Good (1965), Speculations Concerning the First Ultraintelligent Machine
- “intelligence explosion”
- “an ultraintelligent machine could design even better machines; there would then unquestionably be an ‘intelligence explosion’, and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make.”
Vinge (1993), The Coming Technological Singularity
- “the Singularity”
- “Within thirty years, we will have the technological means to create superhuman intelligence. Shortly after, the human era will be ended. […] I think it’s fair to call this event a singularity (‘the Singularity’ for the purposes of this paper). It is a point where our old models must be discarded and a new reality rules.”
Yudkowsky (2007), Levels of Organization in General Intelligence
- “recursive self-improvement” (“seed AI”)
- “A seed AI is an AI designed for self-understanding, self-modification, and recursive self-improvement. […] The later consequences of seed AI (such as true recursive self-improvement) only show up after the AI has achieved significant holonic understanding and general intelligence.”
Omohundro (2007), The Nature of Self-Improving Artificial Intelligence
- “self-improving AI”
- “A self-improving AI is a system that understands its own behavior and is able to make changes to itself in order to improve itself. […] any system which acts in a rational way will want to self-improve itself, so this discussion actually applies to all AIs.”
Hanson (2008), Economics of the Singularity
- “singularity”
- “Its arrival could produce a singularity—an overwhelming departure from prior trends, with uneven and dizzyingly rapid change thereafter […]. The world economy, which now doubles in 15 years or so, would soon double in somewhere from a week to a month.”
Chalmers (2010), The Singularity: A Philosophical Analysis
- “intelligence explosion” (“AI+”, “AI++”)
- “we can put the argument for an intelligence explosion as follows […]. AI+ is artificial intelligence of greater than human level […]. AI++ (or superintelligence) is AI of far greater than human level (say, at least as far beyond the most intelligent human as the most intelligent human is beyond a mouse). […] There will be AI+. […] If there is AI+, there will be AI++. […] There will be AI++.”
- “proportionality thesis”
- “a proportionality thesis: it holds that increases in intelligence (or increases of a certain sort) always lead to proportionate increases in the capacity to design intelligent systems.”
Yudkowsky (2013), Intelligence Explosion Microeconomics
- “returns on cognitive reinvestment”
- “returns on cognitive reinvestment—the ability to invest more computing power, faster computers, or improved cognitive algorithms to yield cognitive labor which produces larger brains, faster brains, or better mind designs.”
Bostrom (2014), Superintelligence
- “recursive self-improvement”
- “an early version of the AI could design an improved version of itself […] such a process of recursive self-improvement might continue long enough to result in an intelligence explosion […] to radical superintelligence.”
Christiano (2018), Takeoff Speeds
- “slow takeoff” / “fast takeoff”
- “whether the development of AGI will look more like a breakthrough within a small group (‘fast takeoff’), or a continuous acceleration distributed across the broader economy or a large firm (‘slow takeoff’). […] [operationalized:] There will be a complete 4 year interval in which world output doubles, before the first 1 year interval in which world output doubles […] fast takeoff is the negation of the above statement.”
Aghion, Jones, and Jones (2019), Artificial Intelligence and Economic Growth
- “singularities”
- “A.I. can become rapidly self-improving, leading to ‘singularities’ that feature unbounded machine intelligence and/or unbounded economic growth in finite time.”
- “Type I” / “Type II” growth explosion
- “a ‘Type I’ growth explosion, where growth rates increase without bound but remain finite at any point in time; and a ‘Type II’ growth explosion, where infinite output is achieved in finite time.”
Roodman (2020), Modeling the Human Trajectory
- “superexponential” growth
- “A univariate stochastic model is introduced that is mathematical kin with the neoclassical economic model […] when projected forward, the superexponential equation sends [GWP] to infinity in finite time. […] if the patterns of history continue, then some sort of economic explosion will take place again, the most plausible channel being AI. It wouldn’t reach infinity, but it could be big.”
Davidson (2021), Could Advanced AI Drive Explosive Economic Growth?
- “explosive growth”
- “‘explosive growth’, meaning > 30% annual growth of gross world product (GWP)”.
Nordhaus (2021), Are We Approaching an Economic Singularity?
- “Singularity”
- “rapid growth in information technology and artificial intelligence will cross some boundary, after which economic growth will rise rapidly […]. I define Singularity as a time when the economic growth rate crosses 20 percent per year.”
Karnofsky (2021), Forecasting Transformative AI: What Kind of AI?
- “PASTA”
- “AI systems that can essentially automate all of the human activities needed to speed up scientific and technological advancement. I will call this sort of technology Process for Automating Scientific and Technological Advancement, or PASTA. (I mean PASTA to refer to either a single system or a collection of systems that can collectively do this sort of automation.)”
Trammell and Korinek (2023), Economic Growth under Transformative AI
- “self-replicate” / “self-improve”
- “fully automating production alone (so that machines can self-replicate) would dramatically raise the growth rate […]. Automating R&D (so that machines can self-improve) would accelerate the transformation, but may not produce it in isolation.”
Erdil and Besiroglu (2024), Explosive Growth from AI Automation
- “explosive growth”
- “we will refer to ‘explosive growth’ as growth an order of magnitude greater than what is typical in today’s frontier economies. Specifically, we define this as annual real gross world product (GWP) exceeding 130% of its maximum value over all previous years.”
Eth and Davidson (2025), Will AI R&D Automation Cause a Software Intelligence Explosion?
- “AI Systems for AI R&D Automation (ASARA)”
- “systems, which we call AI Systems for AI R&D Automation (ASARA), would represent a critical threshold in AI development. The hypothesis is that ASARA would trigger a runaway feedback loop: ASARA would quickly develop more advanced AI, which would itself develop even more advanced AI, resulting in extremely fast AI progress – an ‘intelligence explosion.’ […] [ASARA] can be thought of as being able to substitute for any remote R&D workers at companies advancing the state of the art for AI.”
- “software intelligence explosion (SIE)”
- “AI systems could become dramatically more capable just by finding software improvements […]. We call this scenario a software intelligence explosion (SIE).”
Davidson and Houlden (2025), How Quick and Big Would a Software Intelligence Explosion Be?
- “ASARA”
- “we define ASARA as AI that can replace every human researcher at an AI company with 30 equally capable AI systems each thinking 30X human speed.”
Ho and Whitfill (2025), The Software Intelligence Explosion Debate Needs Experiments
- “software intelligence explosion”
- “These AIs are smart enough to find new algorithms to make smarter AIs, which make even smarter AIs, and so on […] multiple years of AI progress compressed into a single year just through software advances — a ‘software intelligence explosion’.”
Erdil and Barnett (2025), Most AI Value Will Come from Broad Automation, Not from R&D
- “software-only singularity”
- “If AI systems were able to automate the process of their own software R&D, a software-only singularity might become possible: on a fixed stock of compute, we could run AI researchers who search for ways to improve their own algorithms, which would allow us to run even more virtual researchers to make yet more software progress, et cetera.”
Clark (2025), Import AI 455: AI Systems Are About to Start Building Themselves
- “no-human-involved AI R&D”
- “no-human-involved AI R&D - an AI system powerful enough that it could plausibly autonomously build its own successor”.
Kokotajlo, Alexander, et al. (2025), AI 2027 (Takeoff Forecast)
- “superhuman coder (SC)”
- “an AI system that can do any coding tasks that the best AGI company engineer does, while being much faster and cheaper.”
- “superhuman AI researcher (SAR)”
- “An AI system that can do the job of the best human AI researcher but faster, and cheaply enough to run lots of copies.”
- “superintelligent AI researcher (SIAR)”
- “An AI system that is vastly better than the best human AI researchers. The gap between SAR and SIAR is 2x the gap between an automated median AGI company researcher and a SAR.”
- “artificial superintelligence (ASI)”
- “An AI system that is much better than the best human at every cognitive task.”
Kokotajlo, Lifland, et al. (2025), AI Futures Model: Dec 2025 Update
- “superhuman AI researcher (SAR)”
- “An AI system that can do the job of the best human AI researcher but 30x faster and with 30x more agents […]. It must have enough diversity of expertise to on average do the same for other top researchers with complementary skills.”
Jones (2026), A.I. and Our Economic Future
- “weak links”
- “automating intelligence leads economic growth rates to accelerate […] slowed by the presence of ‘weak links’. […] Accelerating economic growth requires the vast majority of the weak links to be automated away.”
Cotra (2026), Six Milestones for AI Automation
- “Adequacy”
- “the very first time the hit from removing humans is smaller than 100% in a given sector — the first time that machines can just barely produce output in that sector, painstakingly limping along by themselves without any humans to operate them. Let’s call this milestone adequacy.”
- “Parity”
- “The next interesting milestone is parity — the first point when getting rid of the AIs slows down progress in the sector more than getting rid of all the humans.”
- “Supremacy”
- “Beyond parity, we can talk about supremacy — the first point when productivity in a given sector would actually increase from removing humans.”
Davidson et al. (2026), When Does Automating AI Research Produce Explosive Growth?
- “recursive self-improvement”
- “recursive self-improvement—where AI systems become increasingly capable of designing and improving themselves—creates a feedback loop leading to an ‘intelligence explosion’ and rapid economic growth.”
- “technological feedback loop”
- “technological feedback loops across the innovation network […] a network of heterogeneous research sectors, where innovations in one sector spill over to increase the rate of innovation in other sectors.”
- “economic feedback loop”
- “an economic feedback loop, in which higher output generates more resources that can be deployed to drive further economic growth. The classic example is capital accumulation: higher output leads to more investment, which produces yet more output.”
- “explosive growth”
- “growth becomes superexponential (‘explosive’) […] if the combined strength of technological and economic feedback loops overcomes diminishing returns.”
- “mathematical singularity”
- “if β < 0, so that there are increasing returns, then there is a literal mathematical singularity: \(S_t\) approaches infinity in finite time.”
Favaro and Clark (2026), When AI Builds Itself
- “recursive self-improvement”
- “Taken far enough, and given enough compute, that trend points to an AI system capable of fully autonomously designing and developing its own successor. This is called recursive self-improvement. We are not there yet, and recursive self-improvement is not inevitable. But it could come sooner than most institutions are prepared for.”
Clark (2026), Import AI 460
- “maximalist” RSI
- “a maximalist version where an AI system is smart enough to autonomously design its own successor”.
- “prosaic” RSI
- “a more prosaic version where we begin to see a compounding speedup of the productivity of the AI labs themselves.”
References
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Citation
BibTeX citation:
@online{cunningham2026,
author = {Cunningham, Tom},
title = {Definitions of {Recursive} {Self-Improvement}},
date = {2026-06-05},
url = {tecunningham.github.io/posts/2026-06-05-rsi-definitions.html},
langid = {en}
}
For attribution, please cite this work as:
Cunningham, Tom. 2026. “Definitions of Recursive
Self-Improvement.” June 5, 2026. tecunningham.github.io/posts/2026-06-05-rsi-definitions.html.