Tracking the
SingularityAn independent research tracker

Are we there yet?

22%

toward AI-led advancement

A judgment-based index, with low confidence. Not a scientific measure or a countdown.

What goes into this number?

Updated: November 7, 2025/1,046 dates/14 fields/85 measurable outcomes

What is the Singularity?

The technological singularity is a transition in which technological advancement across many fields compounds faster than human-directed research could sustain or humans can reliably predict.

It is driven by reinforcing loops, in which each advance makes further advances easier, and its strongest engine is artificial intelligence that first matches and then exceeds human capability.

It is a period we could be partway into, not a single moment. The definition does not claim a date, or that it is certain to happen.

How it could come aboutFull definition and sources

Advancements

Advancements are concrete, real-world products, events and results. Each one is evidence of progress on a measurable outcome, and together they show how far AI has carried a field toward the Singularity.

Mathematics

AAdvanced examination performance25%

BFormal verification25%

CResearch problem success15%

DResearch productivity10%

ESubstantial novelty20%

FTime to a new proof15%

Software

AComplete project delivery20%

CDevelopment speed20%

DFresh issue resolution20%

EMaintenance quality20%

FReliable autonomy20%

AI research

BAlgorithmic efficiency40%

CExperiment efficiency20%

DResearch autonomy25%

EResearch task performance40%

FSuccessive improvement20%

GValid discoveries30%

Computing hardware

ADesign productivity45%

CGeneralization35%

DManufacturability30%

EPower, performance, and area30%

FUseful AI efficiency35%

Robotics

BGeneralization30%

CIntervention rate25%

DReliability25%

ESkill acquisition25%

FUseful productivity20%

Materials

ADeployment value0%

BDiscovery efficiency25%

CFunctional improvement20%

DIdentity and novelty20%

EScale and durability0%

FSynthesis success35%

Chemistry

AExperimental efficiency30%

BProcess burden10%

CRoute execution30%

DSubstantial novelty15%

ETransfer and scale30%

FYield and selectivity30%

Biology

ADesign success40%

BFunctional prediction25%

CGeneralization20%

DResearch efficiency20%

EStructural accuracy45%

FUseful novelty25%

Drug discovery

ACandidate quality25%

BClinical benefit15%

CDevelopment efficiency25%

DPortfolio productivity10%

ETarget validation25%

FTranslation20%

Medicine

ACare delivery25%

BCost effectiveness10%

CDiagnostic performance25%

DEquity and transfer10%

EHarm and unnecessary care15%

FPatient benefit10%

Energy

AFusion control30%

BGrid reliability0%

CNet energy0%

DOperational efficiency0%

EResearch productivity0%

FStorage performance0%

Weather and climate

AClimate application validity35%

BComputation45%

CDecision benefit15%

DExtreme-event performance40%

EForecast skill40%

FRobustness20%

Physics

AEquation recovery0%

BExperiment efficiency25%

CExperimental confirmation0%

DNovel prediction20%

ESimulation efficiency40%

FTheoretical novelty20%

Education

AAccess and disparities15%

BInstructional cost10%

CLearning gain20%

DRetention10%

ETime to mastery25%

FTransfer15%

The End?

Probably not. The Singularity is not a finish line. Reaching 100% is where the curve stops being ours to draw, not where progress stops.

Once advancement compounds on its own, there is no obvious reason for it to end. It could go on forever, or at least for as long as humankind is here to live with it.

What waits up there is guesswork. The things people have dreamed about for generations, such as flying cars, teleportation and immortality, sit on the list beside things no one has imagined yet. Some may arrive, some may prove impossible, and some may simply stop mattering.

This is speculation based on the increasing speed of technological advancements humanity is experiencing.

Dates after this point are based on our rate of advancement.

Understand the idea

How could it
come about?

No single breakthrough brings the singularity about. It builds through loops in which each advance makes the next one easier.

AI improving AI. AI tools help build more capable AI, which could lead to systems that match human ability and then exceed it, each helping to build its successor.

Progress compounding within a field. An advance in medicine, materials or energy opens the way to further advances in the same field, with or without AI involved.

Progress compounding across fields. Better chips, energy, materials and robots feed AI and one another, and AI in turn speeds each of them up.

Progress has always built on itself. What would mark a singularity is the pace: acceleration that is sustained, shows up in many fields at once, and no longer depends on people to choose, do and check the work. Whether that happens, and when, remains an open question.

Read the full definition and its sources
1

People lead

We set the questions, build the tools and check the results.

2

AI contributes

AI takes on useful work, while people guide and verify it.

3

AI advances independently

AI chooses worthwhile work, validates it and keeps improving the process.

These are stages of the idea, not dated predictions. Our evidence includes useful assistance and bounded autonomous tasks; it does not establish that the singularity has begun.
Follow the evidence

Progress looks different
in every field.

A strong result in one task does not mean a whole field runs itself. Open a field to see what works, what is still uncertain and what we track next.

14 fields

Field percentages summarize their outcome estimates. They are not the share of jobs replaced, or proof that a field is that far from full autonomy.

Keep the number in perspective

An estimate you
can look inside.

The headline is a guide to our research, not a verdict on humanity’s future.

What does 22% mean?

We score each outcome against five questions: can AI do the work, handle unfamiliar problems, choose useful goals, check its results and keep improving without people managing the process?

We average the outcomes within each field, then give all 14 fields equal weight. The result is 21.57%, shown as 22%. This is a new summary index built from the existing research scores.

See the calculation
FieldOutcomesOutcome averageHeadline weight
Mathematics618.33%1 of 14 equal shares
Software620.00%1 of 14 equal shares
AI research727.86%1 of 14 equal shares
Computing hardware635.00%1 of 14 equal shares
Robotics624.17%1 of 14 equal shares
Materials616.67%1 of 14 equal shares
Chemistry624.17%1 of 14 equal shares
Biology629.17%1 of 14 equal shares
Drug discovery620.00%1 of 14 equal shares
Medicine615.83%1 of 14 equal shares
Energy65.00%1 of 14 equal shares
Weather and climate632.50%1 of 14 equal shares
Physics617.50%1 of 14 equal shares
Education615.83%1 of 14 equal shares

We calculate with unrounded values and round only the display. Field averages are summaries, not validated field-wide completion measurements.

What are the limits?

The starting point is the period before ChatGPT’s public release in 2022. The endpoint is sustained advancement managed entirely by AI. The distance between those points is not a scientifically established scale.

Missing evidence receives no progress credit, so it can pull the estimate down. A score of zero can mean we do not yet have a qualifying measurement. Small changes in these judgments are not precise measurements of real-world change.

The latest saved assessment is November 7, 2025. Earlier graphs are retrospective estimates, not measurements recorded at the time. This page does not update itself with new research.

Read the full scoring approach