AI gives superpowers to personal computers.

"Diffeomorphic Mapping Operator Learning, DIMON, a new AI framework, accelerates modeling by solving partial differential equations efficiently, reducing computation times from days to seconds. Tested in heart simulations, it promises transformative applications across engineering and science." (ScitechDaily, AI Breakthrough Solves Supercomputer Math on Desktop PCs in Seconds)

"The adaptable technological solution has the potential to revolutionize engineering designs." (ScitechDaily, AI Breakthrough Solves Supercomputer Math on Desktop PCs in Seconds)

"A breakthrough in artificial intelligence is making it possible to model complex systems—like how cars deform in crashes, how spacecraft endure extreme conditions, or how bridges withstand stress—at speeds thousands of times faster than before. This innovation allows personal computers to tackle massive mathematical problems that once demanded the power of supercomputers." (ScitechDaily, AI Breakthrough Solves Supercomputer Math on Desktop PCs in Seconds)

"The new AI framework offers a versatile and efficient method for predicting solutions to challenging mathematical equations. These equations are crucial for modeling phenomena such as fluid flow or electrical current behavior in various geometries, commonly encountered in engineering and design tests." (ScitechDaily, AI Breakthrough Solves Supercomputer Math on Desktop PCs in Seconds)

New AI gives table computers the supercomputer abilities. The idea is that the system uses the complete and complicated models. 

That makes it unnecessary to begin all modeling processes from the beginning. The system can use models that some other computers have made. 

The idea is similar to the picture. So we can use mosaic pictures as an example. Developers make it by using ready-to-use sub-elements. The ability to use free elements is making data-handling operations more effective. That increases the power of regular computers. But it also fits in use of the supercomputers.

"A Revolutionary AI Framework: DIMON. Details about the research appear in Nature Computational Science. Called DIMON (Diffeomorphic Mapping Operator Learning), the framework solves ubiquitous math problems known as partial differential equations that are present in nearly all scientific and engineering research. Using these equations, researchers can translate real-world systems or processes into mathematical representations of how objects or environments will change over time and space." ((ScitechDaily, AI Breakthrough Solves Supercomputer Math on Desktop PCs in Seconds)

And the thing that can boost that ability is the memory handling tool that cleans memory when the model is ready. The system develops models as layers. Every single layer is an independent model. When the model is ready the computer can store it or give it to another computer. 

Then it can clean its memory. Then that system can receive the model that another computer has worked. And continues to develop or build the new model. In that model, the AI-based systems play ping-pong balls with models that they create as stages. In every stage, the system can connect more and more complicated objects into that layer. The system handles program data like Photoshop handles its layers. 

The image that the developer makes could be an example. The city area image. 

The developer or system can select items for that image from the data library. The system can use things like images of houses. That made for some other purposes. 

And that is the idea of object-oriented programming. The idea in C++ and similar programming languages is simple. 

They involve libraries of commonly repeating operations. That means the user of that language doesn't have to program things like simple calculations from the beginning. They must just load the 

Those libraries (like Stdio.h) deny the need to do basic things every time the programmer starts a new job.  

The programmer can use libraries that involve responses for the orders that the programmer writes. Using the programming language. 

The new AI-based model is a new and very advanced version of the old object-oriented programming. The system can collect complicated models from libraries. 

Oor from the net. And that makes it possible for the table computers to get steroids. The other thing is that the computer can take another computer to its work. The system can make the digital twin and download data to the other computer while it cleans its memory. The ability to clean memory while the system develops the model makes it more powerful. In that model, the model is developing in stages. 

When the system makes the new model it can transfer it to its digital twin. And the system can clean the memory of the first computer. The AI-based system can also call more computers to handle the operation. 

https://scitechdaily.com/ai-breakthrough-solves-supercomputer-math-on-desktop-pcs-in-seconds/

https://www.nature.com/articles/s43588-024-00732-2.pdf

https://pubmed.ncbi.nlm.nih.gov/39653845/