Fire360 introduces a 50-hour 360-degree video benchmark where vision-language models trail humans by over 40 points on recognizing fire-damaged objects and answering safety questions.
Episodic memory in AI agents poses risks that should be studied and mitigated
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abstract
Most current AI models have little ability to store and later retrieve a record or representation of what they do. In human cognition, episodic memories play an important role in both recall of the past as well as planning for the future. The ability to form and use episodic memories would similarly enable a broad range of improved capabilities in an AI agent that interacts with and takes actions in the world. Researchers have begun directing more attention to developing memory abilities in AI models. It is therefore likely that models with such capability will be become widespread in the near future. This could in some ways contribute to making such AI agents safer by enabling users to better monitor, understand, and control their actions. However, as a new capability with wide applications, we argue that it will also introduce significant new risks that researchers should begin to study and address. We outline these risks and benefits and propose four principles to guide the development of episodic memory capabilities so that these will enhance, rather than undermine, the effort to keep AI safe and trustworthy.
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
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Fire360: A Benchmark for Robust Perception and Episodic Memory in Degraded 360-Degree Firefighting Videos
Fire360 introduces a 50-hour 360-degree video benchmark where vision-language models trail humans by over 40 points on recognizing fire-damaged objects and answering safety questions.