The growing imbalance between the amount of data that needs to be processed to train large language models (LLMs) and the inability to move that data back and forth fast enough between memories and ...
Memory-enabled artificial intelligence agents that can store and recall user data for more intelligent and personalized decision-making are vulnerable to memory injection attacks that can manipulate ...
What if the future of artificial intelligence is being held back not by a lack of computational power, but by a far more mundane problem: memory? While AI’s computational capabilities have skyrocketed ...
The research project promises more efficient long-term recall by organizing knowledge around abstractions and cue-based ...
Web3 lacks a dedicated memory layer, making its current architecture inefficient and difficult to scale. Random Linear Network Coding (RLNC) offers a solution by enhancing data propagation and storage ...
If we want to avoid making AI agents a huge new attack surface, we’ve got to treat agent memory the way we treat databases: with firewalls, audits, and access privileges. The pace at which large ...
Quantum computers still face limits when it comes to storing information. Researchers at ETH Zurich are now turning to ...
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