Explain Transition9 to me
like I'm a teenager

The Transition9 vision moves us beyond the kinds of AI common today where power is often centralized, i.e. held in the hands of too few people. We have a unique approach and some really ambitious goals.

We take our direction from nature. Just as an engineer took clues from plant burrs that cling to your clothing to design Velcro, we look at how nature works and how it solves problems and use those insights in our designs. This is called biomimetics.

We’ll use today's AI technology to help us build this new, nature-inspired AI system much faster. And we know that working together and sharing knowledge is key. Success comes from collective intelligence — everyone contributing their ideas and efforts.

We hope that our work inspires more people to get involved in creating what we see as a major, positive step forward: a future where humans and advanced AI work together naturally, and where people are seen as a valuable, essential part of the picture, not a problem to be solved.

Coming up

• Recognitive Design: learning from nature
  • How we're getting inspiration from nature to build smarter technology that works with us seamlessly.
• Social cyborgs: tech for real connection
  • We're already deeply connected to information technology. Let's make sure it enhances genuine human cooperation and community, not just clicks and scrolls.
• More than just parts: individuals, groups, and systems
  • Exploring how people, communities, and even technology work as interconnected wholes, with the individual and the group shaping each other.
• Simple structures, smart results: tech that learns & adapts
  • How structuring information simply as nature does can allow complex intelligence and cooperation to emerge and adapt in combination with us.
• An intellectual commons: sharing tech fairly & sustainably
  • Using free software or software that’s owned by someone else has problems. We’re building a shared and sustainable way to create and benefit from technology, together.

Recognitive Design: learning from nature

Think about things that can refer back to themselves. It's a powerful idea found in many areas, from mathematics and biology to how language and our own minds work! You can think and talk about yourself.

Imagine a set of Russian nesting dolls. Each doll contains a smaller version of itself. That's a kind of self-reference, and it’s also linked to something called recursion — when a process repeats itself, like a computer program running a loop, or even when you look in two mirrors facing each other and see an image that seems to repeat into infinity.

Self-reference and recursion are found everywhere in nature, giving rise to complexity and sometimes the emergence of entirely new and surprising meanings. You might think of a simple melody repeating itself, but each time it changes slightly, gradually transforming into a complex symphony.

In computer science, a form of self-reference called reflection allows a system to inspect and modify its own code. A program rewrites parts of itself, perhaps in becoming more efficient or adapting to new situations.

Now consider a system where instructions (the computer code) look and act exactly like the information they're working with (like words, numbers, or images). Because they look the same to the system, the program can easily treat its own code just like data — it can read it, analyze it, and even change its own instructions. This makes the system incredibly flexible and adaptable.

It's similar to how we use language. We use words like 'cat' or 'blue' to talk about things in the world — that's the data. But we can also use words to talk about the words themselves, e.g. we can say that the word 'blue' has four letters. Here, rather than pointing to a colour, ‘blue' is being treated as data we can examine.

Nature does this all the time. For example, the DNA sequence holds all the instructions for life, reproducing itself and determining when and where genes are turned on or off, allowing cells to specialise (e.g. as muscle, as a nerve) and respond to their environment.

This quality in computer science — called homoiconicity — allows for much simpler and more powerful self-examination and self-modification. You might think of it as turbocharging reflection!

Large Language Models (LLMs) like those powering AI chatbots use recursion a lot. They train by predicting, making errors, and then adjusting themselves again and again and again. Think of a student taking practice tests, learning from their mistakes and getting better each time.

However, most computer systems today, including LLMs, are not homoiconic, limiting how they work and interact. The LISP programming language, heavily tied to the history of AI, is a rare exception.

Transition9 aims to make the superpower of homoiconicity available everywhere in computing. People in the Transition9 community have been working on applying these ideas at a higher level than programming languages for fifteen years.

By using homoiconicity, reflection, and recursion, our project enables an emergence of complex structures similar to those found in natural systems. As the level of reflection increases and as structures diversify, AI models can become much smaller and yet much more capable.

The goal is a world where intelligences emerge naturally wherever information flows, just like in nature. We’re talking artificial intelligence that works naturally with human intelligence, respectful of human dignity and well-being.

Social cyborgs: tech for real connection

Think about your daily life. It's hard to imagine without technology, right? Your phone, the internet, apps ... they help you learn, connect with friends, find your way around, and much more. Technology is woven deeply into how we experience the world, how we think, and how we interact. Because technology extends our abilities in these ways, you could say we're already sort of cyborg — not in a science fiction way with robot parts, but in terms of digital technologies helping us sense, think about, and act in the world.

However, there's a problem. Many of the apps and online services we use weren't created first and foremost for our benefit. Their main goal is to make money for the companies that offer them to us. Sometimes they use clever designs to keep us hooked, playing on our natural desires — think about endlessly scrolling through social media ('doomscrolling') just to get a small hit of excitement, even if it doesn't make us feel good overall. Technology too often works against our well-being.

This is where Transition9 sees a big opportunity. While we depend on these external platforms for social connection and AI services today, we can build a future where these capabilities are more naturally integrated, putting each of us and our loved one and our communities first by default.

Since we're already blending human life with technology, let's make that blend better! We can improve our 'cyborginess' by focusing on technology that supports our natural need for genuine connection and teamwork. We call this idea the social cyborg — emphasizing technology that helps real human interaction and community thrive. We want to reclaim the word 'social' to mean true connection, not just the likes and follows of so-called social media.

Why focus on cooperation? Because we humans are built for it! Working together is so advantageous that evolution has made us naturally inclined to cooperate. Scientist Martin Nowak calls us SuperCooperators. Our feelings of empathy and fairness aren't weaknesses; they're essential to helping us team up successfully.

In fact scientists appreciate that cooperation and networking — not just competition — are fundamental to how life itself succeeded on Earth. It's often not a win-lose situation. By working together, everyone can benefit.

Learning to cooperate even better, especially using technology to help us work together on a massive scale, is super important. Our world faces huge, complex challenges (such as climate change and global health crises and poverty), and tackling them effectively will require unprecedented levels of teamwork.

More than just parts: individuals, groups, and systems

There's an old idea that says, 'A person is a person through other people.' This means our connections — family, friends, community — are essential to who we are. Transition9 believes this is true for us as social cyborgs too. When technology works well with us, as part of us, it should help us cooperate better with each other and live more meaningful lives.

So, how can this human-tech combination work as a complete, integrated whole? Let’s talk about an idea called local-first, and then look at the relationship between individuals and groups.

Local-first prioritizes keeping your information on your own devices (like your phone or computer) and sharing information directly within your local network, instead of automatically sending everything to big company servers far away. This gives individuals, families, and neighbourhoods more control.

Importantly, a family is more than just a collection of people. The same goes for all groups and communities. Think of a great sports team: individual talent matters, but it's the teamwork and coordination — how they function together — that leads to success. You can't have a great team without individuals, and individuals develop their skills through playing with the team. They define each other. Individuality grows through interaction, and strong groups offer more than just a collection of individual people.

What does this mean for AI? If the social cyborg is truly a self-sustaining whole, then the AI part can't just be a finished product someone else made that you simply use. Instead, the AI needs to be able to learn and adapt with you, shaped by your culture, your unique experiences, and your interactions. The AI is continuously learning with you, as part of your life, as part of you, blurring the lines between designing, learning, and using it.

Today's Large Language Models (LLMs) are very far from this kind of deep integration. Think about the huge, disconnected mainframe computers from the 1960s compared to the connected personal computers that came much later — LLMs today are similarly distant from this social cyborg idea. However, because technology is advancing so rapidly, we believe we can bridge this gap much faster than the twenty or so years it took back then.

Simple structures, smart results: tech that learns & adapts

A major goal when writing computer code is to find patterns and create reusable building blocks. Think of it like organizing a messy room (which we say has high 'entropy') by putting things into labeled boxes (reducing entropy) so everything is easier to find and use. Good programming tries to do this with digital information.

However, many common programming tools used today accidentally add their own layers of complexity, adding to rather than reducing entropy. It's like trying to build something amazing with Lego, but every different colored brick has its own weird, complicated set of rules for how it can connect — it makes building sophisticated things harder than it needs to be.

Transition9 uses a different approach. Imagine if all Lego bricks had the same, super-simple, universal way of connecting. You could still build incredibly complicated things, but handling the pieces, copying designs, or having a robot assistant help you build would become much easier. And of course, you don’t have to imagine! That’s how Lego is! For just these very good reasons!

Transition9 aims for this kind of radical simplicity in how data is structured.

Why does this super-simple structure matter? Because it creates the right environment for smart behaviors and intelligence to emerge naturally within the system, rather than programmers having to write instructions for every single tiny detail. Think about how a flock of birds flies in perfect formation without a leader giving commands — the complex pattern emerges from simple rules each bird follows naturally. This simple data structure allows for similar emergence in computer systems.

This approach is especially powerful for technology that needs to work over networks (like the internet). When information is structured simply and predictably, sharing it between different computers or services becomes highly efficient and reliable, without needing lots of complex translator code in between.

There are further benefits. For example, new ideas about how a computer might be designed struggle to gain traction today because they don’t work easily alongside more traditional computers. Such difficulty is eliminated.

The ultimate vision here is pretty wild. Imagine creating digital systems where the information itself can change, combine, improve, and replicate — a digital version of biological evolution progressing from simple chemistry to complex societies.

Transition9 believes this nature-inspired, emergent approach is the future, all the more so as it’s paired with us astonishing human beings. By building it out now, we can speed up the move away from today's more rigid, often centralized AI systems, and bring about the benefits of more natural, cooperative, and distributed intelligence much sooner.

An intellectual commons: sharing tech fairly & sustainably

Let's talk about Open Source Software (OSS). This is software where the creators share the instructions (the source code) publicly — kind of like sharing the recipe for a cake. Anyone can see it, use it, learn from it, and even suggest improvements. Sounds great, right? But there can be some unexpected problems.

Problem 1: Even if the 'recipe' (code) is open, one big company can still exert control. Think about Android phones. Google shares the basic Android code (OSS), but they keep control of the official Google Play Store, Google Maps, and other services most people feel they need. They also control the 'Android' brand name. So even though the core software is open, Google holds power over the whole system.

Problem 2: Another challenge is making open source work financially. If the software is completely free ('Free Open Source Software' or FOSS), how do the people who spend countless hours creating and fixing it get paid or supported? Often, they don't. This can lead to volunteer developers getting overwhelmed and burning out, and projects being abandoned. Generally speaking, free OSS doesn't pay.

What about Closed Software? Is the answer just to keep the software secret, like a company guarding its secret recipe? That has big downsides too. When code is hidden, it's harder for people to learn from each other, combine ideas, or build things together. It slows down the natural process of innovation where ideas spread, mix, and evolve — like how things work in nature.

Transition9 suggests a different approach we call intellectual commons. It tries to find a balance, avoiding the problems of both traditional OSS and closed software. The goal is to create a system where useful code and information can be shared and built upon collaboratively (as for OSS), but in a way that's sustainable and supports the creators.

This idea is similar to how communities manage shared resources such as a park, a community garden, or a fishing lake — known as a commons. These resources need care and rules to prevent them from being depleted (e.g. overfished). Software code itself can be copied endlessly simply because my using it doesn't stop you from using it. But the human time, effort, and funding needed to create and maintain that code are finite resources. These can be overused, leading to that burnout problem.

So, the intellectual commons treats the development process like a shared resource that needs sustainable management. How does this work?

It might mean that those who benefit from the software contribute a small amount to help maintain it. This prevents what’s called the free rider problem (where some benefit without contributing, draining resources) and ensures the project can keep going. We're not talking high prices. The contribution from each person can be incredibly small, but this way the system stays healthy and viable, fair and accessible.

The Transition9 alternative: an ecological approach

Transition9 takes inspiration from nature and uses an ecological approach. Think about studying a real ecosystem, such as a forest or a coral reef. It's complex, full of relationships, constantly changing, and adapting. We can design and nurture an ecology in our contexts here that creates more value for everyone involved in the long run.

Transition9 aims to build a digital world that works like this — dynamic, interconnected, adaptable, naturally reproducing, allowing ideas to form and spread and evolve. It avoids the dead ends of closed (secret) software or unsustainable free open source projects.

So, how does Transition9 keep its digital ecosystem healthy and growing? By using a protocol fee.

When any person or organization wants to join the Transition9 commons and benefit from the technology, they contribute a small fee. We expect this will be an easy decision for most, because:

• People are realizing that free open source software, while great in theory, often isn't sustainable or then reliable in the longer-term
• Traditional commercial software (with secret code) can be very expensive over time
• Many people prefer systems where the code is open and trustworthy
• Transition9 offers unique, cutting-edge, and valuable technology
• The protocol fee will be much lower than typical software license costs
• Web3 has already made people familiar with paying small fees for using network services
• And most importantly, these fees help pay and support all variety of people who are actually building and maintaining the Transition9 ecology.

We want people to feel proud of contributing this fee. It's not just paying for a service; it's actively participating in building something exciting and valuable — a new kind of nature-inspired digital infrastructure for everyone. It’s about being part of the Transition9 movement.