Imagine a world in which AI is not controlled by several large corporations, but belongs to people – like you or me. Sounds like something unreal? Maybe yes, but what once seemed impossible today becomes a reality. AI decentralization, i.e. the creation of artificial intelligence systems based on open, common principles, gains on importance and develops at a good pace.
What is AI decentralization?
Let’s start from scratch. Artificial intelligence, such as chatgpt, is a powerful tool that can answer questions, write texts, and even generate images or movies. But there is a catch, most such systems are controlled by large companies, such as OpenAI, Google or Microsoft. They decide how these models work, what data they use and who can use them. If you want to use chatgPT, you send a query to their servers, and they control everything from the very answer to whether you get access at all.
AI decentralization is a completely different philosophy. Instead of one company that holds all strings, we have a network of people and computers around the world that together they create, train and share AI models. Why is this important? Because when AI controls one company, it sets the rules. It can limit access, change the rules or even turn off the service, and you have no influence on it. Decentralization gives users more control, transparency and the ability to co -create. This is AI, which belongs to the community, not to the corporation.
Short story
The idea of decentralization AI is not new, but for a long time it was more a dream than reality. In 2017, there were projects like SingularityNet, which wanted to create a AI service market based on blockchain. It sounded great, but the world was not ready for it – neither technology nor people. Cryptocurrencies were just crawling, and AI was mainly associated with sci-fi movies.
Everything changed in 2022, when Opeli released Chatgpt. As many as one million users won in five days! It was the moment when AI became something that people really wanted to use. But with popularity came questions such as who controls these powerful tools? What if the data on which they are trained are biased? Or if the company suddenly block access?
At the same time, blockchain technology and decentralized networks such as Akash or Filecoin began to mature. Thanks to them, it became possible to divide computing power, store data and train AI models without the need for supercomputers. This opened the door for AI decentralization. Suddenly the idea that once seemed distant became real.
How does AI work and why is centralization a problem?
To understand why decentralization is so important, it’s worth knowing how AI is created at all. The process of creating a model, like chatgpt, can be divided into several stages:
- Pretrection – The model learns basics, processing huge amounts of data such as books, websites and various types of codes. It’s like learning general knowledge about the world. Problem? It costs millions of dollars and requires supercomputers that only the largest companies can afford.
- Tuning (Fine-Tuning) – The model becomes a specialist in a specific field, e.g. in writing code or answering legal questions. But it is the companies that choose what the model is to be in, and ordinary users do not influence it.
- Alignment (alignment) – Here the model learns how to be “polite” or how to answer in a safe and consistent way with the company’s rules. Only that these rules are set behind closed doors, without your participation.
- Use of the model (Inference) – When you ask AI about something, you send a query to the company server. They see what you are asking, they can block or limit it. It’s a bit like you had to ask for permission every time you want to think about something.
Each of these stages requires enormous computing power, which is controlled by large companies, such as Microsoft, Amazon or Google. This makes AI centralized, and only a few have access to tools and data to create such systems.
Decentralization in action
Fortunately, there is an alternative. Projects such as Pluralis Research, Nous Research, Prime Intellect and Gensin show that you can create AI in a completely different way.
Pluralis Research – AI on home Wi -Fi
Pluralis solves a problem that seemed impossible for a long time, i.e. how to train large AI models on ordinary computers, without super fast internet? Usually, training requires the transmission of huge amounts of data between machines, which only works in data centers with fast connections. Pluralis invented how to “pack” these data into smaller packages that can be sent even by home Wi-Fi.
Imagine building a huge puzzle, but instead of sending the entire board to each participant, you only send a sketch with key elements. Everyone adds their own piece, and the whole is created. Pluralis tested this by training a model with 8 billion parameters on ordinary computers with 60 Mbps Internet. Effect? The same as in professional data centers. What does this mean in practice? You can help create AI using your laptop and get a reward for it. The model does not belong to any company but is the property of those who create it. This is decentralization.
Prime Intellect – AI, which studies in chaos
Prime Intellect went a step further. They created a system that allows you to train AI models on computers scattered around the world, even if some of them are free or turn off. Their Intellect 2 model, with 32 billion parameters, was trained in such a way that it works without a central server and on the ordinary Internet.
Imagine a group of people who solve the problem together, but everyone does it at their own pace. One paints the image, the other checks if the colors agree, and the third improves the details. Prime Intellect has created a system that allows computers to work in such a way that everyone does their job, and the whole thing is made up of one model. What’s more, every result is checked cryptographically, so no one can deceive the system.
Prime Intellect has also created a huge set of data (SyntHetic 1), which helps the model learn difficult things, such as mathematics or programming. It’s like a textbook that everyone can supplement and check.
Guesin – AI, who learns like a band
Guesin is a project that works a bit like a student design group. Their system, called RL Swarm, allows small models to learn together, sharing answers and improving each other. Each model first tries to solve the problem, then criticizes the answers of others, and at the end everyone chooses the best solution together. This makes the models learn faster and are more precise. Importantly, all this happens on ordinary computers, without the need for large servers. Genówin shows that even small machines can create something powerful together.
Nous Research – AI on blockchain
Nous Research created the Hermes 3 model, but their greatest achievement is the way they train models. They use the Distro system, which allows computers to exchange data in a very compressed form, a bit like sending smaller SMSs instead of the entire letter. Thanks to this, they can train models on computers scattered all over the world, even if they do not have access to super fast internet. Their psyche Network, based on blockchain Solana, acts like a manager who makes sure that everything goes smoothly and without any problems. He assigns the tasks, checks the results and makes sure that nobody is cheating. Currently, they train the Consilience model with 40 billion parameters, it is one of the largest such projects in the world.
What does this mean to us?
You are probably wondering: “Okay, but what does it give me?” AI decentralization is not only a technological novelty, it is a completely new approach to how we can use knowledge and technology. Imagine that no one can suddenly cut off access to AI, and you have an insight into how the model was created and what data behind it is. You can even help create such AI by using a regular computer, and get a reward for it, and the model belongs to all of us, not to some corporation.
It is also a way to become independent of great players, such as Google or OpenAi. Decentralized AI gives you a choice, especially where the giants do not look, for example in niche projects. In a world where AI affects everything, from elections to education, it is very important because no one has full control. Less risk that someone will use technology against you. It is definitely a chance for the future in which AI is more ours, more transparent and gives you real influence.
AI decentralization sounds like a revolution, but has its traps. Large companies, such as OpenAI, pump more and more power into their models, it started from 117 million parameters in GPT-1 in 2018 to the alleged 1.76 trillion at GPT-4 in 2023, and for all this they are still growing in strength thanks to huge funds and refined products, while decentralized projects, such as the 15-milliard model Nous Research They keep up. Many of them still rely on the models from giants, such as finish or openai, which puts them on fragile ground because if they change the rules, everything can collapse.
In addition, users love simplicity, and chatgpt wins with ease of use, while decentralized AI often scares away complicated interfaces. The projects will also sometimes spread in pursuit of too many ideas at once, losing focus and energy, and the temptation of quick profit from tokens can turn the innovation into a speculative bubble, as is often the case in the world of crypto.
What next?
The AI market is growing like crazy and it is estimated that by 2030 it will be worth over $ 15 trillion. Decentralized AI does not have to defeat the giants to succeed. Even 5% of this market is a lot of money, enough to create a thriving ecosystem. It’s like open source in software, it doesn’t have to dominate, but it’s crucial for the whole internet. Of course there are challenges. First of all, large companies have a huge advantage, because their models are growing and better. Secondly, many decentralized projects still use models created by corporations, which means that they are not fully independent. Thirdly, user interfaces must be as simple as chatgpt, because people like convenience. Finally, projects must focus on clear goals instead of trying to do everything at once.
AI decentralization is not a struggle to replace Opeli or Google. It is building an alternative that gives users a choice and control. As Sun Tzu said: “Avoid what is strong. Attach what is weak”. Decentralized AI can win by offering what great companies do not give, i.e. transparency, community and freedom. For an ordinary user, like you or me, it means the future in which AI is more ours. We can use it without fear that someone will cut us off or impose their rules. And if you have a computer and some time, you can even help create it. This is just the beginning, but it seems that the future AI will be more open, and this is good news for all of us.
