<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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Thinking drafts

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

The Best Programming Language Today is English: How to get Vibe Coding and make software without being a programmer

All art is conceptual art: Reflections on the aftershocks of an AI image-generation earthquake

From frontier to utility: Prompts to test capabilities of Large Language Models

Guides and frameworks

AI Competence Framework and Task Evaluation Cards

Other resources

Weird Semantics: What are Large Language Models Actually Models Of?

Dominik’s AI Hackathon Ideas