<aside> <img src="/icons/help-alternate_gray.svg" alt="/icons/help-alternate_gray.svg" width="40px" /> Collection of drafts to exploring different ways of looking at and thinking about Large Language Models. Unless otherwise noted, all written by Dominik Lukeš.
A companion to more practical guides on OLD Integrating AI into Academic Practice: Guide to Reflective Exploration
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Semantic Machines: A quick introduction to thinking about generative AI [DRAFT]
How does ChatGPT read your text: RAG and Context Window
What does it mean for an AI model to be trained? Five frequently confused uses of “training”
LLMs, Attention and Working Memory
Towards a periodicization of AI history
How do LLMs know the meaning of words: Exploring the limits of purely relational semantics
What do machines need us for? Dexterity, judgment and intentionality
"Look Ma, no hands!" A brief history of vague agentic extrapolation in AI
All art is conceptual art: Reflections on the aftershocks of an AI image-generation earthquake
Creation is perception: On the role of skill in the age of AI
From frontier to utility: Prompts to test capabilities of Large Language Models
AI Competence Framework and Task Evaluation Cards
Weird Semantics: What are Large Language Models Actually Models Of?