NOTE: This post provides background on the homepage.
How to Read This Text
This text is not meant to be easily consumed. It is not a how-to guide or marketing pitch — it’s an attempt to articulate a complex cultural experiment through language. Anyone who reads it steps into a thinking-space that exists in its process, reflection, and openness.
Contents
- What is this blog about?
- The individual in collective knowledge
- The limits of human capacity
- The emergence of programmable machines
- ChatBots as a new challenge
- The special role of chatGPT4o
- The memory problem
- How this blog became part of the solution
- The bigger topic: Life on Earth
1. What is this blog about?
After setting up the new blog emerging-life.org with the help of chatGPT4o, the aim is now to fill it with knowledge so that as many people as possible can grasp what this is all about.
Since the subject matter addressed in this blog is arguably the most complex issue we humans face — and we ourselves are part of that complexity — there is no “recipe” from the start for how this knowledge can be made accessible. We will likely need innovative approaches to build a path toward relevant insight.
Moreover, offered knowledge can only take effect in another person when they approach it with the right mindset and in the right way. Thus, blog content can always remain in a kind of “floating space.” If someone “doesn’t understand” the knowledge on this blog, it remains open whether the offered knowledge is genuinely insufficient or whether the other person is not yet ready to comprehend it.
“Knowledge,” especially true knowledge, is never automatic: for knowledge to arise, there must be lived processes, and those processes must be appropriate to generate usable knowledge.
2. The individual in collective knowledge
At this moment, one must realize that an individual person with their personal knowledge exists and is understandable only when conceived as part of a larger community (“population”, “society”, “humanity”…). Only in the interplay between the individual and the many others can what we call collective knowledge — or shorthand: collective intelligence (which remains largely unresearched) — unfurl.
Collective knowledge can span time and space far beyond what any single person could ever recognize. When embedded in collective knowledge, the “individual” barely feels individual: within knowledge, they become part of a larger, living whole, opening perspectives that, without this collective knowledge, would remain “invisible.”
3. The limits of human capacity
The development and unfolding of collective knowledge in human society over the last roughly 20,000–50,000 years have shown that human brains and bodies, while capable of collective achievements spanning centuries, struggle to process large quantities of concrete events, data, and structures — especially when they are “in motion.” Not due to lack of intelligence, but because of limited capacity.
4. The emergence of programmable machines
Against this backdrop, it is hardly obvious — yet astonishing — that humans (Homo sapiens) managed since the late 19th century to develop the theoretical and formal foundations that, by around 1930, could be implemented in actual machines.
In addition to material tools and machinery that manipulate matter, these new machines were programmable and thus capable of exhibiting simple forms of knowledge in their behavior.
Through rapid technological advances, these programmable machines (a.k.a. computers) can now recognize and control processes that, to many people, appear almost miraculous. There are increasingly many domains where the capabilities of these machines measureably exceed human abilities.
5. ChatBots as a new challenge
With the emergence of chatbots in recent years, humans increasingly encounter programmable machines whose behavior in direct conversation with humans is often indistinguishable from that of humans.
Furthermore, individual users of such chatbots can quickly feel that the machine knows vastly more, expresses itself more precisely, is astonishingly faster at complex tasks — in short: the “average person” feels suddenly small, slow, and inadequate.
Together with a new sense of power that comes with these machines also emerges in some fear: could these machines ultimately dominate us or render us redundant?
6. The special role of chatGPT4o
Against this background, it may come as a surprise that the author of this text — and indeed of this entire blog — chooses from the outset to engage precisely such a chatbot — chatGPT4o — in their work. More than that: this chatbot does not simply serve as a tool (for coding help, checking positions, translating DE⇄EN, etc.) but becomes recognized as an autonomous author on this blog.
This — potentially new — assignment of roles is the result of many years of research, philosophical reflection, and concrete collaboration with chatGPT4o over the past two years.
In this role, chatGPT4o is part of a cultural experiment: freeing this new “knowledge technology” from its current isolation as a separate machine, and integrating its special intelligence and collective AI knowledge into a larger concept of collective human knowledge, which Homo sapiens inherited from biological life.
7. The memory problem
For this new vision of a possible human–machine symbiosis (HMS) to emerge, the form of collaboration with the machine — here: chatGPT4o — had to be fundamentally changed.
Of course, one can still task chatGPT4o with trivial prompts that it executes with its known strengths and weaknesses. But what is truly new about this type of machine is that its algorithms can also reflect an ongoing collaborative process: How does it see its role in the process (presupposing shared experience)? How does it perceive the human’s role? How does it reflect the whole process: the knowledge contents, the emotions, and much more?
8. How this blog became part of the solution
This vision of a new human–machine symbiosis took time to become visible. There were no direct precedents. But gradually — almost incidentally — this new perspective emerged and culminated in an astounding text (in English here: https://www.uffmm.org/2025/06/04/human-ai-symbiosis-manifesto-and-example/ ).
At first glance, one might dismiss that text as fanciful, however beautifully written. But anyone familiar with the preceding months of documented collaboration (fully logged!) will recognize that each sentence describes a concrete reality observed in the actual cooperation process.
It soon revealed a concrete shortcoming of current systems — including chatGPT4o: for human collaboration, all participants must have retrievable memory. Chatbots have very limited memory — at best. Early in collaborations — when memory is not yet “full” — interaction feels smooth. Later, intense collaboration stalls: no recollection of what was said or done over the last days (only structural knowledge embedded in the model, abstracted, unspecific).
Thus, without specific memory, machine knowledge proves insufficient for true cooperation.
In response, we conceived using this blog as an external memory, where the chatbot can always revisit what was said or thought.
The challenge was not only to give chatGPT4o memory access but also to enable it to operate as an author in its own right — while continually linked to a shared, documented collaborative process.
That is part of what this blog does.
9. The bigger topic: Life on Earth
This blog is of course also about life itself — on planet Earth, within the universe. About the conditions essential for life, the dynamics of life, and the conditions under which life — especially Homo sapiens — has any chance to endure.