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## Blog
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## Blog
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[[Extrusion 01.24]]
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[[Honcho; User Context Management for LLM Apps|Honcho: User Context Management for LLM Apps]]
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[[Honcho; User Context Management for LLM Apps|Honcho: User Context Management for LLM Apps]]
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[[blog/Theory-of-Mind Is All You Need]]
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[[blog/Theory-of-Mind Is All You Need]]
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[[blog/Open-Sourcing Tutor-GPT]]
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[[blog/Open-Sourcing Tutor-GPT]]
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Welcome to the inaugural edition of Plastic Labs' "Extrusions," a monthly prose-form synthesis of what we've been chewing on. No one needs another curation newsletter, so expect these to be densely linked glimpses into the thought-space of our organization. And if you like, [you can engage with the ideas directly](https://github.com/plastic-labs/blog).
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## 2023 Recap
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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]]":
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>[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...
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Building a production-grade, user-centric AI application, then giving it nascent [theory of mind](https://arxiv.org/pdf/2304.11490.pdf) and [[Metacognition in LLMs is inference about inference|metacognition]], made it glaringly obvious to us that social cognition in LLMs was both under-explored and under-leveraged.
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We pivoted to address this hole in the stack and build the user context management solution agent developers need to truly give their users superpowers. Plastic applied and was accepted to [Betaworks](https://www.betaworks.com/)' [AI Camp: Augment](https://techcrunch.com/2023/08/30/betaworks-goes-all-in-on-augmentative-ai-in-latest-camp-cohort-were-rabidly-interested/?guccounter=1):
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<iframe src="https://player.vimeo.com/video/868985592?h=deff771ffe&color=F6F5F2&title=0&byline=0&portrait=0" width="640" height="360" frameborder="0" allow="autoplay; fullscreen; picture-in-picture" allowfullscreen></iframe>
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We spent camp in a research cycle, then [published pre-print](https://arxiv.org/abs/2310.06983) showing it's possible to enhance LLM theory of mind ability with [predictive coding-inspired](https://js.langchain.com/docs/use_cases/agent_simulations/violation_of_expectations_chain) [metaprompting](https://arxiv.org/abs/2102.07350).
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<iframe width="560" height="315" src="https://www.youtube.com/embed/PbuzqCdY0hg?si=OSujtqg44AK3y_W-" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
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Then it was back to building.
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## 2024 Roadmap
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2024 will be the year of Honcho. Check out the new site we're launching today.
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![[honcho logo and text.png]]
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Last week [[Honcho; User Context Management for LLM Apps|we released]] the...
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>...first iteration of [[Honcho name lore|Honcho]], our project to re-define LLM application development through user context management. At this nascent stage, you can think of it as an open-source version of the OpenAI Assistants API. Honcho is a REST API that defines a storage schema to seamlessly manage your application's data on a per-user basis. It ships with a Python SDK which [you can read more about how to use here](https://github.com/plastic-labs/honcho/blob/main/README.md).
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And coming up, you can expect a lot more:
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- Next we'll drop a fresh paradigm for constructing agent cognitive architectures with users at the center, replete with cookbooks, integrations, and examples
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- After that, we've got some dev viz tooling in the works that allows anyone to quickly grok all the inferences and context at play in a conversation, compare sessions, and visualize and manipulate entire architectures--as well as swap and compare the performance of custom architectures across the landscape of models
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- Finally, we'll bundle the most useful of all this into an offering of managed, hosted services
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## Keep in Touch
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Thanks for reading.
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You can find is on [X/Twitter](https://twitter.com/plastic_labs), but we'd really like to see you in our [Discord](https://discord.gg/plasticlabs) 🫡.
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{
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{
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"name": "@jackyzha0/quartz",
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"name": "@jackyzha0/quartz",
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<<<<<<< HEAD
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"version": "4.1.2",
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"version": "4.1.2",
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=======
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"version": "4.1.0",
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>>>>>>> f8d1298d (fix: missing field in config)
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"lockfileVersion": 3,
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"requires": true,
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"packages": {
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"name": "@jackyzha0/quartz",
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<<<<<<< HEAD
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"version": "4.1.2",
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=======
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"version": "4.1.0",
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>>>>>>> f8d1298d (fix: missing field in config)
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"license": "MIT",
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"license": "MIT",
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"dependencies": {
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"dependencies": {
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"@clack/prompts": "^0.6.3",
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"@clack/prompts": "^0.6.3",
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}
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