New agentic memory framework uses 118K tokens per query. LangMem burns through 3.26M.

NUS researchers' MRAgent framework reduces LLM agent memory retrieval to 118K tokens per query — vs. 3.26M for LangMem — using step-by-step reasoning.
InfoQ

Redis Improves Performance of Vector Semantic Search with Multi-Threaded Query Engine

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VentureBeat

Beyond RAG: SEARCH-R1 integrates search engines directly into reasoning models

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Large language models (LLMs) have seen ...