AI4Science · Field Atlas ↤ The map
A landscape of 335 tools · 1,926 skills

What AI actually does to a scientific input.

Everyone maps this field by listing tools — the wrong unit. One level down, at the skills each tool exposes, the whole landscape collapses to just nine things AI does to a scientific input: it finds, extracts, synthesizes, verifies, generates, plans, computes, predicts, formats.

335
tools
1,926
skills
70
capabilities
9
verbs
FIG. 01

From tools to verbs

335
tools
1,926
skill mentions
70
canonical capabilities
9
transform verbs

1,526 of 1,926 raw skill strings (79.2%) cluster into the 70 canonical capabilities; each capability is one of nine transform types, defined by what it does to its input.

FIG. 02

The field at a glance

what the 335 tools are
By tool type
By scientific domain
Openness

Maturity — 200 active · 59 maintained · 39 beta · 21 research-only · 15 stale.
License trap — 48 tools state no license; some model weights are non-commercial even when code is open.

Biggest tools · GitHub stars
FIG. 03

The distribution is lopsided

tool-capabilities per verb

The field crowds the easy, high-volume verbs (Find, Compute, Plan) and thins out on the hard ones (Verify, Predict). Bar = number of tool-capabilities of each verb — the demand signal.

FIG. 04

The nine verbs

The literature loop — read · understand · write
The experiment loop — decide · run · predict
Plumbing
FIG. 05

What it means

06

Future directions

Have an idea?

A new capability worth tracking, a method the gym should test, a direction this should go — send it over. It goes straight to the team.