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AI meeting summary: The transcript is a recording of an introductory session for a decentralized science project called Active Blockfrince. Participants introduce themselves and their interests in AI, web three protocols, political science, and biodiversity modeling. The session will involve applying the active entity ontology for Science (AOS) to generate a generalized notation model of an AOS DSI system and publishing it on Zenodo as co-authors. The goal is to explore incense making and acting in various settings using flexible modeling methods like active inference and Cadcad framework simulations. The transcript discusses Cadcad, a system for complex systems simulation. It explains how Cadcad is used to track and change parameters in simulations, with applications ranging from hydroelectric dams to economic systems. The active blockfronts add cognitive modeling as a bottom-up microagentic framework into Cadcad. The transcript also introduces active inference, a first-principles framework for perception and action that can be applied to different decision-making entities such as artificial intelligence or even the liver. AOS is an active entity ontology for science that organizes informational entities (static knowledge objects) and active entities (decision-making entities). The transcript discusses the use of active inference and generative modeling to describe multiscale systems, including nested entities such as humans, teams, organizations, and universities. The framework provides a tool for perception and action that can be used to build specific models for different systems of interest. The discussion also includes the importance of considering all relevant entities and pieces of information when developing a model, including interfaces between agents. The group then drafts a pseudocode summary of a situation they want to model - onboarding participants into the Token Engineering Commons community of practice. During a collaborative session, the group discusses cognitive modeling for DSI systems and specifically onboarding a person into the token engineering commons. They focus on one microcosmic action of visiting a website and seeing it or not. They discuss creating an accessible and inclusive space for new members while also respecting privacy. The group plans to create a professional-grade cognitive model of participants that respects privacy in a legible way. They also explore how values and norms are enacted in design and operation within communities, including considerations such as mental health and career progression. Ultimately, they plan to publish their work on Zenodo as a citable artifact for future reference. The speaker discusses options for creating a center of gravity or meeting point for people who care to serve. They mention keywords, access rights, and contributors including authors and editors. The speaker shares their process for exporting and uploading a file for submission to an unconference, with the goal of obtaining a DOI citation. They thank participants in the session and end by stopping the recording and removing the note taker. Keywords:AI, active inference, DSI, ecosystem, simulation, ontology. Share feedback: https://airtable.com/shrTJHhCq2PHdC3fl

Outline: I have identified several topics discussed in the transcript that can be used to create an outline. Here is the outline with approximate timestamps:

1. Introduction to the session (0:00 - 1:30) Participants introduce themselves and share their interests The recording of the session is announced
2. Overview of the session (1:30 - 6:00) The session will take about two hours The first part is for introductions and context The middle part will focus on applying the active entity ontology for Science (AOS) The last part is for polishing and publishing a page The goal is to explore the use of active inference and generative modeling for complex system simulations
3. Background on the project (6:00 - 14:00) The project is related to block Science Labs and Cadcad The active block prints via Cat CAD are used to work fluidly between natural language and language models The goal of the project is to develop an ontology for decentralized science using a controlled vocabulary
4. Developing a cognitive model of human onboarding (14:00 - 33:00) The group discusses the concept of onboarding and decides to focus on a specific case They develop a plain text representation that summarizes the process of onboarding a human into a community of practice The representation uses active and informational entities and can be seen in plain text, visualization, and simulation The group plans to publish their work on Zenodo
5. Summary and future work (33:00 - end) The group summarizes their work and thanks everyone for their participation They discuss possible directions for future work and suggest using a ledger or CERN upload for publishing The recording is stopped Note: The timestamps are approximate and may vary depending on the version of the transcript.

Notes: The session is being recorded on Zoom. The first part is just introductions and context. The session is participatory. The session will be less than two hours. The work will be collaborative and anonymous. The group will explore terms and acronyms. The group will explore accessibility and preference. Participants can ask questions in the chat. The group will work on a page together. The group will explore computational modeling. The group will explore active inference and generative modeling. The group will develop a plain text representation. The group will summarize the situation they want to describe. The group will draft pseudocode. The group will write an abstract. Participants can upload a paper to enter something into the scientific literature. The group will export the Coda document to PDF. The recording will be stopped after the closing word.

Action items: Follow-ups: What is the Active Inference Institute and what are their goals? Can you explain more about the Active Blockprints project and how it relates to active inference? How does Cadcad fit into the picture and what is its role in these projects? Action items: Record the session on Zoom for backup purposes. Introduce ourselves and share our backgrounds/interests at the beginning of the session. Collaboratively work on a GNN model for an active entity ontology for science (AOS) DSI system. Publish our completed page as a PDF on Zenodo with author information. Reflect on our experience during this microcosm of a DSI scenario, exploring ways we could have done things better. Follow-ups:

1. What are the benefits of using Cadcad for complex system simulations?
2. How does active Block add cognitive modeling to Cadcad's top-down structural perspective?
3. Can active inference models be transposed easily across different systems and settings? Action items:
4. Explore the link provided in the chat to learn more about active inference.
5. Develop a new informational entity within the AOS ontology.
6. Consider how generative models can be used to create and compose different types of active entities in decentralized science ecosystems. Follow-ups: How can we apply the framework of active inference to specific systems of interest? What are the potential consequences and lost opportunities when implementing individual mechanisms or systems in decentralized science ecosystems? How can a plain text notation for active inference help with fluidity between natural language, graphical visualizations, and executable simulations? Action items: Develop a cognitive model of a human onboarding into Token Engineering Commons community of practice Characterize relevant entities (active and informational) in the situation Use plain text representation to summarize and move towards natural language, visualization, and simulation Follow-ups:
7. What other entities will the person interact with or what actions will they take?
8. What is the simple action that initiates onboarding, and what happens once they are in this role?
9. How do we deal with people dropping into a new room? Action items:
10. Model the onboarding of a person into the token engineering commons.
11. Characterize it in terms of active entities and informational entities.
12. Consider additional features such as privacy and modularity.
13. Write pseudo code for a GNN model focused on whether or not someone chooses to visit the website.
14. Upload the paper to Zenodo for publication as a citable artifact.
15. Explore future directions for work in DSI systems, including how values and norms are enacted in design and operation, making participatory systems, recognizing healthy ecosystems, and balancing social good vibes with rigor/documentation/professionalism aspects of science/engineering spaces. Note: Some action items may have been missed due to interruptions during the transcript (e.g., inappropriate behavior) Follow-ups:
16. Add citations to facilitate bibliography work and give information on the journal.
17. Check the file by exporting it to PDF and ensure that all links work.
18. Upload the file, fill in DOI, date, title, authors, abstract version keywords more notes open access Creative Commons no funding, no other Identifiers part of unconference details and save it. Action items:
19. Shrink a particular section slightly and rerun it for submission to conference.
20. Update the page with publication information and change privileges back.
21. Remove note taker from session recording.