles; more intelligent generations would appear more and more rapidly, causing an explosive increase in intelligence that culminates in a powerful superintelligence, far surpassing human intelligence. Prominent technologists and academics dispute the plausibility of a technological singularity and associated artificial intelligence "explosion", including Paul Allen, Jeff Hawkins, John Holland, Jaron Lanier, Steven Pinker, Theodore Modis, Gordon Moore, and Roger Penrose. One claim is that artificial intelligence growth is likely to run into decreasing returns instead of accelerating ones. Stuart J. Russell and Peter Norvig observe that in the history of technology, improvement in a particular area tends to follow an S curve: it begins with accelerating improvement, then levels off without continuing upward into a hyperbolic singularity.

Web Search Results

• AI Takeoff — LessWrong

  # Hard takeoff A hard takeoff (or an AI going "FOOM" ) 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.: the small genetic difference between humans and chimps lead to huge increases in capability) . # Notable posts Hard Takeoff by Eliezer Yudkowsky # External links [...] Hard Takeoff by Eliezer Yudkowsky # External links The Age of Virtuous Machines by J. Storrs Hall President of The Foresight Institute Hard take off Hypothesis by Ben Goertzel. Extensive archive of Hard takeoff Essays from Accelerating Future Can we avoid a hard take off? by Vernor Vinge Robot: Mere Machine to Transcendent Mind by Hans Moravec The Singularity is Near by Ray Kurzweil References 1. 2. 3. Subscribe Discussion 2 Subscribe Discussion 2 Posts tagged AI Takeoff 13 101AlphaGo Zero and the Foom Debate Eliezer Yudkowsky 17 13 74New report: Intelligence Explosion Microeconomics Eliezer Yudkowsky 246 12 105Arguments about fast takeoff Ω paulfchristiano Ω 68 11 196Discontinuous progress in history: an update KatjaGrace 25 11

• [1704.00783] Brief Notes on Hard Takeoff, Value Alignment, and Coherent Extrapolated Volition

  There is no precise boundary between the two scenarios, but in broad strokes, a hard takeoff refers to a transition from human level intelligence to superintelligence in a matter of minutes, hours or days. A soft takeoff refers to a scenario where this transition is much more gradual, perhaps taking many months or years. The practical importance of this qualitative distinction is that in a soft takeoff, there may opportunities for human intervention in the event that the initial AI systems have problematic design flaws. [...] # Brief Notes on Hard Takeoff, Value Alignment, and Coherent Extrapolated Volition Gopal P. Sarma[!(/html/1704.00783/assets/orcid128.png)1](  1. Emory University, Atlanta, GA USA Email: gopal.sarma@emory.edu ## I. On Hard Takeoff The distinction between hard takeoff and soft takeoff has been used to describe different possible scenarios following the arrival of human-level artificial intelligence. The basic premise underlying these concepts is that software-based agents would have the ability to improve their own intelligence by analyzing and rewriting their source code, whereas biological organisms are significantly more restricted in their capacity for self-improvement [1, 2, 3, 4, 5]. [...] However, the premise of intelligent agents with capacities in substantial excess of any human being, which are able to process the sum total of human knowledge in the form of books, video, and ongoing contemporary events implies that greater levels of intelligence in the AI systems will be accompanied by actions taken with a corresponding level of information, insight, and operational skill. Therefore, if the initial systems are designed correctly with respect to value alignment and goal structure stability, it is in fact a hard takeoff scenario which would be less disruptive than a soft takeoff, not the other way around.

• What are the differences between a singularity, an intelligence explosion, and a hard takeoff? — LessWrong

  A hard takeoff is a scenario where the transition to superintelligence happens quickly and suddenly instead of gradually. The opposite is a soft takeoff. Related distinctions include fast versus slow takeoff and discontinuous versus continuous takeoff. A takeoff can be continuous but eventually become very fast, as in the case of Paul Christiano's predictions of a "slow takeoff" that results in hyperbolic growth. [...] "FOOM" is more or less a synonym of "hard takeoff", perhaps based on the sound you might imagine a substance making if it instantly expanded to a huge volume. The term is associated mostly with the Yudkowsky vs. Hanson FOOM debate: both eventually expect very fast change, but Yudkowsky argues for sudden and discontinuous change driven by local recursive self-improvement, while Hanson argues for a more gradual and spread-out process. Hard takeoff does not require recursive self-improvement, and Yudkowsky now thinks regular improvement of AI by humans may cause sufficiently big capability leaps to preempt recursive self-improvement. On the other hand, recursive self-improvement could be gradual (or at least start out that way): Paul Christiano thinks an intelligence explosion is "very

• Technological singularity - Wikipedia

  In a hard takeoff scenario, an artificial superintelligence rapidly self-improves, "taking control" of the world (perhaps in a matter of hours), too quickly for significant human-initiated error correction or for a gradual tuning of the agent's goals. In a soft takeoff, the AI still becomes far more powerful than humanity, but at a human-like pace (perhaps on the order of decades), on a timescale where ongoing human interaction and correction can effectively steer its development.( [...] Ramez Naam argues against a hard takeoff. He has pointed out that we already see recursive self-improvement by superintelligences, such as corporations. Intel, for example, has "the collective brainpower of tens of thousands of humans and probably millions of CPU cores to... design better CPUs!" But this has not led to a hard takeoff; rather, it has led to a soft takeoff in the form of Moore's law.( Naam further points out that the computational complexity of higher intelligence may be much greater than linear, such that "creating a mind of intelligence 2 is probably _more_ than twice as hard as creating a mind of intelligence 1."( [...] J. Storrs Hall believes that "many of the more commonly seen scenarios for overnight hard takeoff are circular–they seem to assume hyperhuman capabilities at the _starting point_ of the self-improvement process" in order for an AI to be able to make the dramatic, domain-general improvements required for takeoff. Hall suggests that rather than recursively self-improving its hardware, software, and infrastructure all on its own, a fledgling AI would be better off specializing in one area where it was most effective and then buying the remaining components on the marketplace, because the quality of products on the marketplace continually improves, and the AI would have a hard time keeping up with the cutting-edge technology used by the rest of the world.(

• Distinguishing definitions of takeoff — AI Alignment Forum

  # Foom/Hard takeoff The traditional hard takeoff position, or "Foom" position (these appear to be equivalent terms) was characterized in this post from Eliezer Yudkowsky. It contrasts Hanson's takeoff scenario by emphasizing local dynamics: rather than a population of artificial intelligences coming into existence, there would be a single intelligence that quickly reaches a level of competence that outstrips the world's capabilities to control it. The proposed mechanism that causes such a dynamic is recursive self improvement, though Yudkowsky later suggested that this wasn't necessary.