The ability to generalize things. It is the main element for AI. And it's trustworthy.

The term Matrioshka brain. Means a giant, but hypothetical supercomputer. The idea is taken from Dyson’s sphere. The ultimate megastructure. Created by the physicist Freeman Dyson. The Dyson sphere means a theoretical massive sphere. That surrounds an entire star or solar system. The evolution model of that hypothetical megastructure called the Matrioshka brain. The giant supercomputer that surrounds entire stars. Even the solar system-sized megacomputers. They can interact with human-sized robots or laptops. And that makes those systems interesting. This kind of data chain can be like a group of matryoshka dolls. In those dolls, there is always a doll inside the larger doll. In the same way as the matryoshka model. The supercomputers form. The chain there, the larger computers operate the smaller computers by using chains. The next computer in the line is only a little bit smaller. Than the larger computer. 

AI learned laws of physics. And gamers could play games using their brainwaves. These kinds of things tell about the abilities of the AI. The AI, or the LLM (large language model), is a tool that can learn to read things like brainwaves. In the same way as the AI observes and compiles the radio waves that neutron stars transmit. The AI compiles physical movements and reactions in the human body into brainwaves. That its sensors observe. The AI can connect certain brainwaves to certain actions. And that is the key element in the BCi (Brain Computer Interface). The AI requires training. It can connect certain. Brain waves. With certain actions. 

The AI can also read the human mind. By benefiting from signals that certain brain lobes send to the spoken words. Those signals can be used. For giving data. To a speech-to-text application. And then the system can drive that text into the LLM. The computer games. They can be used as a simulation to map the brain waves. And connect that data. With things like physical objects, such as robots. The BCI can control robots and things like aircraft. There is no limit. For the use of the BCI. And that is one of the things that we must realize. 

AI learns things faster than humans. When it must guard the qubit. The AI must only adjust its temperature. And it must know the point. There. The information must be stored in some mass memory. And the qubit must be re-adjusted. This means that the AI is a very effective tool. When it must operate in a limited and well-controlled environment. The reason why the AI is the tool. That can solve physics problems. Or it can create new math. The AI can operate with longer prime decimal numbers than ever before. This is why the AI is a revolutionary tool. When AI must use only observations and connect that data with previous observations. It can make things that we cannot even imagine. Creation of the new physics. Requires the ability to interconnect objects from multiple sources. 

How does AI win architectural competitions? The problem with AI is how to transform things like buildings and their details into a numerical model. The numerical introduction. The main work is. How to transform materials, angles, and colours into numerical form. The AI can use statistical methods to create new houses. In those cases, the AI must only find a formula. That it must follow.  The idea is that. The AI must find the way. To please the jury. And the answer. It can be the statistics. If people have similar backgrounds. They probably like similar things. And the AI can use that thing in their work. 

The architectural competition is abstract. But when we think about the AI and the abstraction that people must handle in that work. We must realize that when people have similar backgrounds. They have similar ways to handle abstraction. So if we have a certain group of people. Acts in a similar way. We can generalize those people and their behavior to all people with similar backgrounds. So, that means that. If we cannot predict an individual person’s behavior. That means we don’t know everything about that person. 

But then we can ask one thing: can a computer handle abstraction? The computer can create things that do not physically exist. The system can use complicated flow simulations and connect them with CAD images. This means that. The AI. It can design things like aircraft. The system can connect those simulations with things like matter matter strength simulations. And this makes it possible to create. The simulations about the structures that don’t exist. The AI makes things using mathematical or sharper. Statistical models. If the AI must design houses for the architectural competition. It must collect data about the environment where the planned house will be built. Then it must search for similarities. With other winners and their environments. Those similarities. They are the purpose of the house. And the type of houses were there before the work was introduced. 

Then the AI requires information about the background of the jury members. Where those jury members sit. Before they entered the jury.  What kind of decisions did they make before that competition? What articles are written about houses, and how are they written?  And how do they show? Are they qualified people? For that architecture jury? This means that if similar persons with similar backgrounds judge competition entries. They should like similar works. And that helps the AI to create its advertisements. The AI also requires building instructions and material restrictions. So that it can create works that please the jury. This is the idea of the competitions. The works should only please the jury. And the AI must find data. That uncovers the type of buildings that pleases the jury members. This means that the AI. It can make creative work. Buildings are always full of geometrical details. 

That thing can be used to calculate statistical things like angles of certain walls. The most challenging thing is this. How to transform things like materials  into numbers. The solution can be that. The concrete. It can have a numerical value of 2. Colors can also have numerical values. Red, it can be 4. If the concrete element has two colors. The system can calculate. On what percentage of the area can certain colors cover? And of course, scattering of those colors can also be calculated. The system must calculate the area. That certain color covers. And that makes it possible to create numerical statistics about things. It must notice when it tries to win that theoretical competition. Maybe quite soon, we will see the AI create things like houses in architectural competitions. 

https://scitechdaily.com/scientists-let-people-play-video-games-using-only-their-thoughts/

https://scitechdaily.com/this-ai-learned-the-laws-of-physics-and-could-accelerate-quantum-computing-breakthroughs/

https://en.wikipedia.org/wiki/Matrioshka_brain