The article discusses the development of the TTM model at IBM Research, which employs a multi-level architecture designed for enhanced accuracy and efficiency in AI forecasting. Key components include the TTM Backbone, built on TSMixer architecture that enables effective feature mixing, and a smaller TTM Decoder. The model also includes a Forecast Head for output production and an Optional Exogenous Mixer for integrating external data into the forecasting mechanism. The refactoring approach allows for flexibility in model behavior according to different workflows.
TTM employs a multi-level architecture with advanced components like the TTM Backbone and Decoder, enhancing accuracy and efficiency in AI forecasting tasks.
The TTM Backbone is built using efficient TSMixer architecture, significantly improving feature mixing while minimizing computational resources compared to traditional models.
#ai-model-development #multi-level-architecture #forecasting-techniques #machine-learning #ibm-research
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