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  2. Venn diagram - Wikipedia

    en.wikipedia.org/wiki/Venn_diagram

    A Venn diagram is a widely used diagram style that shows the logical relation between sets, popularized by John Venn (1834–1923) in the 1880s. The diagrams are used to teach elementary set theory, and to illustrate simple set relationships in probability, logic, statistics, linguistics and computer science.

  3. You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  4. File:Venn diagram rgb.svg - Wikipedia

    en.wikipedia.org/wiki/File:Venn_diagram_rgb.svg

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses ...

  5. File:LogicGates.svg - Wikipedia

    en.wikipedia.org/wiki/File:LogicGates.svg

    File information Description Venn Diagrams Representing all Intersectional Logic Gates Between Two Inputs. Based on Image:LogicGates.jpg.. Source I (ZanderSchubert ()) created this work entirely by myself.

  6. Canva - Wikipedia

    en.wikipedia.org/wiki/Canva

    On December 7, 2022, Canva launched Magic Write, which is the platform’s AI-powered copywriting assistant. [33] On March 22, 2023, Canva announced its new Assistant tool, which makes recommendations on graphics and styles that match the user's existing design. [34] On January 11, 2024, Canva launched its own GPT in OpenAI's GPT Store. [35]

  7. Information diagram - Wikipedia

    en.wikipedia.org/wiki/Information_diagram

    Information diagrams have also been applied to specific problems such as for displaying the information theoretic similarity between sets of ontological terms. [ 3 ] Venn diagram showing additive and subtractive relationships among various information measures associated with correlated variables X and Y .