It's Time For a New Type of Network / Liminal Space Navigator: your gateway to better connections and opportunities.

Note of thanks to James Collura for reminding me about slime mold behavior and the need for a new type of network. 

Also Note: It is important to know before proceeding, that this is the vision. The framework, ideas, theoretical research, creation of the chatbot and the Google Form are there. Needed, at this point, are the people required for self-organization and emergent properties to work, e.g. the API that connects the spreadsheet to the chatbot. Theoretically, and while this is emerging, we could run this on NotebookLM, i.e. 50 sources of 50 spreadsheets where everyone who used the chatbot had access. That alone, could be powerful. Eventually, I imagine, NotebookLM will upgrade to reasoning and search models like DeepSeek or ChatGPT o3. That is why your help is needed to make this work. And, if you are the person to help in connecting these functions, please reach out: 

My-True-Self: Where people go to navigate the space between and thrive on the edge of chaos.

Philosophical Vision

For too long, we’ve relied on outdated, linear systems to find the right people—resumes, job boards, LinkedIn connections that go nowhere. These traditional methods force us into rigid categories that don’t reflect who we truly are or what we’re capable of. But what if there was another way?

Nature offers a clue. Slime molds, ant colonies, and even decentralized human networks don’t function by rigid hierarchy. They thrive through emergence—patterns forming organically as individuals interact, adapt, and share knowledge. The most resilient systems aren’t centrally controlled; they evolve dynamically based on real-time connections and needs.

Liminal Space Navigator is built on this principle. It’s not just a chatbot—it’s the starting point for an adaptive human network, where creativity, skills, and ideas flow freely, forming connections that wouldn’t happen in a structured, top-down system. It’s an experiment in collective intelligence, an invitation to step outside traditional networking models and into a system that grows with us.

If you’ve ever felt frustrated by the limitations of conventional job searches, if you’ve ever wished for a way to find the right collaborators faster, or if you’re simply curious about what we could build together, this is your invitation.

How It Will Work

1. Engage With the Chatbot

   • Visit My True Self and answer seven thought-provoking questions about your strengths, skills, and aspirations.

   • The chatbot analyzes your responses using Myers-Briggs, True Colors, and Multiple Intelligences frameworks to identify hidden strengths and potential collaborations.

2. Join the Network

   • Your results will be integrated into a shared intelligence system—a network that connects people based on complementary skills, work styles, and opportunities.

   • Think of it as an emergent LinkedIn, where connections are made not by static profiles but by real-time needs and shared goals.

3. Unlock Collaboration

   • Whether you're a technologist, creative, strategist, political operative, or educator, you’ll quickly find like-minded (or better yet, complementary) people.

   • Need a developer for a project? Looking for a writer who understands your vision? Want to partner with a policy strategist who sees the world differently? The network will help surface the right connections.

Why This Matters

We’re in a moment where AI is changing everything—and those who know how to leverage it will have a massive advantage. But AI alone isn’t enough. We need human networks that are just as intelligent, just as adaptive, just as capable of evolving.

This tool is for:

• Entrepreneurs and innovators looking for the right people to bring ideas to life.

• Creatives, developers, and educators who want to work in a way that feels natural and meaningful.

• Strategists and operatives who need to move beyond outdated systems and build agile, self-organizing networks that can tackle major challenges.

We’ve all seen how hard it is to tackle big projects alone. The tools we rely on are inefficient. But if we embrace a more emergent, adaptive model, we can unlock a new kind of collective intelligence—one that helps us find exactly the right people at exactly the right time.

This is our experiment. If it resonates, we invite you to join us—and to share it with those you trust. Let’s see what happens when we connect, not through rigid algorithms, but through shared curiosity, insight, and purpose.

Let’s build the first Human Slime Mold Network.

Are you in?

🔗 Start Here: https://poe.com/My-True-Self

The Connection Between Polymathy And Creativity

The following is quoted directly from the article. The link is at the bottom. 
Why Being A Polymath Is Increasingly Essential For Success

ByAytekin Tank, Contributor. 

Aytekin Tank is the founder and CEO of Jotform.

Jan 14, 2025, 10:50am EST 

The Connection Between Polymathy And Creativity

Research suggests that developing diverse disciplines fuels creativity and productivity. For example, studies show Nobel Prize-winning scientists are about 25 times more likely to sing, dance, or act than the average scientist, 17 times more likely to create visual art, 12 times more likely to write poetry, and four times more likely to be a musician. Talk about multi-faceted over-achievers.

Read More: How Overthinking Is Keeping You From Achieving Your Goals

Experts believe it stems from cross-pollination. Ideas from one discipline can inspire another. World-renowned chef Massimo Bottura, for instance, has said that art inspires his Michelin-starred cooking. What’s more, shifting mental gears can give your brain a much-needed rest, clearing the space for creative breakthroughs.

I could not have said it better. Here is a link to the full article. 

Generative AI: Is This the Age of the Creative Generalist?

New research on large language models suggests LLMs are exhibiting certain human-like qualities (notably how it is organizing information geometrically and conceptually). If this is true, how we prompt a generative AI system might also need to change. If it responds well to more abstract, metaphorical or conceptual prompts, that would imply we need people who can think like this.

Whether or not you accept the premise that some LLMs are developing in this way, we still have our own experiences using generative AI and know that the creative possibilities appear to be endless. It might, therefore, be a good time to ask ourselves if, indeed, we are entering the age of the “creative generalist.”

This is something that Daniel Pink suggested in his 2006 book A Whole New Mind when he said that in the future, there might come a time when we need more “right brained” individuals to piece together all the disparate technologies in sensible, meaningful ways. In such a world, vision, philosophy, history, art, morality, ethics and musical knowledge, might hold a place equal to that of the engineer, scientist or technologist. The question is, is anyone else noticing this shift? Are people seeing the potential? Are companies making strides to bring in systems thinkers, philosophers and ethicists into their AI departments? Are schools of liberal arts taking note and adjusting the curriculum?

Should we, for example, make changes at schools and universities such that AI is not taught merely as an extension of computer science, but is taught in schools for the liberal arts?

Certainly, there are many examples we can look at. One that immediately comes to mind is the creative use of datasets. For example, something that I’ve started looking into as an AI content strategist, is to load datasets of personality and intelligence inventories, like Myers-Briggs and Gardner’s multiple intelligences and then ask the AI to help me better understand the audience or a company in terms of how they are more likely to process information. Other things come to mind too such as training AI on a piece of music like the Finale to Shostakovich, Symphony no. 7 and then asking it to translate that into an equally powerful conclusion to a piece of writing. What about a sustainable business model that resembles a natural process like photosynthesis or documenting the the ecosystem of a forest and modeling the design of a community college in this way. These are all things, by the way, that AI can do right now.

I asked GPT4o: “If certain LLMs are organizing information more geometrically and conceptually, is there a good argument for recruiting more people with creative, conceptually minded brains into the field? Should we, therefore, make changes at schools and universities such that AI is not taught merely as an extension of computer science, but is taught in schools for the liberal arts.”

It replied:

The research paper, The Geometry of Concepts: Sparse Autoencoder Feature Structure, suggests that large language models (LLMs) are organizing information in ways that resemble the functional and structural organization of the human brain. By analyzing the geometry of sparse autoencoders (SAEs), the authors found three levels of conceptual structure: (1) “atomic” small-scale structures, such as parallelograms and trapezoids that encode relationships (e.g., man:woman::king:queen); (2) “brain-like” intermediate-scale modularity, where clusters of related concepts, like math and code, form localized “lobes” similar to those in neural fMRI images; and (3) “galaxy-scale” large-scale structures, where the overall feature space exhibits non-random, fractal-like clustering and power-law eigenvalue distributions. These findings indicate that LLMs are more than linear systems — they are evolving toward complex, hierarchical representations of knowledge, akin to human cognition.

This research has implications for how we approach AI development and education. If LLMs are creating conceptually rich and geometrically organized knowledge spaces, there is an argument for involving more creative, interdisciplinary thinkers — those trained to recognize patterns, connections, and abstract relationships — in the field. This could mean recruiting individuals from liberal arts, philosophy, and design backgrounds, alongside traditional computer scientists. Moreover, it raises the question of whether AI should be taught differently, not just as a technical discipline but as a conceptual, creative practice. Perhaps universities should integrate AI into liberal arts programs, encouraging the development of “creative generalists” who can bridge conceptual thinking and technical expertise. This shift might not only enrich AI research but also lead to more intuitive and human-centered prompt engineering, better suited to the conceptual landscapes LLMs are now navigating.”

Perhaps we have entered the age of the creative generalist.

If you’ve made it this far, you are a good candidate to learn about an upcoming presentation and discussion. On December 21st, I will explore this topic and why I believe there is a good opportunity for creatives, generalists and especially “hyper-generalists” to enter the field of generative AI.

For a deeper exploration of this topic, please see the following:

1. When Everything Became Possible / An AI Podcast
2. The Soul of AI (Ep. 12: Lee Chazen)
3. THE GEOMETRY OF CONCEPTS: SPARSE AUTOENCODER FEATURE STRUCTURE
4. Discussion around The Geometry of Concepts Paper
5. I asked GPT 4o the most complex question I could think of. Here's what happened.
6. Free Copy: When Everything Became Possible: The Story of Three Universal Characters, Set Free to Help us Understand our Future with AI by Lee Chazen