Google outlines MIRAS and Titans, a possible path toward continuously learning AI

A year after publishing its Titans paper, Google has formally detailed the architecture on its research blog, pairing it with a new framework called MIRAS. Both projects target a major frontier in AI: models that keep learning during use and maintain a functional long-term memory instead of remaining static after pretraining.

Google frames the motivation in familiar terms. Traditional Transformers struggle with very long inputs like books, genome sequences, or extended videos because their computational cost grows quadratically with context length. Faster alternatives such as modern RNNs or…