4 results about "Category specific" patented technology

Methods and systems are provided for managing private data access for resolving a query. The system, e.g., accesses private data generated by a plurality of distinct applications associated with a user and inputs the data into a data classification model. The model classifies the private data into specific data categories based on data type. The classified data is then aggregated into a dataspace, which serves as a unified repository for private data corresponding to a specific category collected from the distinct applications. A unique access configuration is associated with the dataspace to define a set of authorized connection types permitted to access the repository. In response to a query requiring the private data, access to the dataspace is provided if the requesting entity matches the authorized connection types defined in the unique access configuration.

The present disclosure provides systems and methods for hierarchical multi-level model distillation that create specialized artificial intelligence models from large language models. A hierarchy for generating specialized generative models from a large language model is determined, including models associated with different categories and complexity levels for tasks with varying computational requirements. The specialized models are trained using the large language model based on specific categories to provide responses to category-related requests. Each model is pruned based on complexity levels to enable responses to requests of varying complexity. The models are quantized from common precision factors to corresponding precision factors associated with complexity levels. Deployment locations are determined for each pruned model based on complexity levels. Specialized models are transmitted to corresponding locations for deployment across diverse computational environments.

To provide a gaming machine that can improve the enjoyment of the game. [Solution] A gaming machine comprising: a win / fail lottery means that performs a win / fail lottery triggered by the fulfillment of predetermined conditions; an effect execution means that performs a variation effect from the start of variation of decorative symbols for notifying the win / fail lottery result by the win / fail lottery means until it stops in a manner corresponding to the win / fail lottery result; and a customization function that allows the player to arbitrarily change the probability of occurrence of some effects that may occur during the variation effect, wherein the customization function is provided as a specific customization for which multiple types of target effects are subject to customization, and the customization image displayed when using the specific customization indicates that specific attribute effects belonging to a specific category are subject to customization, and effect α, which is one of the multiple types of target effects, is a non-specific attribute effect that does not belong to the specific category.

This invention discloses a privileged learning classification method based on category awareness and interpretability guidance, belonging to the field of artificial intelligence and machine learning. The method includes: first, dividing the training data into a privileged set containing complete information and a non-privileged set containing only source domain features; for a specific category, extracting feature importance through interpretability analysis and sparsifying it to generate a category-specific weight vector; then, calculating the weighted similarity between non-privileged samples and similar samples in the privileged set based on this weight vector, retrieving and transferring the privileged features of the best-matching sample as reconstructed features, and dynamically assigning confidence coefficients negatively correlated with similarity; finally, fusing real and reconstructed privileged features to construct a joint optimization objective function with an adaptive penalty mechanism for confidence coefficients for model training. This invention effectively improves the classification accuracy and robustness of the model in scenarios where some privileged information is missing.