Is AI a black box?

In the black box model, the only thing that means is the thing that the outside observer sees. That thing was the primary element in early 20th-century psychology. And the most modern observation tools are changing that thing. But in the early 20th century the brains were totally unknown. There was no change to research living brains. When EEG systems developed researchers could investigate the brain shell electricity. 

But things like PET and MEG scanners open new ways to see how brains work. But if we think of brain research as the box model, the early 20th-century models were black box models. The modern scanners brought the glass box or white box model to brain research. And the AI brought the grey box to neurology. That means the brain-computer interfaces, BCI, where researchers use brain electricity to control computers and soon read thoughts. 

When developers use the black box method to test programs they simply test that the program works. When we make the black box model for psychological learning methods, we can think about some 9-year-old child. That child can read almost everything and we can put that person to read even complicated scientific articles. The child can read those words but that person doesn’t understand what those things mean. The black box means that the actor can make many things, but the action is the only thing that the outside observer sees. That means that black box applications are not as safe as they could be. 

And most of the computer applications are black boxes for users. A regular user sees the interface and that’s enough.  In the white box or glass box application test, the tester tests the code. In the grey box, the test unit tests the functionality and code in the case of programming. The fact is that the AIs that we see are black-box applications. We see only the command line and the answer or thing that the AI makes. We don’t actually know even if the images and texts that we order the AI to make are made by some humans. 

In the case of the black box, the only thing that matters is that the system gives the right answer. The way the system makes that answer doesn’t matter. The only thing that the user sees means something. 

Is AI a black box? The idea of AI intelligence is something that is handled very little. We know that AI can solve many problems independently, but AI doesn’t know what it really makes. The AI can know many things, but it cannot have deep knowledge about those things. The model is taken from the black box psychology. In black box psychology, the key element is that the behavior that an outsider observer sees is something that we can accept. That means the AI just mimics human intelligence. The black box model means that the AI can give the right answers for some mathematical problems. 

But the same AI cannot make anything else. That is the idea of the black box. In the black box model, the thing that the AI gives the right answer is enough. The AI must do only things that the operator orders. So when the operator asks about the uranium enrichments and something like that the AI must give the answer. It must not make its own connections to things like weapon development. There can be things that deny the AI to give orders that can cause damage to operators or their environment. But those orders are in the AI’s code. The AI doesn't make those orders itself. 

The AI is sliding to the grey box application. For making autonomous learning the AI must have access to its source code. And the second thing is that the AI must have the ability to test the code. The AI can involve three parts. The system that creates the code. Another system that tests and accepts the code. And the last system that keeps the backup copy of the AI source code. A backup is needed for the errors. The system should have the ability to reject the code that is not functional. 

Quantum entanglements and human consciousness.

Researchers noticed that human brains emit light. That very weak light that very sensitive sensors see is the thing that causes interesting ideas and thoughts. The fact is that we know that there is nothing meaningless in human brains. And that strange light must have some connection to brain activity. The question is can part of our thoughts be based on quantum entanglement between some electric or photonic field in human brains? 

The human brains have the capacity to feel magnetic fields because axons transport electric signals. The question is what parts in our brain make that entanglement? Do neurons trap ions like protons into the ion pumps and then make quantum entanglement with them? There is suspicion that the myelin cylinders are the key element in the brain's quantum entanglement. 

If that structure is the thing, that is behind the human brain's superiority it would be the ultimate boost for quantum computing. Researchers can copy that structure into the quantum processors. And make room-temperature quantum computers possible. 

The quantum entanglement can be made between axons or electric fields around axons. We know that human brains will not make anything that it doesn’t need. And the thing is that the very weak light in brains can have its purpose in the thinking process. There is also another interesting thing that researchers noticed. The human brain cells are growing in old age. The memory cells make new neurons all the time. The reason why our cognitive abilities decrease when we turn older is that our brains lose more neurons than they can replace. 

"Liu et al., Physical Review E, 2024

"A closer look at myelin cylinders and its location along the neuron’s axon." (Popular mechanics, Quantum Entanglement in Your Brain Is What Generates Consciousness, Radical Study Suggests)

The finding of the thing. That makes superposition in human brains. Can uncover and supercharge the quantum computer's advance. 

Or neurons start to remove connections faster than before. The destructive thing is that the number of axon connections will decrease so fast that brains cannot adapt to that situation. Our brains simply don't have time to transport memories to the next neuron generation. So do we use our brains less in middle age than in young ages? Do our brains cut so many useless axon connections that they cannot save memories? 

But the problem with alcoholism and some other brain damage caused is that those things destroy brain cells faster than the new brain cells can form. When the memory cell creates a new brain cell, that cell is meaningless without its memories. Brain damage sometimes means that the brain memory neurons have no time to send the memories to those cells. That makes them "empty". 

If those neurons exist they cannot perform the same duties as their precursors can. The cell loses its instructions on how it must make those things. Without those memory units, the neuron cannot do anything. The ability to create new neurons in the old ages makes it theoretically possible to input data, or “train” those new cells and then inject them into human brains. 

The big question is does AI make us less intelligent than our precursors were? The thing is that if a person uses lots of AI the person uses less brain capacity than a person who uses less AI if we think about the neurological aspect, if brains do not use some neural tracks that means that neurons remove those tracks. So if a person writes all texts and draws all things using the AI that can decrease the use of axons and that can decrease the IQ if that happens over a long period. When a person doesn’t use neural tracks that means brains will remove those tracks. 

When people use artificial intelligence for essays they must not think. They must not collect information and the main thing is that they must not process that data. The AI will give them a correct set. And that doesn't give them a chance to process and taste information. In the worst case, the student simply copy-paste the test task to AI. And that makes the essay for them. That doesn't require very much thinking. And in that version, the student cannot advance very much. 

So that means that it’s necessary that people use their brains for thinking. Without thinking, brains disconnect their connections. People say that we should read books and advance our way of thinking. But the problem is this: we have no time to read. 

https://www.euronews.com/next/2025/06/21/using-ai-bots-like-chatgptcould-be-causing-cognitive-decline-new-study-shows

https://www.laptopmag.com/ai/chatgpt-study-by-mit

https://www.popularmechanics.com/science/a65368553/quantum-entanglement-in-brain-consciousness/

 https://www.sciencealert.com/your-brain-emits-a-secret-light-that-scientists-are-trying-to-read

B https://scitechdaily.com/brain-cells-keep-growing-even-in-old-age-study-finds/

The new genetic engineering beats Sci-Fi tales.

The new systems are making genetic engineering more powerful than ever before. The biological artificial intelligence called PROTEUS can usher in a new era for medicine and gene therapy. When we think about things like cancer and blocked blood vessels there is the possibility to send new small robots to destroy those tissues and open blockades. 

The problem is that those robots are hard to control in the human body. AI-controlled biorobots can solve that problem and maybe in the future, genetically engineered bacteria can destroy wanted cells. Or maybe those cells can make much more than just remove cancer cells from blood. The artificial amoebas can also be used to transport tissues in the damaged areas of the human body. The artificial amoeba searches the point where the damaged tissue is. 

Then the amoeba closes the blood vessel and then the mRNA or DNA reprograms that amoeba into the tissue that fixes the damage. Researchers have noticed that the brain's memory centers are constantly generating new neurons. That thing makes it possible to create systems that can used to recover memories in the case of brain damage. The genetically engineered amoeba can travel to damaged neural areas and then transform into neurons. And the problem is how to transfer the memories or skills that destroyed neurons involved into the new neurons. 

When a memory cell creates a new neuron and transfers its memory to that cell it's possible to steal those cells. And then put them into the freezer. The artificial parasite can go to the brain and steal those cells. Then the genetically engineered mosquito can call those parasite-robots to it and then transfer biorobots to the laboratory. The AI can read those memory blocks. And maybe, sooner than we expected, that thing allows researchers to read people’s memories without brain implants. 

The ability to create 3D printings in the cells creates new ways to reprogram cells. The 3D printer simply makes the mRNA molecule in the cell. And that tool can adjust the cell's purpose anytime when researchers want. 

Genetically engineered cells can also be used to transport data from the chemical memory DNA or mRNA to the computers. The idea is that the cell can send electric impulses or blink the bioluminescence light to the data transport. Genetic engineering makes it possible to make almost everything. The genetically engineered mice that had the human genome started to be discussed. And that is one version of the new visions for genetically engineered animals. In visions, intelligent pets are animals whose mission is to assist their masters. Those intelligent pets are things that are opening new visions for bio-engineered creatures. 

What would you do with talking mice? If the AI can communicate with those creatures like talking mice, those creatures can tell us what animals talk. And the ability to talk with animals would open new roads to biology, ecosystem understanding, and many other sciences. 

And all those visions are not things that feel good. 

We know that people like Kim Jong-Un want things like super soldiers. And new technology brings vision about the super skills that a person can have only when those skills and abilities are needed. That means that person gets the super muscles only when that person is frightening. 

When we think about the possibility of changing genomes in the human body we face the ultimate dream of human history. That dream is about the superhuman. The superhuman is a creature that is stronger and more intelligent than a regular human. And the product of that dream is the super soldier.  Genetic engineering makes biological creatures like humans the product. The new tools like self-amplifying RNA, saRNA make it possible to customize human skills for every situation. 

The ability to adjust the human intelligence level and transfer things like wolf’s behavior genomes to a person's body makes it possible to create soldiers who are obedient. That thing makes those people perfect soldiers. Otherwise, that genome makes those people dangerous in the wrong hands.  But what if the system can remove that ability when a person is out of service? The idea is that the person, or creature has some ability only when that creature requires that ability. '

https://www.earth.com/news/life-copying-itself-scientists-create-a-self-replicating-rna-system/

https://medicalxpress.com/news/2025-07-scientists-biological-artificial-intelligence.html

https://www.sciencealert.com/brains-memory-center-never-stops-making-neurons-study-confirms

https://www.sciencenews.org/article/3d-print-elephant-inside-cell

What separates us from AI?

Today we use lots of time to think, why does AI decrease our IQ? The answer is this: this modern time where we live benefits superficial people. Our working life encourages us to have maximum velocity. There is nothing wrong with the velocity-based working life. But the problem is that the measurement tools for velocity are things like how many executions we make during our working day. The measurement tool can be how many screws we tight. Or how much money we bring to our employer. 

Deep thinking is not encouraged in our working life. When somebody sits in a coding company, that person should use the AI assistant. Can you even seriously imagine that you would go to the library and borrow a book about the problems? And would you have time to stop deeply thinking about things that something really means? How often in the week, do we discuss philosophically and think deeply about things that we really see? We can do many things without deep thinking and logic. 

And when we think about things like some 1970s chess simulators, we must ask ourselves are those things really thinking? Do some ATARI, or Commodore 64 really think? It can drive a car on screen, but does it think? The system can move chess buttons and win chess games or some formula games against humans. But is that a mark of advanced thinking? Or does the horse, who sees three fingers and knocks the floor three times using its hoof, be some doctor of philosophy? Is a chess simulator with 64 kb memory more intelligent than some university professor? Maybe that thing is not as versatile as a professor. 

The IQ is something only if we compare it with something else. If we play chess alone or make something else, we don't need to be intelligent. If we are surrounded by people who have an extremely high IQ, in that case even a high IQ doesn't mean impressive. Same way. If our only opponent in a chess game is Garry Kasparov. That makes all of us seem like very bad chess players. Then we can think how ordinary chess player Kasparov is. Did an ordinary player play 2533 matches at the world champion level and win 1371 of those games? That means 54,13% winning games. But that happened at the highest possible level of the chess game. So does an ordinary player ever reach that level? 

But if the professor wins the AI in chess that is not news. The news is that the professor, some AI chatbot, or quantum computer loses a chess game against that machine. Nobody cares how many things the professor made before that chess game. Nobody even cares if the professor plays that person’s first chess game. And nobody even asked if the AI played chess before, or did the AI even knew how to move buttons. In the same way, a professor might not necessarily play chess at all. The fact is that all geniuses don’t even play chess. And if AI learns like humans, there must be something there that gets things like button movements. The computer can play chess but it might not do anything else. 

Normally we say that AI simply mimics things and then it doesn’t have a deep knowledge of things that it makes. When I read about that kind of thing, I sometimes remember one question from philosophy exams. That question is: “What separates philosophical thinking from the every day, or regular thinking?”. The answer is that philosophical thinking is deeper and more analytic than regular thinking. And that brings new questions into my mind. That is when we last exercise philosophical, deep thinking?”. When we do something, like turn screws in workplaces, do we really think about the purpose of that action? 

How deep out thinking? And how deeply do we think about things that we do in everyday life? The thing that’s enough is that we do what we must and that’s it. We have no time to think deeply about what some screw or other things can do. We simply do our job and that’s it. The thing is that humans learn through mimicking. We know many things. We know how to drive cars and use computers. We know how to fly airplanes and still, we don’t know anything about those things. We can drive cars. But we don’t need to know what happens in the car when we pull the gas pedal. We know that cars accelerate, but we must not know how cars make that thing. 

We could put the car to react with the gas pedal two ways. We can make physical contact between the gas pedal and the engine. Or we can use a camera that registers the gas pedal’s position. Then the AI accelerates or brakes the vehicle. For that system, the AI doesn't need any deep knowledge of things that it does. The system must simply accelerate the electric engines if we use electric cars. And the fact is that the AI must not even know what an electric engine is. When a car accelerates the system can involve code there is the word “engine”. Then some control circuits have a code that makes it react to the signal that is meant for the engine. 

Same way, if we hear the word that is our name, we automatically react to that thing. Our name is the thing that activates our attention. Sometimes we think about our names. But we forget that we learn that thing. Why cannot our name be C3PO? Because our parents didn’t give that name to us. Our names are “Jacks” and “Jills” because our parents gave those names to us. But have we ever wondered why some names are reserved for girls and others for boys?  And then we learn that those words are our names. 

But if our parents would give the name C3PO to us. We would react to that as our name. But do we ever imagine, why cannot our name be C3PO? Because we never thought that before. Then we can go back to begin, and ask how to describe thinking. Does thinking mean that we think how many times we hit some nails? Or does thinking mean how many chess games we learn? 

The thing is this: if we drive about 10000 kilometers without accidents or we win millions of chess games in our life that is not news. The news is that if some robot car drives off the road. Or if some supercomputer loses a chess game to some ATARI chess machine. Those things can be translated into that maybe the ATARI chess machine is more intelligent than humans and supercomputers. 

Training determines the abilities of the AI.

The new remote-controlled robot uses technology that allows it to teleport all human movements to that robot's body. That thing turns so-called external, or exobodies true. That nobody can operate in every mission where humans can. This kind of body can operate as an AI-training tool. The operator controls that robot in different situations. Then that system can share its data with other full-automatic robots that operate independently. In the robot world the word “independent” doesn’t mean necessary the same as in the human world. An independently operating robot is a robot that can do its duties without human assistance. That kind of system can operate under the control of data centers. 

So, those systems use the internet for the remote control of the robot body, and that computing capacity is not high enough to run complicated algorithms that do things like walking in the city and visiting shops to buy things. The fact is that the training of the AI determines its abilities. The human-shaped robot is like a screwdriver. The AI that controls that system is the thing that makes it capable of operating in many situations. The first real robocops are coming to the streets in Indonesia. 

Many armies and civil defense and rescue organizations test robot dogs that can search things like mines. Those systems can carry lasers or even missiles in the back. So that makes them able to destroy tanks and other vehicles. Those robot dogs can have quadcopter propellers in their legs. The system can turn the twin wing rotors in the same line. And then pull them in. In use, those systems can push propellers out. Turn the legs to the side. And then turn those propellers into an X-position. 

Researchers trained the Chat GPT for space pilots. That system did its mission very well, and that means the new drones can get AI-based autopilots. And in the wrong hands, those systems are terrifying. That means basically anybody can train their own AI-based aircraft pilot that can operate drones or, why not, full-scale aircraft. There are risks in those applications. The same autopilot program that controls the drone can control full-size aircraft. 

Some researchers are worried that AI chatbots can start to create biological weapons. Those systems can make almost everything. AI-controlled laboratories are things that can revolutionize material and molecule research. That means that those laboratories can also connect the DNA molecules together. Those systems can also make artificial organisms using AI-controlled nanotechnology. 

The self-replicating or self-amplifying mRNA molecules are created for self-replicating vaccines. Those self-amplifying (m)RNA (sa(M)RNA) can also unlock new tools for controlling nanorobots if a small miniature robot can carry saRNA molecules to the right cells. And that thing can make it possible to create the system that orders those cells to die. That mRNA molecule can order the cell to shut down its protein synthesis. Those self-amplifying molecules can also act like chemical computer programs. And that makes new tools to control nano- and biorobots. 

The ability to produce and self-replicate mRNA molecules in a dish, outside the cells. That opens new paths to genetic engineering. And another thing is that this kind of ability makes it possible to create new mRNA and DNA-based computers and data storages. 

There is a possibility to create the artificial mRNA molecule that self-replicates in the dish. That thing makes it possible to create the mRNA that reprograms the cell. There are two ways to make a large number of artificial cells. The first way is to create artificial DNA or mRNA molecules. The researchers can change the DNA from inside the cell’s nucleus. The other way is to use the mRNA molecule to reprogram the cell organelle and force it to create artificial mRNA viruses. 

The new method is to create artificial mRNA or DNA molecules. Then that molecule can self-replicate. Then researchers can take cells in control and inject those mRNA molecules into cell organelles. Or they can exchange DNA from the cell nucleus. That makes it possible to create artificial cells. The difference is how to produce that genetic material. In the last case, the genetic material is produced separately from the cells. And that makes this genetic material easier to control. That material opens new doors for DNA and mRNA-based computing and controlling miniature robots. 

https://www.birmingham.ac.uk/news/2023/ai-could-be-used-to-develop-bioweapons-if-not-regulated-urgently-says-new-report

https://futurism.com/scientists-chatgpt-controls-spaceship

https://www.rudebaguette.com/en/2025/06/real-life-avatar-tech-arrives-new-capsule-teleports-full-body-human-motion-directly-into-remote-controlled-robots/

https://www.rudebaguette.com/en/2025/07/theyve-gone-full-robocop-indonesia-unleashes-humanoid-police-robots-to-hunt-criminals-and-crush-the-drug-trade/

https://www.science.org/content/blog-post/first-self-amplifying-mrna-vaccine

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

https://en.wikipedia.org/wiki/Self-amplifying_RNA

New types of particle accelerators revolutionize civil and military research.

"Conceptual illustration of micronozzle acceleration (MNA). A solid hydrogen rod is embedded in an aluminum micronozzle, which channels and focuses plasma flow to optimize proton acceleration. Credit: Masakatsu Murakami"(Phys.org/Tabletop particle blaster: How tiny nozzles and lasers could replace giant accelerators)

Lasers and micronozzles bring the tabletop particle accelerators closer to reality. Those systems use laser beams and magnetic fields to accelerate protons and electrons. Those systems can raise the electron’s energy level. The new system that combines liquid hydrogen and laser beams can raise the proton’s energy level to 1 GeV. That kind of ion system is much smaller than CERN particle accelerators, The new accelerator type can revolutionize civil and military technology. The ion engines or plasma ion engines that use high-energy plasma to create thrust can use that new particle accelerator type. 

The system can inject high-energy particles into gas and that system turns plasma into a high-energy level. The ion engine that can expand plasma like a regular rocket engine can form higher thrust than the regular ion engines. The plasma-ion engines combine ion and rocket engines under the new hybrid concept where high-energy plasma raises the gas temperature. There is a possibility to use antimatter injection to create high-energy plasma. The antiproton or positron injection will raise the gas's temperature and that creates thrust. 

"Concept of micronozzle acceleration (MNA). The MNA target employs a micronozzle housing a solid hydrogen rod (H-rod), precisely placed near the nozzle neck to maximize proton yield. Acting as a "power lens," the micronozzle focuses the incident laser energy onto the H-rod, enabling efficient and localized energy deposition. This configuration significantly boosts proton acceleration near the nozzle exit, outperforming setups lacking the nozzle structure. Credit: Scientific Reports (2025). DOI: 10.1038/s41598-025-03385-x" (Phys.org/Tabletop particle blaster: How tiny nozzles and lasers could replace giant accelerators)

*The implications are wide-reaching:

*Energy: Supports fast ignition schemes in laser-driven nuclear fusion.

*Medicine: Enables more compact and precise systems for proton cancer therapy.

*Fundamental science: Creates conditions to simulate extreme astrophysical environments and probe matter under ultra-strong magnetic fields.

(Phys.org/Tabletop particle blaster: How tiny nozzles and lasers could replace giant accelerators)

********************************************************************

"Illustration of a spacecraft powered by nuclear propulsion and solar sails traveling towards Sedna. Image generated by AI." (RudeBaquette, “We’re Finally Fast Enough”: Nuclear Propulsion and Solar Sails Could Blast a Spacecraft to Sedna in Just 7 Years)

In that spacecraft, the solar sail can act as a reactor cooler. The futuristic system comprises a solar sail and a nuclear thermal engine that can boost the rocket into a very high speed. And the atomic engine can use pulsed plasma to create ultra-high thrust. Begin of the journey the system can use both, solar sail and a nuclear engine for maximum thrust. Then at a longer distance that solar sail can turn into a cooling system. 

These kinds of plasma systems are dangerous in the wrong hands. The ion cannon is basically the same system as the ion engine. The main problem with ion cannons is how to keep the particle beam in its form. Particles with the same polarity repel each other. There is a possibility to shoot electron beams in the ion beam. Or the target can be loaded with opposite-polarity electricity that pulls those ions to it.

But there is also the possibility of creating plasma bombs by using ion technology. Basically, a plasma bomb is only a magnetic tank where high-energy plasma hovers away from the wall. The laser, microwave, or particle accelerators can create that plasma. The particle accelerator can load high-energy plasma into the bomb by using the positron injection. When that bomb drops to the ground its shell is broken. And that releases plasma from 10- 10000 or even millions of degrees Celsius to the air. Theoretically, plasma bombs can replace thermonuclear weapons if they can create plasma that has a temperature of tens of millions of degrees Celsius. 

The antimatter bomb is the tank where antimatter hovers away from the walls. The small-sized particle accelerator that is in the airplane can load antimatter into those capsules that the system shoots at the enemy. The antimatter capsules can also be used as fuel pellets for antimatter rockets. 

https://physicsworld.com/a/micronozzle-could-give-laser-driven-particle-accelerators-a-boost/

https://phys.org/news/2025-06-tabletop-particle-blaster-tiny-nozzles.html

https://www.rudebaguette.com/en/2025/07/were-finally-fast-enough-nuclear-propulsion-and-solar-sails-could-blast-a-spacecraft-to-sedna-in-just-7-years/

The String theory and the 5-plet problem.

"Concept image of strange particles in an atom." (InterestingEngineering)

The 5-plet is a strange 5-particle group detected in the Large Hadron Collider that can challenge String theory and give answers for Dark Matter problems. The problem is that the 5-plet must not exist in the String model. But it still exists. When we think about String theory itself, that theory seems to give answers to every problem in the universe. String theory has the same problem with the Big Bang theory. That theory is commonly accepted, even if it's incomplete. String theory is made for filling the Big Bang theory giving answers to where the material that formed the Big Bang came from. The purpose of String Theory is to answer the question: What “exploded" in the Big Bang? 

String theory is not the same as the Grand Unified Theory, GUT. Some people think that the String theory gives answers to all problems in the universe. 

That is not even close to the truth. The String theory handles small parts of the entirety. And the thing that supports some kind of superstring’s existence is the cosmic web. The main idea of the String theory is that the internal superstrings or energy channels form a dimension. And the universe is like a bubble in one extremely large superstring. Those strings also form material and everything. And every single particle is a bubble in a superstring. We often forget that the Superstring theory is a repair tool for the Big Bang theory, which should explain where the material and energy came from. 

(InterestingEngineering)

The problem with the Big Bang theory is this: it doesn’t answer one of the most critical questions in physics. Where did that energy that formed the Big Bang come from? The Big Bang theory's basement is in the wave-particle duality, WPD. That means wave movement can turn into particles and particles can turn into wave movement. But without wave movement, there are no particles. So there are many updates in the Big Bang theory. The most modern model is that time itself formed the Big Bang. And the Big Bang was rather the Big Burst than the single Bang. That means in modern models the Big Bang was a series of events that formed the material in the form as we know it. 

That means the Big Bang was some kind of annihilation, but it doesn’t answer where those particles that formed the annihilation came from. One of the suggestions for that question is that there formed a giant black hole that exploded.  That black hole could have formed from wave movement that existed before the Big Bang. Or, another suggestion is that the hypothetical black hole was a remnant of the universe that existed before our universe. The multiverse model explains the space as a dimension where Big Bangs happen all the time. And universes form in the crossing points of other universes' radiation. That radiation pushes particles or wave movement into the points where their gravitational effect starts to form new universes. 

But proving that the model is not a very easy thing. If there is material outside the universe, that material is so cold that we cannot see it. But the multiverse is a logical conclusion that begins from the galaxies, galaxy clusters, and superclusters. The idea is that the universe itself is part of a larger entirety. But then we face another way to answer the problem of where everything came from. That answer is written in a very incomplete Brane theory. The idea is that the dimension or third dimension simply collapsed. That opened the channel from the fourth dimension straight to the second dimension. That energy channel formed the event called the Big Bang. If that model can be true the 3D material cannot close that channel because its energy level is too high. 

https://interestingengineering.com/science/ghost-particles-that-could-snap-string-theory

https://penntoday.upenn.edu/news/things-know-can-data-large-hadron-collider-snap-string-theory

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

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

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

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

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

https://en.wikipedia.org/wiki/Wave%E2%80%93particle_duality