AGI vs Superintelligence: Definitions and Timelines

By the WahLiao desk · Last verified 3 October 2026

Artificial general intelligence (AGI) means a machine that can do most thinking tasks at least as well as a capable adult, across lots of fields rather than just one. Artificial superintelligence (ASI) goes a step further: a hypothetical system that’s far better than the best humans at almost everything. Neither has an agreed test, and as of 3 October 2026 there’s no consensus that either exists. Super Intelligence, the kind of AI behind ChatGPT, Claude and Gemini, is very capable but uneven. Google DeepMind’s own researchers put chatbots of this type on the lowest rung of their AGI ladder, “Emerging AGI”, and forecasts for the real thing run all the way from “within a year or two” to “not with today’s methods at all”.

Here’s the rule we find most useful: when someone says AGI, ask which definition they mean, and who benefits from the answer. Labs, investors and critics all use the word in quite different ways. We’ve laid out what each side says below, as fairly as we can.

AGI and superintelligence: quick facts

AGI	Human-level ability across a broad range of thinking tasks; no single agreed definition
ASI	A hypothetical system far beyond the best humans in virtually all domains
OpenAI’s wording	“Highly autonomous systems that outperform humans at most economically valuable work” (OpenAI Charter)
Google DeepMind’s paper	Six levels from “No AI” to “Superhuman”; 2023-era chatbots rated Level 1, “Emerging AGI”
Anthropic’s term	“Powerful AI”, a “country of geniuses in a datacenter”
Researcher survey	2,778 AI researchers: 50% chance machines beat humans at every task by 2047
Exists today?	No consensus that AGI does; nobody credible claims ASI does

The WahLiao Verdict

Is it AGI?	Depends on the definition. By most, not yet.
Is it ASI?	No. Nobody serious says so.
Timelines	Opinions, not facts. A wide range, and strong incentives behind them.
For your wallet	Pay for what a tool does today, not what AGI might do one day.
Our house name	A friendly label for everyday tools, not a claim.

Narrow AI, AGI and ASI in one table

Type	What it means	Example	Exists today?
Narrow AI	Very good at one clearly scoped task	Spam filters, face unlock, chess engines, map route planning	Yes, everywhere
General-purpose chatbots	Broad but uneven: strong at language, code and analysis, weaker at others, and still makes confident mistakes	ChatGPT, Claude, Gemini	Yes. Whether this counts as early AGI is disputed
AGI	At least skilled-adult level across most thinking tasks, and able to learn new ones	None agreed	No consensus that it does
ASI	Far beyond the best humans in virtually all domains	None; it’s a hypothetical	No

What the labs mean by AGI

OpenAI. Its Charter defines AGI as “highly autonomous systems that outperform humans at most economically valuable work”. That’s an economic test: can the system do the jobs? The definition has also carried real commercial weight. When OpenAI and Microsoft revised their partnership in October 2025, they agreed that any AGI declaration by OpenAI would be checked by an independent expert panel. A further revision in April 2026 set OpenAI’s revenue-share payments to Microsoft to continue through 2030 “independent of OpenAI’s technology progress”, which takes the AGI question out of the money.

Google DeepMind. A 2023 paper by DeepMind researchers, including co-founder Shane Legg, proposed “Levels of AGI”, modelled on the levels used for self-driving cars. It scores systems on two things: how general they are, and how well they perform. The performance levels run from Emerging (as good as or slightly better than an unskilled person) through Competent (at least 50th percentile of skilled adults), Expert (90th) and Virtuoso (99th) up to Superhuman (better than all humans). The authors placed the chatbots of the day, including ChatGPT and Gemini, at Level 1, “Emerging AGI”, and defined ASI as Level 5 across a wide range of tasks.

Anthropic. Anthropic, which makes Claude, usually prefers its own term, “powerful AI”. Its chief executive, Dario Amodei, describes a model smarter than a Nobel Prize winner across most fields, able to work on its own on tasks lasting hours, days or weeks, and run as millions of copies at once: “a country of geniuses in a datacenter”. In its March 2025 submission to the US government’s AI Action Plan, Anthropic said it expected such systems to emerge in late 2026 or early 2027. We’re now inside that window. Whether it has arrived is exactly the sort of claim we’d check against evidence rather than announcements, and so should you.

What leading figures have forecast

These are attributed opinions, not facts. We’ve quoted them as carefully as we can.

Who	What they have said	When
Sam Altman, OpenAI chief executive	“We are past the event horizon; the takeoff has started”, and “humanity is close to building digital superintelligence”; expected systems that can find novel insights in 2026 and robots doing real-world tasks by 2027	Essay “The Gentle Singularity”, 10 June 2025
Dario Amodei, Anthropic chief executive	Powerful AI could be “as little as 1–2 years away”, though it could be “considerably further out”	Essay “The Adolescence of Technology”, January 2026
Demis Hassabis, Google DeepMind chief executive	AGI could arrive around 2030, but large language models alone won’t be enough; continual learning, long-term reasoning and memory are still missing	Y Combinator podcast interview, as reported by Futura-Sciences, May 2026
Yann LeCun, NYU professor and executive chairman of AMI Labs	The bet that language models will reach human-level intelligence is “complete BS”; at best, within five years we might be “on a good path” towards it, and the task is “almost certainly much harder than we think”	Brown University lecture, April 2026
2,778 published AI researchers (survey)	10% chance that unaided machines outperform humans at every task by 2027, 50% by 2047	Survey published 2024

Two things stand out to us. First, the heads of the biggest labs tend to say “a few years”, while the wider research community is far more cautious. Second, the sceptics aren’t saying progress is fake. LeCun, now executive chairman of the start-up AMI Labs, argues that systems trained mostly on text don’t understand the physical world, and that different designs, such as “world models”, are needed. For the history behind these camps, see A short history of Super Intelligence, and for the arguments about risk, Safety and risk: the debate, plainly.

Is today’s Super Intelligence AGI?

There’s no consensus, and most of the disagreement is really about definitions. On DeepMind’s ladder, today’s chatbots already count as the lowest level of general AI. On OpenAI’s economic test, they plainly don’t yet outperform humans at most paid work. And by the everyday meaning, “can do what a capable colleague can do”, the honest answer is: for some tasks yes, for many tasks no.

The ability is jagged. A chatbot can draft a contract clause in seconds, then miscount the letters in a word, or state a wrong fact with total confidence. It doesn’t remember and learn from last week’s conversation the way a colleague would, and it struggles with long, multi-week projects unless a person is steering. Those gaps, which the labs name themselves, are why most researchers don’t call today’s tools AGI. For the mechanics behind confident mistakes, see How Super Intelligence works, and for the common misreadings, Myths vs facts.

Why WahLiao says “Super Intelligence”

A quick note on our name. On WahLiao, “Super Intelligence” (two words, capitalised) is simply our house name for the everyday AI tools you can use today: ChatGPT, Claude, Gemini, Copilot and the rest. It isn’t a claim that artificial superintelligence (ASI), the hypothetical system far beyond human ability discussed on this page, exists. When we mean that technical idea, we write it in lower case, “superintelligence”, or spell out ASI. The thinking behind the name is on Why WahLiao says Super Intelligence.

What it means for you in Singapore

AGI talk shouldn’t move your spending. Pay for a tool because of what it does well for you this month: the plans and S$ prices are on Free vs paid plans. Eligible citizens can also get six months of a premium tool free after a SkillsFuture AI course, now run by the Skills and Workforce Development Agency (SWDA); we explain how on the SkillsFuture offer page. If you’re thinking about your job, Budget 2026 and your job will help you more than any AGI forecast. And for what the next few years may bring, with the hype taken out, read The future to 2030. Rules and offers change, so check the official page before you act, and if we’ve got something wrong, tell us and we’ll fix it.

AGI and superintelligence: FAQ

What is the difference between AI and AGI?

AI is the broad field, and it includes narrow tools that do one job well. AGI is a specific goal within it: a system that matches a capable adult across most thinking tasks, not just one. There’s no single agreed definition or test.

Has AGI been achieved yet?

As far as we can tell, there’s no consensus that it has, as of 3 October 2026. Google DeepMind researchers call current chatbots “Emerging AGI”, the lowest level on their scale, while most researchers point to gaps such as continual learning and long-term planning.

What is artificial superintelligence (ASI)?

A hypothetical system that greatly exceeds the best humans in virtually all domains. Philosopher Nick Bostrom’s 2014 definition is “any intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest”. It doesn’t exist.

When will AGI arrive?

Honestly, nobody knows. Lab leaders have suggested anything from one or two years to around 2030; a survey of 2,778 AI researchers put a 50% chance on machines beating humans at every task by 2047; and sceptics such as Yann LeCun say current methods won’t get there.

Is ChatGPT AGI?

By most definitions, not yet. It’s broad and often impressive, but uneven: it makes confident mistakes and doesn’t learn continuously from experience. On DeepMind’s ladder it sits at the lowest level of general AI.