diff --git a/content/_index.md b/content/_index.md index 914451ae4..abe26d46d 100644 --- a/content/_index.md +++ b/content/_index.md @@ -11,11 +11,19 @@ It’s our mission to realize this future. ## Blog -[[Extrusion 01.24]] [[Honcho; User Context Management for LLM Apps|Honcho: User Context Management for LLM Apps]] [[blog/Theory-of-Mind Is All You Need]] [[blog/Open-Sourcing Tutor-GPT]] +## Extrusions + +[[extrusions/Extrusion 01.24|Extrusion 01.24]] +## Notes + +[[Honcho name lore]] +[[Metacognition in LLMs is inference about inference]] +[[The machine learning industry is too focused on general task performance]] + ## Research [Violation of Expectation Reduces Theory-of-Mind Prediction Error in Large Language Models](https://arxiv.org/pdf/2310.06983.pdf) diff --git a/content/blog/Extrusion 01.24.md b/content/extrusions/Extrusion 01.24.md similarity index 97% rename from content/blog/Extrusion 01.24.md rename to content/extrusions/Extrusion 01.24.md index 9aecf4649..4ba95f7f0 100644 --- a/content/blog/Extrusion 01.24.md +++ b/content/extrusions/Extrusion 01.24.md @@ -6,7 +6,7 @@ No one needs another newsletter, so we'll work to make these worthwhile. Expect ## 2023 Recap -Last year was wild. We started as an edtech company and ended as anything but. There's a deep dive on some of the conceptual lore in last week's blog post, "[[Honcho; User Context Management for LLM Apps]]": +Last year was wild. We started as an edtech company and ended as anything but. There's a deep dive on some of the conceptual lore in last week's "[[Honcho; User Context Management for LLM Apps|Honcho: User Context Management for LLM Apps]]": >[Plastic Labs](https://plasticlabs.ai) was conceived as a research group exploring the intersection of education and emerging technology...with the advent of ChatGPT...we shifted our focus to large language models...we set out to build a non-skeuomorphic, AI-native tutor that put users first...our [[Open-Sourcing Tutor-GPT|experimental tutor]], Bloom, [[Theory-of-Mind Is All You Need|was remarkably effective]]--for thousands of users during the 9 months we hosted it for free... diff --git a/content/notes/The machine learning industry is too focused on general task performance.md b/content/notes/The machine learning industry is too focused on general task performance.md index 6b00d111d..8965fa308 100644 --- a/content/notes/The machine learning industry is too focused on general task performance.md +++ b/content/notes/The machine learning industry is too focused on general task performance.md @@ -4,4 +4,4 @@ However, general capability doesn't necessarily translate to completing tasks as Take summarization. It’s a popular machine learning task at which models have become quite proficient, at least from a benchmark perspective. However, when models summarize for users with a pulse, they fall short. The reason is simple: the models don’t know this individual. The key takeaways for a specific user differ dramatically from the takeaways _any possible_ internet user _would probably_ note. -So a shift in focus toward user-specific task performance would provide a much more dynamic & realistic approach. Catering to individual needs & paving she way for more personalized & effective ML applications. +So a shift in focus toward user-specific task performance would provide a much more dynamic & realistic approach. Catering to individual needs & paving the way for more personalized & effective ML applications.