ideas to implement a model database

Let’s use a dog as an example

  • each model can potentially cause an agent to move or change in an imagined environment
  • language definition is stored
  • each model has the ability to compose with other models
  • each model the ability to be used in other environment
  • there are core or base models in which the majority of other models are built off
  • there are deep learning vision classifiers associated with many of the models
  • some form of grounded representation, whether that is a vector, sequence, grid cell like representation, or something else. Maybe that just means movement from above.
  • there are visual generative models that can be combined with other models
  • models can be simulated to run in a “causality engine”
  • many models can act as a computational function. “dogify”
  • new models can be added to the database
  • models are probabilistic
  • model information can link to the web, wikipedia, or other data source

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