- AI · arxiv/cs.LG · 8 min
Mixed Precision Training Stabilizes Neural ODEs
Researchers demonstrate a framework that reduces memory use by 50% and speeds up neural ODE training 2x by carefully mixing low and high precision arithmetic.
May 3, 2026 Read → → - AI · arxiv/cs.LG · 4 min
Selective-Update RNNs Match Transformers While Using Less Memory
A new RNN architecture learns when to update internal state, preserving memory across long sequences and reducing computational waste on redundant input.
May 3, 2026 Read → → - AI · arxiv/cs.AI · 8 min
Schema-Grounded Memory Outperforms Search-Based AI Recall
Treating AI memory as a structured database rather than a retrieval problem improves accuracy and reliability for production agents.
May 1, 2026 Read → → - AI · hackernoon · 6 min
Continuity in AI agents requires architecture, not bigger memory stores
A solo builder argues that persistent AI identity depends on scheduled cognition cycles and narrative compression, not retrieval systems.
April 30, 2026 Read → → - AI · arxiv/cs.AI · 6 min
OjaKV: Online Low-Rank Compression for LLM Key-Value Caches
A hybrid storage and adaptive subspace method reduces KV cache memory by compressing intermediate tokens while preserving critical anchors, compatible with FlashAttention.
April 20, 2026 Read → →