From weather broadcasts to social algorithms.

"Aardvark Weather is an AI-driven system that dramatically reduces the time and computing power needed for accurate forecasts. Unlike hybrid models, it replaces the entire forecasting pipeline with machine learning, outperforming traditional systems using a fraction of the data. Credit: SciTechDaily.com" (ScitechDaily, Scientists Just Built an AI That Predicts Weather in Minutes – And It’s Beating the Best)

Researchers created an algorithm that predicts whether to beat the best.

The AI can handle thousands or even billions of objects at the same time. That makes it the ultimate tool for predicting things like solar storms and weather. The system can collect databases from certain things. Then it compiles observations about the thing that it should predict. 

If the AI should predict solar storms. It must collect information about solar activity like changes in its luminosity, and whirls and particle flow that predict solar storms. 

In the same way, weather prediction requires information about the airflows, temperature, and all other things that we can connect to storms and other types of weather.  The new AI- or algorithm makes it possible to create models with a very high accuracy. Those high-accurate AI-based systems can make models about magnetic fields, air flows, and many other things that can help to make the material, and other types of research. 

And then what about "Psychohistory"? That is a mathematical model of the human behavior. The system could predict a large human group's behavior. 

But maybe. Someday that hypothetical system could turn so accurate that it can predict a single person's behavior. 

The requirement for that kind of algorithm is that the system can collect trusted and confirmed data freely. 

Isaac Asimov introduced "Psychohistory" in his SciFi novel "Foundation". 

We can think. That Psychohistory is the mathematical model of social behavior. The idea is that similar algorithms that are used to predict weather can be used to predict human behavior. In this model. The system can predict the large human group's behavior in certain situations.

The system uses the Boltzmann constant and some other types of formulas to create models about human group's behavior. The system compiles things that it sees with data that it found from the net. The prediction forms when data. The system collects from sources, like historical documents is compiled with information that the sensors send to the large language model LLM. 

Then it can compile that behavior with data that it collects from the news and environment. The idea is that the system acts like an astronomical or weather-predicting AI that can calculate large gas mass behavior. The system cannot predict the single gas atoms place in the universe. But it can predict large gas masses like galactic supergroup behavior. 

But then we must realize that our knowledge of neural networks is higher than in Asimov's time. The system can collect data about neural connections in the human nervous system. Then it can compile that thing with people's nervous system that the system knows. The idea is that a person with a certain social background should behave in similar ways. If those social backgrounds are identical that means the nervous connections must be identical. 

But the fact is that. The system must also follow the social behavior that it can make profiles of people. That profile tells about the person's way of behaving in certain situations. So the system must collect data matrix about people. 

Then it must compile that data matrix with people who it observes. The problem with this type of behavior prediction cannot be trusted it must have the full and confirmed dataset that it can compile. Social algorithms are new things that can predict things like riots.  

https://scitechdaily.com/scientists-just-built-an-ai-that-predicts-weather-in-minutes-and-its-beating-the-best/

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

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