Thinking·OS

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Explore the knowledge graph

Algorithm models Turing machine. Activate to inspect this relation.Algorithm is a Sequence. Activate to inspect this relation.Computational biology applies to Algorithm. Activate to inspect this relation.Computational complexity theory is part of Algorithm. Activate to inspect this relation.Data compression depends on Algorithm. Activate to inspect this relation.DNA is analogous to Algorithm. Activate to inspect this relation.DNA is a Sequence. Activate to inspect this relation.Dynamic programming applies to Algorithm. Activate to inspect this relation.Encryption depends on Algorithm. Activate to inspect this relation.Fibonacci sequence depends on Recursion. Activate to inspect this relation.Fibonacci sequence is a Sequence. Activate to inspect this relation.Greedy algorithm is a Algorithm. Activate to inspect this relation.Infinity applies to Sequence. Activate to inspect this relation.Iterative method is a Algorithm. Activate to inspect this relation.Machine learning is a Algorithm. Activate to inspect this relation.P versus NP applies to Algorithm. Activate to inspect this relation.Randomized algorithm is a Algorithm. Activate to inspect this relation.Recursion applies to Algorithm. Activate to inspect this relation.Search algorithm is a Algorithm. Activate to inspect this relation.Sequence is a Pattern. Activate to inspect this relation.Sorting algorithm is a Algorithm. Activate to inspect this relation.Turing machine models Algorithm. Activate to inspect this relation.RecursionAlgorithmFibonacci sequenceSequenceMachine learningGreedy algorithmSearch algorithmData compressionDNASorting algorithmTuring machineComputational biologyComputational complexity theoryIterative methodP versus NPRandomized algorithmDynamic programmingEncryptionPatternInfinity
Relationship types

10 concepts viewed through this lens. Bridge concepts connect this view to Agriculture, Algebra, Algorithms, Archaeology….

Legend
  • Focused concept
  • Connected concept
  • Bridge concept (just outside the lens)
  • Arrow points from cause / source to effect / target
  • A line with no arrow is a two-way relationship
  • Node colour marks the concept’s primary discipline
20 concepts22 relationships28 disciplines5 relation families

At a glance

Recursion occurs when the definition of a concept or process depends on a simpler or previous version of itself.

Disciplines
Mathematics · Discrete Mathematics · Computer Science
Role in the graph
Cross-disciplinary bridge — reaches Algorithms, Logic, Software Engineering, Theory of Computation
Relationships
2 · 2 relation families
Mental models
2

What am I looking at?

In this lens (10)

Bridge concepts (49)

Just outside the lens — they connect it to other context.

Insights from this view

Structural observations about the concepts shown here — descriptions of this graph, not claims about the world.

  • This view connects 28 disciplines: Algorithms, Artificial Intelligence, Biochemistry, Bioinformatics, Biology, Cell Biology, Cognitive Science, Computational Biology, Computational Complexity, Computer Science, Data Structures, Design, Discrete Mathematics, Education, Educational Science, Evolutionary Biology, Genetics, History, Information Theory, Logic, Machine Learning, Mathematics, Molecular Biology, Numerical Analysis, Optimization, Software Engineering, Statistics, Theory of Computation.
  • Recursion is a bridge concept — viewed here through Computer Science, Discrete Mathematics, Mathematics.
  • The connections here span 5 relation families.
  • Information explains 7 concepts in this view (Algorithms, Artificial Intelligence, Biochemistry, Bioinformatics, Cell Biology, Computational Complexity, Computer Science, Data Structures, Discrete Mathematics, Evolutionary Biology, Genetics, History, Information Theory, Logic, Machine Learning, Mathematics, Molecular Biology, Software Engineering, Statistics, Theory of Computation).

Relationships as a list

The focused concept’s relationships. Pick another concept in the graph above to update this list.

Explore through a different lens

A lens is a deterministic projection of the graph. Pick a discipline, thinking pattern or journey to reframe the whole view.

By discipline

ChemistryBiologyPhysicsMathematicsComputer ScienceGeologyMineralogyEconomics

By thinking pattern

Bayesian updatingCause and effectCompoundingConservationConstraintsDefense in depthDiffusion & spreadEmergenceEnergy transformationEntropy & irreversibilityEquilibriumFeedback loopIncentivesInformationLevels & hierarchyModularityNetworksOptimizationOscillationProbabilityRecursion & self-similarityScaleSignal vs noiseSource–pathway–receptorStocks and flowsSymmetry & invarianceThresholds & tipping pointsTrade-offsTriangulationVariation & selectionWaves

By journey

From a Leaf to the ClimateWhy Music Moves UsHow Machines LearnReasoning about a Leaf and the Climate

Concept collections

Concept collections are curated lenses onto the fabric — themed sets of ideas that recur across disciplines. They are not journeys; they are a way to read the graph.

About this view

What this is

Start from one concept and expand outward. The view never shows everything at once — click a node to refocus, filter by relationship type, or switch to an accessible list.

One fabric

3750 concepts and 5051 typed relations form one connected component — no isolated silo.

How to read it

Focus a concept, or apply a lens (discipline, mental model, journey) to see only the threads that matter.