Tag: text
What's a Model?
2025-09-01 alignment basics theory text Gemma hallucination What do we actually mean when we talk about a "model"? Where do they come from? How much do they cost? What are prompts, loss functions, and fine-tuning? This extra-long introductory talk covers some of the basic concepts in the AI landscape, with a special focus on chatbots. Access: Public
Rotary Position Encoding
2025-08-18 basics text AIAYN tokenization I review position encoding - why it's needed, and how classic Transformers do it - and then go in detail into the Rotary Positioning Embedding (RoPE) enhancement to position encoding. RoPE is widely used in recent large language models. Access: $ Basic
Believable sampling with Mirostat
2025-08-11 basics text sampling It's often hard to choose the right sampling parameters for language generation. This paper introduces Mirostat, a technique for adaptively choosing the value of "k" in top-k sampling to give easier and more consistent control over the information density of the output. Access: $ Basic
Rappaccini's language model
2025-08-01 alignment text toxicity There's a lot of talk about generative models producing "toxic" output; but what does that actually mean? How can we measure it or prevent it, and is it even a good idea to try? Access: $$$ Pro
The road to MoE
2025-08-01 model-intro text DeepSeek MoE General coverage of the "Mixture of Experts" (MoE) technique, and specific details of DeepSeek's "fine-grained expert segmentation" and "shared expert isolation" enhancements to it, as well as some load-balancing tricks, all of which went into their recently-notable model. Access: $$$ Pro
Bidirectional attention and BERT: Taking off the mask
2025-08-01 model-intro text BERT attention Introduction to BERT, a transformer-type model with bidirectional attention, suited to interesting tasks other than plain generation. This was one of the first powerful models to have open weights; and it remains a common baseline to which new models can be compared. Access: $ Basic
Grammar is all you get
2025-08-01 model-intro basics text AIAYN attention An overview of the classic "Attention is all you need" paper, with focus on the attention mechanism and its resemblance to dependency grammar. Access: $ Basic
Cheap fine-tuning with LoRA
2025-08-01 basics training text image GPT LoRA Rather than re-training the entire large matrices of a model, we can train smaller, cheaper adjustments that function like software patches. Access: $$$ Pro
Better (than) tokenization with BLTs
2025-08-01 theory text LLaMA tokenization Using "patches" of input bytes, instead of a fixed token list, allows better scalability and improves performance on some tasks that are hard for token-based LLMs. Access: $ Basic
Generate and read: Oh no they didn't
2025-05-21 prompting text GPT RAG hallucination What if instead of looking up facts in Wikipedia, you just used a language model to generate fake Wikipedia articles? Access: Public