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What I learned after removing all the abstractions and building the architecture underneath GPT from scratch.
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A unified mental model of embedding, classification, and detection in deep vision systems
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Before you argue about embedding models, answer the one question that actually decides your retrieval architecture.
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Why the smartest model in the room is almost never the reason AI projects fail.
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A deep dive into how modern AI voice agents work using Twilio, SIP, PBX systems, RTP streaming, IVR routing, and realtime AI infrastructure.
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How to build a mental model that works across text, images, and object detection
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Why LLMs should write SQL, not guess KPIs from retrieved chunks.