Skip to main content

The AI and trust.



What is the biggest problem with the AI? The answer is trust. The AI requires systems. That drives information into the system so that the AI can analyze information. Without information AI makes nothing. Another thing is that the AI collects information from very large areas. The AI can give trusted answers only if somebody can confirm that data. The AI follows the same rules as other systems. There must be error detection and correction algorithms. 

If we want to use AI, we must know the topics, if we want to use that system effectively. The AI itself is well-protected, but manipulating answers can happen by manipulating sources. Sometimes the AI gives wrong answers because it selects the wrong homepages. 

When AI generates answers to questions, it uses the X number of homepages, and then it connects data from those homepages or other databases. The problem is that the AI doesn't think. And if there is some kind of false information. The AI will not realize that thing. 

The big problem for the AI, and especially, large language models, LLMs are these: they require precise and well-written orders to make answers. In the new models to use the AI, LLMs are the system used to generate limited, more effective, precise AIs that operate as the RISC models. The RISC is like a pocket calculator. It has a limited operational sector, but it handles those operations very fast. 


It's an algorithm that controls some machines and communicates with larger-scale  An idea is this: The LLM operator describes the need that the new AI must make to LLM that generates the code. 

One example of this kind of AI model is the DNA analyzing AI. These kinds of systems are meant for one purpose. They might be complicated and involve many modules. But they just analyze the DNA and then compile the results with people with a certain detail in their phenotype. 

The system can cut the DNA into multiple analyzers. Then each one of those analyzers operates with a certain DNA bite. The system operates like a virtual quantum computer. It drives DNA through the laser spectrometer, which opens the DNA chemical code by reading its base-pair orders. 

The laser system can read the DNA and the laser spectrometer can tell if there is thymine, adenine, guanine, or cytosine that the laser illuminates. Maybe those kinds of systems are effective. But the thing is that those systems are tools that highly trained professionals use. Those people know how to ask things from the AI. But the main thing is this. The AI that makes DNA analysis makes only one thing.

It illuminates the DNA with a laser and reads the data using microscopes and spectrometers. The thing that searches for things like hereditary diseases is another AI. The idea is that the system uses RISC processors. And DNA analyzers as groups. The system searches for similarities in the DNA of people, who have a certain ability. 


https://bigthink.com/the-present/when-to-trust-ai/

Comments

Popular posts from this blog

Antigravity will be the greatest thing. That we have ever created.

"Artistic depiction of a fictional anti-gravity vehicle" (Wikipedia, Anti-gravity) Sometimes, if the airships have the same lifting power as the weight of the airship.  It can act like some “antigravity system”. Those systems are based on lighter-than-air gas or hot air. The system can have a helium tank. And the hot-air section whose temperature can be adjusted using microwaves or particles that lasers warm. Those systems are faster to control than some gas flames. This makes it possible. To adjust the lifting power.  If a thing like a balloon has the same lifting power as its weight, the balloon can be lifted to a certain point and altitude. And the balloon stands at that point until something moves it. That kind of thing can make an impression. On the antigravity systems. Modern airships. Like Lockheed-Martin P-791 can look. Like a “UFO”. The system can use systems to move the craft. Or maybe those ion systems are used for plasma stealth systems, if those airships' mis...

Capitalism is a blessing and a curse.

Basically. There is nothing wrong with capitalism. The idea of capitalism is simple. If people like your products, they buy them. And that brings money to your bank accounts. If people don’t like our product, they don’t buy it. And that drives you into bankruptcy. That is the economic Darwinism. If the company cannot sell its products. That removes it from markets.  Other ways. We can say that if the company cannot answer those new challenges, it will be terminated immediately. In the Soviet Union, there was no capitalism. And the competition between companies. Did not exist. That caused a situation where the merchandise. With bad quality being. Entered. Into shops. Without competition, there was no development. And that turned those products old-fashioned. That raised the Soviets' addiction. To the natural resources. To get Western currency. They sold gas and oil to get dollars, which they needed to buy Western technology. That caused a situation. The Soviet technology started to ...

The problem with mirror life.

"Mirror life presents serious dangers, primarily due to its potential to interact unpredictably with the natural world. Without natural checks like predators or antibiotics, mirror organisms could replicate uncontrollably, creating risks that scientists are only beginning to understand. Credit: SciTechDaily.com" (ScitechDaily, “Mirror Bacteria” Warning: A New Kind of Life Could Pose a Global Threat) When we think about artificial life, and especially mirror life. We must say. This technology. It can save billions of lives. But otherwise, those kinds of organisms could be hostile to their mirror forms. The shape of the mirror-life is like a form of a vampire. In movies, vampires look cute. But then. They show their real nature. The mirror-organisms are created for something. They look like original organisms. But they are AI-generated mirror-organisms. The purpose is to control things like hospital bacteria.  Mirror-life is the artificial life created by AI. And genologists. T...