Firehose

This paper introduces a new type of AI model called memory foundation models, which allows the model to learn and retain information internally, rather than relying on external memory modules. This could be useful for practitioners who want to build more efficient and flexible AI agents.

This paper evaluates how multimodal large language models use intermediate visual states during reasoning and finds that these visual states are not as crucial as previously thought, but can still impact model performance under certain conditions. Practitioners might care because understanding how these models use visual states can help improve their performance and reliability.