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Continue reading →: What is Tokenization?
LLMs don’t work with words the way we do. They break language into tokens—pieces that can be smaller or larger than words—and use those to learn and generate text. This post walks through what tokenization is, why it matters, and how it shapes everything from model behavior to prompt limits.
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Continue reading →: Understanding and Overcoming the Static, Stateless Nature of LLMs
This post demystifies how AI like ChatGPT works, explaining that the core model is static and forgetful. It reveals how the application around it creates the illusion of memory and conversation, and how developers work around these inherent limitations.
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Continue reading →: The Static, Stateless, and Directional Nature of LLMs
This article breaks down three core concepts of LLMs: their static knowledge, their stateless nature, and their one-directional text generation, clarifying common misconceptions about how AI like ChatGPT actually works.
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Continue reading →: Beyond the Hype: A Technical Look at the Limits of Transformer AI
A technical overview of how LLM models work, explaining their static architecture, pattern-matching basis, and fundamental limitations that separate them from true reasoning or AGI.
Who is AightBits?
Dave Ziegler
I’m a full-stack AI/LLM practitioner and solutions architect with 30+ years enterprise IT, application development, consulting, and technical communication experience.
While I currently engage in LLM consulting, application development, integration, local deployments, and technical training, my focus is on AI safety, ethics, education, and industry transparency.
Open to opportunities in technical education, system design consultation, practical deployment guidance, model evaluation, red teaming/adversarial prompting, and technical communication.
My passion is bridging the gap between theory and practice by making complex systems comprehensible and actionable.
Founding Member, AI Mental Health Collective
Community Moderator / SME, The Human Line Community
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