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Directions · AUTOMATED EXPERIMENT

AI in scientific research

In one viewAI already predicts protein and material structures, proposes candidates, and can guide robotic systems through narrow series of experiments while choosing the next step.

This is not yet an independent scientist, but a chain of specialised models, instruments and algorithms. The main frontier is a complete loop: hypothesis → experiment → verification → new hypothesis.

Status
TypeDirections
Marker
Events in dossier10
Development chronology

Researched

2021-07

AlphaFold 2

About this eventPredicting a protein's 3D structure from its amino-acid sequence approached experimental accuracy for a broad class of problems.

2022

200 million protein structures

About this eventAlphaFold DB published predictions for nearly every catalogued protein known to science. It accelerates research but does not replace experimental validation.

2023

2.2M predicted crystals

About this eventGNoME proposed 2.2 million new crystal structures, including 380,000 potentially stable candidates. These are computational candidates, not finished materials.

2023

36 materials in 17 days

About this eventThe robotic A-Lab planned syntheses, ran experiments and revised recipes, producing 36 of 57 target compounds.

2024

AlphaFold 3: molecular interactions

About this eventThe model began predicting joint structures of proteins, DNA, RNA, small molecules and ions — a step from protein shape toward interaction mechanisms.

2026-09-08

Navier–Stokes: research publication

About this eventOpenAI presented a proposed proof and Lean formalization, produced by a system using an internal model and subject to expert assessment.

NEWreportedPermanent page

In progress

now

The prediction-to-experiment gap

About this eventA model can propose thousands of candidates, but making a sample, measuring its properties and reproducing the result remain slow and expensive.

now

Narrow closed loops

About this eventSelf-driving systems already optimise specific reactions and materials, but stay inside a predefined domain and still rely on people to set the objective.

Planned

planned

A shared language for laboratories

About this eventStandard data formats and instrument interfaces are needed so models can transfer experience between setups and results can be reproduced.

Distant horizons

ahead

Verifiable machine discovery

About this eventAI formulates a novel hypothesis, chooses the decisive experiment and produces a result independently confirmed by other laboratories.

Sources and research

Primary material behind this dossier: papers, lab publications and official reports.

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