This work presents a theoretical architecture for continually adapting AI systems organized around three distinct timescales: (1) fast transformer key-value context for immediate interaction, (2) medium-term persistent recurrent memory with decaying importance and consolidation, and (3) slow, controlled parameter adapt...
Chaman Prakash Kanth· Zenodo (CERN European Organi...· 0 citations
This work presents a theoretical architecture for continually adapting AI systems organized around three distinct timescales: (1) fast transformer key-value context for immediate interaction, (2) medium-term persistent recurrent memory with decaying importance and consolidation, and (3) slow, controlled parameter adapt...
Chaman Prakash Kanth· Zenodo (CERN European Organi...· 0 citations
This work presents a theoretical architecture for continually adapting AI systems organized around three distinct timescales: (1) fast transformer key-value context for immediate interaction, (2) medium-term persistent recurrent memory with decaying importance and consolidation, and (3) slow, controlled parameter adapt...
Chaman Prakash Kanth· Zenodo (CERN European Organi...· 0 citations
This work presents a theoretical architecture for continually adapting AI systems organized around three distinct timescales: (1) fast transformer key-value context for immediate interaction, (2) medium-term persistent recurrent memory with decaying importance and consolidation, and (3) slow, controlled parameter adapt...
Chaman Prakash Kanth· Zenodo (CERN European Organi...· 0 citations
This work presents a theoretical architecture for continually adapting AI systems organized around three distinct timescales: (1) fast transformer key-value context for immediate interaction, (2) medium-term persistent recurrent memory with decaying importance and consolidation, and (3) slow, controlled parameter adapt...
Chaman Prakash Kanth· Zenodo (CERN European Organi...· 0 citations
This work presents a theoretical architecture for continually adapting AI systems organized around three distinct timescales: (1) fast transformer key-value context for immediate interaction, (2) medium-term persistent recurrent memory with decaying importance and consolidation, and (3) slow, controlled parameter adapt...
Chaman Prakash Kanth· Zenodo (CERN European Organi...· 0 citations
This work presents a theoretical architecture for continually adapting AI systems organized around three distinct timescales: (1) fast transformer key-value context for immediate interaction, (2) medium-term persistent recurrent memory with decaying importance and consolidation, and (3) slow, controlled parameter adapt...
Chaman Prakash Kanth· Zenodo (CERN European Organi...· 0 citations
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