Tokenization: How LLMs Turn Text Into Something They Can Process
You type a sentence and assume the model receives it as you wrote it. It does not. What actually happens to your text before the model ever sees it.
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You type a sentence and assume the model receives it as you wrote it. It does not. What actually happens to your text before the model ever sees it.
What a large language model actually is, and why these models are called 'large' — the foundation piece, before tokenization and everything built on top of it.
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Senior MLOps & LLMOps Engineer with 6+ years in AI. At Unifonic she is the central MLOps/LLMOps support across AI teams — agentic products with LangGraph and MCP, LLM evaluation and observability, and 30B+ model serving on Kubernetes. She designed and teaches "Production ML Engineering" at ITI, and built Valeo's first production RAG system.

AI Engineer working on 3D perception and generative AI, with 5+ years building deep learning pipelines for autonomous systems. Leads the 3D perception stack at Wakeb Data and previously productionised LiDAR simulation models at Valeo. Completing an MSc in Informatics at Nile University.

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