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2. Maze generation algorithm - Wikipedia

   en.wikipedia.org/wiki/Maze_generation_algorithm

   This algorithm, also known as the "recursive backtracker" algorithm, is a randomized version of the depth-first search algorithm. Frequently implemented with a stack, this approach is one of the simplest ways to generate a maze using a computer. Consider the space for a maze being a large grid of cells (like a large chess board), each cell ...

3. DALL-E - Wikipedia

   en.wikipedia.org/wiki/DALL-E

   t. e. DALL·E, DALL·E 2, and DALL·E 3 (pronounced DOLL-E) are text-to-image models developed by OpenAI using deep learning methodologies to generate digital images from natural language descriptions known as "prompts". The first version of DALL-E was announced in January 2021. In the following year, its successor DALL-E 2 was released.

4. AI boom - Wikipedia

   en.wikipedia.org/wiki/AI_boom

   The AI boom, [1][2] or AI spring, [3][4] is an ongoing period of rapid progress in the field of artificial intelligence (AI) that started in the late 2010s before gaining international prominence in the early 2020s. Examples include protein folding prediction led by Google DeepMind and generative AI applications developed by OpenAI.

5. Erdős–Rényi model - Wikipedia

   en.wikipedia.org/wiki/Erdős–Rényi_model

   e. In the mathematical field of graph theory, the Erdős–Rényi model refers to one of two closely related models for generating random graphs or the evolution of a random network. These models are named after Hungarian mathematicians Paul Erdős and Alfréd Rényi, who introduced one of the models in 1959. [1][2] Edgar Gilbert introduced the ...

6. Desmos - Wikipedia

   en.wikipedia.org/wiki/Desmos

   Desmos was founded by Eli Luberoff, a math and physics double major from Yale University, [3] and was launched as a startup at TechCrunch 's Disrupt New York conference in 2011. [4] As of September 2012, it had received around 1 million US dollars of funding from Kapor Capital, Learn Capital, Kindler Capital, Elm Street Ventures and Google ...

7. Graph neural network - Wikipedia

   en.wikipedia.org/wiki/Graph_neural_network

   t. e. A graph neural network (GNN) belongs to a class of artificial neural networks for processing data that can be represented as graphs. [1][2][3][4][5] Basic building blocks of a graph neural network (GNN). Permutation equivariant layer. Local pooling layer. Global pooling (or readout) layer. Colors indicate features.