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  2. Memory model (programming) - Wikipedia

    en.wikipedia.org/wiki/Memory_model_(programming)

    The memory model stipulates that changes to the values of shared variables only need to be made visible to other threads when such a synchronization barrier is reached. Moreover, the entire notion of a race condition is defined over the order of operations with respect to these memory barriers.

  3. List of artificial intelligence projects - Wikipedia

    en.wikipedia.org/wiki/List_of_artificial...

    LaMDA, a family of conversational neural language models developed by Google. [61] LLaMA, a 2023 language model family developed by Meta that includes 7, 13, 33 and 65 billion parameter models. Mycroft, a free and open-source intelligent personal assistant that uses a natural language user interface. [62]

  4. Hyperparameter (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Hyperparameter_(machine...

    In machine learning, a hyperparameter is a parameter that can be set in order to define any configurable part of a model's learning process. Hyperparameters can be classified as either model hyperparameters (such as the topology and size of a neural network) or algorithm hyperparameters (such as the learning rate and the batch size of an optimizer).

  5. Parameter - Wikipedia

    en.wikipedia.org/wiki/Parameter

    Parameters in a model are the weight of the various probabilities. Tiernan Ray, in an article on GPT-3, described parameters this way: A parameter is a calculation in a neural network that applies a great or lesser weighting to some aspect of the data, to give that aspect greater or lesser prominence in the overall calculation of the data.

  6. Expectation–maximization algorithm - Wikipedia

    en.wikipedia.org/wiki/Expectation–maximization...

    The parameters are continuous, and are of two kinds: Parameters that are associated with all data points, and those associated with a specific value of a latent variable (i.e., associated with all data points whose corresponding latent variable has that value). However, it is possible to apply EM to other sorts of models.

  7. Neural scaling law - Wikipedia

    en.wikipedia.org/wiki/Neural_scaling_law

    Suppose the model has parameter count , and after being finetuned on Python tokens, it achieves some loss . We say that its "transferred token count" is D T {\displaystyle D_{T}} , if another model with the same N {\displaystyle N} achieves the same L {\displaystyle L} after training on D F + D T {\displaystyle D_{F}+D_{T}} Python tokens.

  8. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Heating and cooling requirements given as a function of building parameters. Building parameters given. 768 Text Classification, regression 2012 [212] [213] A. Xifara et al. Airfoil Self-Noise Dataset A series of aerodynamic and acoustic tests of two and three-dimensional airfoil blade sections. Data about frequency, angle of attack, etc., are ...

  9. Bidirectional associative memory - Wikipedia

    en.wikipedia.org/wiki/Bidirectional_associative...

    The memory or storage capacity of BAM may be given as (,), where "" is the number of units in the X layer and "" is the number of units in the Y layer. [3]The internal matrix has n x p independent degrees of freedom, where n is the dimension of the first vector (6 in this example) and p is the dimension of the second vector (4).