The Counterfactual
Sean TrottCognitive Science, statistics, AI.
| Platform |  | Pricing | Freemium | Publishes | Weekly |
|---|---|---|---|---|---|
| Issues | 108 | Founded | 4 years ago | Last Issue | 9 days ago |
| Active | |||||
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seantrott.substack.comLatest Issues
Bad habits
In July of 2022—now almost four years ago—I wrote about the possibility that large language models (LLMs) could change the way we use language. This was pre-ChatGPT, but after the release of GPT-3. It was a strange liminal period for resear...
The problem of induction (heads), pt. II
In my last post, I discussed research on induction heads: parts of large language models (LLMs) that learn to attend to repeated sequences in the context and enable LLMs to copy strings of text.
I suggested that as scientific constructs,...
The problem of induction (heads), pt. I
A key aim of mechanistic interpretability research is to identify which internal components of a neural network—like a large language model (LLM)—produce observable behaviors.
Explanations, here, typically reference specific model compone...
Why benchmarks don't resolve disagreements
There are a number of epistemological challenges involved in the study of Large Language Models (LLMs). Foremost among them is evaluation: determining what LLMs can and can’t do is hard, and discussion of their capabilities is thus rife wit...
Language models and the intentional stance
Humans often grapple with new concepts by way of metaphor or analogy. These days, many people (including myself) are struggling with the question of how to properly conceive of systems like large language models (LLMs). As I’ve written befo...
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The writers behind this newsletter.
Assistant Professor at UC San Diego.
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