New eye implant restores vision.

"A new electronic eye implant has restored reading vision to people blinded by dry age-related macular degeneration. In a major trial, patients using the PRIMA implant and augmented-reality glasses were able to see letters and words again after years of darkness." (ScitechDaily, Solar-Powered Eye Implant Restores Reading Vision)

The solar-powered eye implant restores reading vision. These types of innovations are coming. Into everyday use. Those microchip implants could make a person see in the dark. If there is an IR and thermal IR vision. The fact is that these kinds of microchips are tools. That can make it possible to combine humans with machines in new ways. The eye-implanted microchips can act as screens. That makes it possible to create a connection with the internet without the brain implants. 

The microchip that restores vision can send that data into the nerve, or it can act as a screen. The system can transmit those signals to the optic nerve or straight to the visual cortex of the brain. That requires a connection between that chip and the visual cortex. 

The last version is the intelligent contact lens that can revolutionize. The human’s abilities. In those systems, the CCD camera is on the other side. And the screen is on the other side. The system can have a miniaturized Bluetooth. This makes it possible to communicate. With other Bluetooth devices. 

The same technology is used with those microchips. It can be used with intelligent contact lenses, which are a lightweight method. To complete the human-machine interface. The intelligent microchips can accomplish the task. That we can call. The technical remote view. Those microhips can collect information from drones and other tools. Which have the compatible systems. 

There is a possibility that the animal. Like some bird. Could get this microchip. And then the GSM- or radio transmitter. That allows it to transmit everything that it sees to the ground stations. Small-sized data transmitters can be connected to the feet of the bird, like message capsules are connected with a bird of prey. Or they can be surgically implanted under the chest of the animal. Those systems can transmit voice and images to the observers. Those microchips can involve microphones. And they allow operators to see how real animals behave. They can also be used in robots as tools that can collect information and share it between other actors. 

https://scitechdaily.com/solar-powered-eye-implant-restores-reading-vision/

The mosaic model can be a novel approach to creating AI.

   The mosaic model can be a novel approach to creating AI. 

The regular model for creating AI is the large language model, or LLM. That means that. Developers must have control over large data masses. And large code structures. All large code structures are complicated. Because they involve a lot of code. And there are always some kind of errors in the code. That means, when the number of code lines increases, there are more possibilities to make errors. Making the AI is like making a statue. When the system turns more sophisticated. And more advanced, the development process turns slower. When we want to make statues, the first steps are always fast.

 But when we are closing the goal, finishing details takes more and more time. The finishing process just before the statue or product is ready for delivery to customers. Takes most of the time in the development process. The same way. Finishing and detecting errors from the data structure takes most of the time in the programming process. The problem is this: the LLM requires many event handlers. And each event handler is an independent algorithm. That means LLM is a large number of algorithms that operate as a whole. 

The problem is that the LLM rises like dough. That means there are more and more algorithms that must operate as one system. And when the code mass. And the data mass that the system operates on is both large. There can be lots of errors. The AI is a tool that can detect errors in other programs. But the system is not very effective if it must search for errors in its own code. The outsider algorithm can make error detection. AI needs a model. That it can compare its code to. With the code model. Actually, the outsider AI makes the comparison process with two other language models. 

And the problem is: when a new AI model comes. There are no models that the developers can compare their code to. Without models, it is impossible to compare even billions of code lines, which can involve minimal errors. But when there are billions of code lines, and let’s say. There is an error in 1000 lines; searching those codes is a long-term process. That requires carefulness. 

The modular, mosaic model helps expand the AI. 

The mosaic structure or the morphing neural network. That can involve multiple independently operating small language models. It can make it possible to make a flexible and elastic system. Every brick in the mosaic structure is an independently operating server that runs an independent small language model, SLM. Each SLM is a module that involves a certain skill. If the system doesn’t need a module. It can put the server that runs the module into sleeping mode. That makes it more energy efficient.  When developers want to give a new skill to the AI. They can make a new SLM and then connect. That thing to the entirety. 

Researchers say that the future belongs to small language models, SLMs. SLMs are lighter; they involve less code, which makes the development process easier to handle. The SLMs can also operate as a whole. This means: each SLM can operate independently. But those things can also form the virtual entirety. That entirety is like a mosaic. Each SLM has certain skills. When the user sends signals to the system, the SLM knows. If it has that skill or capacity. If the SLM doesn’t have a match. That system forwards the message to another language model, which has the database. That involves data about the SLMs and their skills. And the system sends that information to SLM, which can make the job. 

The idea is that each bite of the mosaic can be written independently. Which means developers can make new modules for AI. And then collect them into  a mosaic. The mosaic-type developing means that. Programmers can control the code better. That also decreases electric use, because if those modules or parts of the mosaic are not required, the system can put its servers to sleep. A mosaic model or morphing neural network structure allows developers to make an elastic and flexible system.