Skip to main content

AI does things differently than humans.



The AI can think. But it's thinking is different than human's thinking. The AI can collect new images from its hard disks like puzzles. But even if we think that AI makes impressive new entireties about things, that are stored in its memory. The AI can't make all things better than humans. 

Humans recognize faces better than AI. The reason for that is in logic that the AI uses. The AI's way of using fuzzy logic is different than the human brain. In AI fuzzy logic is a series of precise logic algorithms. That means the AI has problems comparing two images like faces, if the images are taken from different angles. The AI compares two images by making a matrix of them. And then this system puts those images overlap each other. 

The system doesn't see those images the same way as we see them. Artificial intelligence sees the color and brightness values of images as RGB codes. If there is a difference in light conditions between two images there are different RGB codes. And that thing makes those images seem different in the eyes of AI. 



The human brain sees the image as an image. That makes the human brain less accurate. The brain doesn't remember all the details of the image like AI. The brain remembers some details or main characters about images. And then senses fill those frames. The brain uses more blocks than the AI. So that means the AI is not as good as the brain. If the image that it should compile is from another direction. Or there are some kind of shadows or some other differences from the original images. 

When a certain part of the frame matches with memory, the brains check the databases that are connected with that memory. The brain handles memories as entireties. In the center is an image. And then the other memory cells connected with that image. Those other cells cooperate with cells that control movements or some other things. 


Memory is one interesting thing in the human brain. The purpose of memory is to save people. This thing means that we remember bad things better than good things. The memory is not created for the past. It's created for the future. The memory's purpose is to make us learn from our mistakes. The memory is a library that the brain can use in the future for solving problems. 

For the AI the memory is different. Memory is a static thing for computers. And that means the AI can remember things, that were once stored in a hard disk like those things that happened yesterday. Computers don't forget things. They don't learn new things like humans either. The traditional way to make computers learn new things was simply by making programs for them. 

The automatic learning process is harder to make. The computer requires algorithms that determine details of what it should remember. Or if the computer stores every single detail from the day to the hard disks that system requires lots of hard disk space. The human brain has impressive memory capacity but in the same way, there are limits to its capacity. 


https://bigthink.com/the-present/facial-recognition-ai/


https://bigthink.com/the-learning-curve/why-memory-is-more-about-your-future/

Comments

Popular posts from this blog

The LK-99 could be a fundamental advance even if it cannot reach superconductivity in 400K.

The next step in superconducting research is that LK-99 was not superconducting at room temperature. Or was it? The thing is that there is needed more research about that material. And even if it couldn't reach superconductivity in 400K that doesn't mean that material is not fundamental. And if LK-99 can maintain its superconductivity in 400K that means a fundamental breakthrough in superconducting technology.  The LK-99 can be hype or it can be the real thing. The thing is, anyway, that high-voltage cables and our electric networks are not turning superconducting before next summer. But if we can change the electric network to superconducting by using some reasonable material. That thing can be the next step in the environment. Superconductors decrease the need to produce electricity. But today cooling systems that need lots of energy are the thing that turn superconductors that need low temperatures non-practical for everyday use.  When the project begins there is lots of ent

Black holes, the speed of light, and gravitational background are things that are connecting the universe.

 Black holes, the speed of light, and gravitational background are things that are connecting the universe.  Black holes and gravitational waves: is black hole's singularity at so high energy level that energy travels in one direction in the form of a gravitational wave.  We normally say that black holes do not send radiation. And we are wrong. Black holes send gravitational waves. Gravitational waves are wave movement or radiation. And that means the black holes are bright gravitational objects.  If we can use water to illustrate the gravitational interaction we can say that gravitational waves push the surface tension out from the gravitational center. Then the other quantum fields push particles or objects into a black hole. The gravitational waves push energy out from the objects. And then the energy or quantum fields behind that object push them into the gravitational center.  The elementary particles are quantum fields or whisk-looking structures. If the gravitational wave is

The CEO of Open AI, Sam Altman said that AI development requires a similar organization as IAEA.

We know that there are many risks in AI development. And there must be something that puts people realize that these kinds of things are not jokes. The problem is how to take control of the AI development. If we think about international contracts regarding AI development. We must realize that there is a possibility that the contract that should limit AI development turns into another version of the Nuclear Non-Proliferation Treaty. That treaty didn't ever deny the escalation of nuclear weapons. And there is a big possibility that the AI-limitation contracts follow the route of the Nuclear Non-Proliferation Treaty.  The biggest problem with AI development is the new platforms that can run every complicated and effective code. That means the quantum computer-based neural networks can turn themselves more intelligent than humans. The AI has the ultimate ability to learn new things. And if it runs on the quantum-hybrid system that switches its state between binary and quantum states,