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Quick, Draw! is an online guessing game developed and published by Google that challenges players to draw a picture of an object or idea and then uses a neural network artificial intelligence to guess what the drawings represent. [2] [3] [4] The AI learns from each drawing, improving its ability to guess correctly in the future. [3]
When QKV attention is used as a building block for an autoregressive decoder, and when at training time all input and output matrices have rows, a masked attention variant is used: (,,) = (+) where the mask, is a strictly upper triangular matrix, with zeros on and below the diagonal and in every element above the diagonal.
20Q is a computerized game of twenty questions that began as a test in artificial intelligence (AI). It was invented by Robin Burgener in 1988. [1] The game was made handheld by Radica in 2003, but was discontinued in 2011 because Techno Source took the license for 20Q handheld devices.
Multi-head attention enhances this process by introducing multiple parallel attention heads. Each attention head learns different linear projections of the Q, K, and V matrices. This allows the model to capture different aspects of the relationships between words in the sequence simultaneously, rather than focusing on a single aspect.
Kahoot! is a Norwegian online game-based learning platform. [3] It has learning games, also known as "kahoots", which are user-generated multiple-choice quizzes that can be accessed via a web browser or the Kahoot! app. [4] [5]
The game follows the rise of a self-improving AI tasked with maximizing paperclip production, [6] a directive it takes to the logical extreme. An activity log records the player’s accomplishments while giving glimpses into the AI's occasionally unsettling thoughts. [7] [failed verification] All game interaction is done through pressing buttons.
Will Howard threw two touchdown passes to freshman Jeremiah Smith and Ohio State routed Tennessee 42-17 on Saturday night in a first-round College Football Playoff game, setting up a New Year's ...
Multiheaded attention, block diagram Exact dimension counts within a multiheaded attention module. One set of (,,) matrices is called an attention head, and each layer in a transformer model has multiple attention heads. While each attention head attends to the tokens that are relevant to each token, multiple attention heads allow the model to ...