✳ INTELLIGENCE EXPLOSION AN EXPLORER BY TOM HARWOOD

AI-ASSISTED SCIENCE, SOURCE BY SOURCE

Is discovery accelerating?

Watch the curve grow, follow what builds on what,
and read the limits before you decide.

A GROWING, CURATED COLLECTION

— milestones in the last 90 days · — in the 90 days before

— milestones · 5 fields · 2020–2026

● Verified   ◉ Provisional   ○ Claimed

SELECT A POINT TO TRACE WHAT IT BUILDS ON

Linear axes · one point per entry · gold arcs show documented “builds on” links. How to read this ↓

Measured elsewhere

This collection is curated. These trends are measured. Read them together.

METR · SOFTWARE TASKS

How long a task can an agent complete?

~7 months → ~3 months long-run → since 2024 · 50% task-horizon doubling

METR’s TH1.1 analysis reports 89-day doubling since 2024, compared with 196 days over 2019–2025 using a hybrid of TH1 and TH1.1 estimates. Task length is measured in human expert time.

The May 19 report puts the public-frontier 50% horizon at ~12h (CI 5h–61h) for February–March 2026.

Task difficulty, not runtime; the suite cannot reliably measure above ~16h. Trends depend on task composition.

Read Time Horizon 1.1 ↗ Analysis: Jan 29, 2026 · checked Oct 19, 2026

Read the frontier risk report ↗

Analysis: May 19, 2026 · checked Oct 19, 2026
EPOCH AI · TRAINING COMPUTE

How much computation goes into training?

~5× per year doubling ~5.2 months · 90% CI 4–6× per year

Epoch AI reports this growth in training compute for frontier language models since 2020.

Compute is an input to AI development, not a count of discoveries or a direct measure of scientific progress.

Read Epoch AI’s trends ↗ Analysis: Feb 5, 2026 · checked Oct 19, 2026
Capability signal

Four Gemini 4 Argon agents beat Minecraft

27h 14m to defeat the Ender Dragon

4 agents controlled players through Mineflayer on Easy difficulty with a random seed. They wrote 2,783 programs themselves and died 605 times, with no human-written game logic.

Long-horizon autonomy — not a scientific discovery, but the kind of capability discovery agents run on.

Read the abstract ↗ Paper: Oct 15, 2026 · checked Oct 19, 2026
See the plotted values
WATCH THE COLLECTION GROW2026
2020202120222023202420252026
HOW TO READ THIS What the curve can and cannot tell you

01 / A MAP, NOT A MEASUREMENT Every point is one curated entry, and a batch release counts once. The curve shows how this collection grows. It is not a measured rate of scientific progress. A selective collection cannot establish a scientific “knee” or an exponential growth rate.

02 / WHY RECENT MONTHS LOOK DENSER Recent announcements are easier to find and still fresh, and older periods have been backfilled by hand. The hero comparison counts entries in two equal 90-day windows ending at the editorial cutoff. More entries can mean more work, more announcements, more attention, or our own selection. It does not prove faster science.

03 / WHAT “BUILDS ON” MEANS A link appears only where the source documents the dependency, for example a model trained on, or using, an earlier system’s outputs. Missing links do not mean independence. Branches in the tree group fields. They do not claim causation.

05 / DEEP TIME AND SELECTION Deep time uses a reversed logarithmic scale of years before the editorial cutoff; recent years occupy more space. Time dive narrows the window from 1440 to 2020. Historical markers are hand-picked context, not milestones. Comparing their gaps with recent entries illustrates selection bias: neither list is complete or consistently sampled, and shorter gaps do not establish acceleration.

04 / FOLLOW THE EVIDENCE Each entry links to a primary source and states its limits. Prediction, laboratory evidence, benchmarks and mathematical verification are different kinds of progress. The collection is curated by hand. Automatic updates are not enabled.

HOW PROGRESS COMPOUNDS

Each advance leaves tools behind.

01 / SHARED INFRASTRUCTURE

AlphaFold → antimicrobial investigation

In October 2026, Antigravity used AlphaFold Database structures alongside protein annotations and genomic context to investigate an antimicrobial candidate. Wet-lab validation is pending.

Follow the source ↗
02 / TOOLS CROSS DISCIPLINES

Physics → exact quantitative science

BootLoops describes a growing toolkit: methods from particle physics transfer to Bayesian calculations, and each project contributes improved tools.

Explore BootLoops ↗
03 / RESULTS BECOME INPUTS

Earlier results → further arguments

OpenAI reports that some outputs in its mathematics collection build on earlier model-produced results. Verification varies across the collection.

Explore the manuscripts ↗

ABOUT THIS COLLECTION

Wonder, with receipts.

Intelligence Explosion follows selected milestones in AI-assisted science. Dates mark the linked publication or announcement, not necessarily the first experiment.

Tree branches are subject categories, not claims of causation. “Builds on” links appear only where a source documents the dependency. Points and leaves have equal weight. Their size does not score importance. Every entry comes with its source description and limits.

The collection covers 2020–2026 and is not comprehensive. New findings require editorial review before publication. Last editorial review: .

Built for Tom Harwood’s Intelligence Explosion project.