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Time-Series Optimized Transformer for Observability (TOTO)

发明专利审中
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20权利要求 · 1 独立
§ Ⅰ

卷宗概要

发明人

Benjamin Jacob Cohen; Emaad Ali Khwaja; Viktoriya Zhukova; Othmane Abou-Amal

IPC 分类

G6N 3/985G6N 3/45G6N 3/499

CPC 分类

G6N3/985G6N3/45G6N3/499

The present disclosure describes technology for training and deploying time-series optimized transformers for observability (TOTO). The system may process multivariate time-series data using an artificial intelligence (AI) model. The model may include a patch embedding layer and a transformer architecture. The patch embedding layer is configured to receive the multivariate time-series data and output patch embeddings. The transformer architecture is configured to process the output patch embeddings and output transformed embeddings. The transformer architecture may include segments, with each segment including at least one space-wise block and a configurable number of time-wise blocks.

原文(中文)

The present disclosure describes technology for training and deploying time-series optimized transformers for observability (TOTO). The system may process multivariate time-series data using an artificial intelligence (AI) model. The model may include a patch embedding layer and a transformer architecture. The patch embedding layer is configured to receive the multivariate time-series data and output patch embeddings. The transformer architecture is configured to process the output patch embeddings and output transformed embeddings. The transformer architecture may include segments, with each segment including at least one space-wise block and a configurable number of time-wise blocks.