Teaching physics allows AI to make autonomous discoveries.

The AI is a suitable tool to make astronomical discoveries. All objects in the universe are following the laws of physics. And things like dangerous asteroids can search by using AI-boosted telescopes. The AI is an excellent tool for searching for changes from the images taken during certain periods. The AI can see if some point is moved. And that is the mark of the new asteroid or even planet. The AI can search thousands of objects.

And that makes it an ultimate tool for astronomers. Searching new planet is not very dramatic. Astronomers are just looking at the points in two images taken in a certain period. And if one of those points is moved there could be the planet or dwarf planet or asteroid. That work is very boring. And it can leave to the AI.

The AI can search for changes in those points and then check from the database. If there is some asteroid in that trajectory. Then the AI can take an image of that asteroid and compare it with images of known asteroids. That thing makes it possible to compare those images by using face recognition software. And that thing can tell if there is a similar asteroid in the database. The fact is that there could be many dwarf planets and asteroids that have the same trajectory.

Physics is one thing that can be useful for AI that should make discoveries. Physics and mathematics are things there are strict rules. And that thing is necessary when researchers are making the AI that can make discoveries. Things like Kepler radius are always the same. And the Kepler radius depends on the size of the star. These kinds of things are the tools that AI needs to find new planetary systems.

The problem with new astronomical tools like JWST-telescopes is that they send very big data mass. And that data mass requires analysis. Finding planetary systems and exoplanets is quite boring work. The system must wait that the planet will travel between Earth and a distant star. And then the research team must search for changes in the star's brightness.

This kind of method is useful. But it requires intensive measurements and a little bit of luck that the astronomers can notice the changes in the brightness.

To observe changes in the star's brightness. The telescope must keep aimed at that star all the time when the planet makes its overpass. This is why the most exoplanet systems are orbiting red dwarfs. The orbit time of those planets is only a couple of days. And all the time when the telescope is aimed at a certain star. It is reserved. And out of other work.

Red dwarfs are so small that planets are causing wobbling in their trajectory. And that's a good hint for astronomers. But if we want to search for habitable planets we must realize that those planets are orbiting very far away from very massive yellow stars that are giants to red dwarfs. Even our entire solar system doesn't have a big effect on the trajectory of the sun.

Planets of red dwarfs are cold or they are locked. But if we want to search for planets that are orbiting yellow stars like our sun in its habitable zone we are facing one problem. The planet's overpass takes longer. And there is the possibility that the trajectory of that planet is askew that planet will not cross the plate of the star.

That kind of planet requires more intensive work. AI is a very suitable tool to hunt planets. It can measure the changes in the brightness and changes in the dust disk around stars. Those deifications are suitable to find exoplanets from around young stars.

The problem with hypothetical technical civilizations is that they are living on very mature planets. Mature planetary systems are cleaned from dust and ice. And that means finding those really interesting planets requires something else than searching for densification from the dust and ice.

https://scitechdaily.com/teaching-physics-to-ai-can-allow-it-to-make-new-discoveries-all-on-its-own/

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

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

https://miraclesofthequantumworld.blogspot.com/

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.

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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,

Cogito ergo sum. I think; therefore I am (René Descartes, French philosopher)

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