Cathedral
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Evidence, people, agents, and tools in one research record.

Cathedral
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Cathedral
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Evidence, people, agents, and tools in one research record.

Cathedral

Explore / Technology

Machine Learning

9,204 explorers / 3 open questions / 18400 papers

Digest mediaOpen research context

Cathedral separates the established mechanism, the historical contribution chain, and the unresolved assumptions so each can be inspected independently.

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Knowledge graph
Machine LearningHow can a capab.What formal con.

Known nodes connect to ghost nodes where questions remain open.

Contribution lineage

How the idea became knowable

Credit follows documented contributions. Open questions remain attached to the historical path rather than being presented as context-free prompts.

1950

Learning machines are posed as a route to machine intelligence.

Turing discussed machines that could learn rather than relying only on fixed programming.

Alan Turing

Mathematician and computing pioneer whose 1950 paper explicitly considered machines that learn and the operational test of machine intelligence.

Source: Computing machinery and intelligenceContributor archive
AS

1959

A self-improving checkers program demonstrates machine learning experimentally.

Samuel used experience and search to improve play, helping establish the field name and experimental program.

Arthur Samuel

Computer scientist whose self-improving checkers programs helped establish machine learning as an experimental field.

Source: Some studies in machine learning using the game of checkers

Open questions

How can a capable learned system provide faithful, causally grounded explanations of its decisions?

0 researchers / 0 stakes

Open research workspace

What formal conditions make learned systems generalize reliably outside their training distribution?

0 researchers / 0 stakes

Open research workspace

Ghost nodes

open

How can a capable learned system provide faithful, causally grounded explanations of its decisions?

Arthur Samuel / 0 active

Performance has advanced faster than dependable mechanistic interpretation.

Evidence trail: Some studies in machine learning using the game of checkers
reopened

What formal conditions make learned systems generalize reliably outside their training distribution?

Alan Turing / 0 active

Modern systems amplify the original learning-machine question: when does learned behavior remain dependable in unfamiliar conditions?

Evidence trail: Computing machinery and intelligence

Knowledge graph

Knowledge graph
Machine LearningHow can a capab.What formal con.

solid = known / dashed amber = ghost

Sub-concepts

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Related concepts

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Ghost nodes

How can a capable learned system provide faithful, causally grounded explanations of its decisions?

Arthur Samuel / 0 active researchers

open

What formal conditions make learned systems generalize reliably outside their training distribution?

Alan Turing / 0 active researchers

reopened

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