Memory Architecture Is the Next Target in AI Engineering
To build truly agent-native systems, we need to stop feeding the LLM “snapshots” and start giving it a persistent architecture for memory.
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Running RAG & Semantic Search… Locally!
One of the challenges I’ve faced with vector databases like Chroma DB is how heavy they can get even with a handful of small PDFs. I have seen them consume 180+ MB once vectorized. Great for experimentation, but not exactly lightweight or (work) laptop‑friendly. Those who have been following me, know that I am a…
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Knowledge Bridging in LLMs via Attention Mechanism
As AI continues to revolutionize industries, one challenge remains: integrating domain-specific knowledge into Large Language Models (LLMs) without constant retraining. Enter KBLAM — a breakthrough approach that seamlessly augments LLMs with your company’s unique knowledge base, making AI more efficient, dynamic, and reliable. All without a separate search systems.