Table 2.

Future advances in AI.

Method	Description
	Uses decentralized training where a global model is trained on locally-stored data and then updated while preserving the privacy of local data.
	To calculate an uncertainty estimate for model predictions so model confidence can be interpreted by end user.
	Allows the use of multiple types of data to train a combined model to take advantage of unique differences in data.
	Enables a model to continue learning on a new stream of data.
	Model is used to train compressed representations of data so new instances can be recreated.
	Model uses text based prompt to generate a response based on language based learning.