AI & ML Research 24 Hours

Last updated: June 14, 2026, 11:37 AM ET

AI & ML Research

Analyzing GPU time-slicing costs on Kubernetes reveals hidden microarchitectural overhead that raises latency for co‑located LLM agents, prompting a rethink of container‑orchestration policies for Agentic AI workloads. Evaluating RAG context limits shows that simply expanding the retrieval window does not improve accuracy on aggregation tasks and instead masks errors, leading the author to benchmark traditional pipelines against a deterministic filter that restores reliable output.