What happens when we get AGI?

What does AGI (Artificial General Intelligence) mean? That is the extension of the large language models, LLMs, that can control every data network in the world. Or the system can control physical tools that are connected under their dome. Normal LLM has its domain. The domain is like a state that involves certain actions. Drone control is one domain, and home appliances are one domain. Those domains can have multiple subdomains. The AGI interconnects those domains under one dome or one entirety. So how far are we from that model? 

The answer is more complicated than we can imagine. We can think that the LLM can control things like microwave ovens, but for controlling those tools the LLM requires a socket that it can use to adjust microwave ovens. So the man-shaped robot can use a microwave oven, or the other version is that the home appliances are equipped with a control system that the AI can use to command it. 

When we connect new things under AI control we can face the same thing as when we try to learn to use some new systems. When we buy something new like a microwave oven, we must learn how to use it. In the same way, the AI must learn to use those equipment. And we have two versions for making that thing. 

To use any tool the AI requires a model that it can use in that operation. The model can be in the central server that runs the AI. But where does that server get the model? That is the point. The operator can teach the AI to use the microwave oven as well as the drone. But the system that is connected to the AI can also involve that model. Things like quadcopters must involve programs that control the rotor’s positions. In those cases the operative model is in the robot, or some other thing. The LLM gives orders to robots where they must travel. 

Then the robot can use its internal systems to navigate and move to the location. But orders for autonomic operations are coming from the central systems. This kind of network-based solution is easier for programmers. In those solutions, every single machine that is connected under the LLM domain has its own operational model. The system is modular and each module is independently programmed. 

Basically, if we think that AGI is the tool that just connects multiple devices under one domain, we could do that thing immediately. We can use man-shaped robots that can do almost everything. But the key word is “almost”. 

 Let’s return to the microwave oven. The reason why it’s hard to make that precise thing is the lack of standard user interfaces. The robot must learn to use every single microwave oven independently. That means it must make an independent model for each microwave oven. If there is a system where we can put seconds and minutes separately, the systems where there are only minutes in the timer are not the same. We learn that difference in minutes. But for robots, we must make an independent model of how to adjust the timer. 

Many systems in the world are so easy to use that nobody has wasted time creating standards for them. Easy systems are easy for people, but then we must think about things like the microwave oven. There are button- or toggle timers and that makes them hard to learn. For robots and AI the difficulty is this in the fact all microwave oven models require their independent model of how to use them. 

The robot must connect images from the user manual to the microwave oven’s interface. There is a possibility that if the system does not learn independently the “teacher” or programmer takes an image of the front panel, and then puts the buttons in the right places. Then the AI can learn the rest of the task from the user manual. 

The AI requires new hardware. Servers that can run the AI must have a lot of power.

"Scientists have created an ultra-efficient AI accelerator that uses light-based circuits instead of traditional chips—making AI faster, greener, and ready for massive scale. Credit: SciTechDaily.com" (ScitechDaily, Scientists have created an ultra-efficient AI accelerator that uses light-based circuits instead of traditional chips—making AI faster, greener, and ready for massive scale. Credit: SciTechDaily.com)

One solution. That can help to save energy. The system recycles the heat of its microprocessors. 

That heat can expand liquids. That is used in freezers. That expanding liquid rotates the generator's wheel. That helps to save energy on those servers. So, operators must bring less energy from outside. 

Temperature makes those servers ineffective. When the temperature rises too high, it slows the computers. Temperature rises oscillation. That raises resistance. The resistance denies the signal going through. 

Or resistance destroys data in the signal. That causes the system. Must raise power to make a signal travel through 

The resistance that temperature damages data structure. That travels in them. So, the system goes in a circle where. It must raise its power to make the signal go through. 

And finally, those wires melt. 

"A Harvard-led team created the first self-contained, chip-based laser that pulses in the mid-infrared – ideal for advanced gas sensing and imaging. This innovation could power next-gen tools for climate science and healthcare. Credit: SciTechDaily.com" (ScitechDaily, Harvard Builds Laser the Size of a Chip, Bright Enough to Map Invisible Worlds) The Harvard laser chip can also transmit data into photonic systems and out from it. 

So, the answer to the problem is the photonic microchips. The system can use photons to transmit data to silicone. 

That means. The system can use a photovoltaic phenomenon when it hits the silicone layer. 

There, light forms electric impulses by shooting electrons away from their orbitals. The photonic microchips can advance AI. Those microchips are colder than the electric system. Those photonic systems can operate for a longer time with maximum power than regular microchips. The photonic microchips can use lasers. To transmit data to them. There are three versions of the photonic computers. 

1) In the simplest version.

Data travels between components in laser rays. 

The system can use flat lasers to transmit data between those components. 

2) The system. The internal structure of microchips uses photonics in data handling operations. 

But prisms and mirrors that the system uses as routers and switches. And gates are electrically operated. 

3) All photonic computers: there are laser beams that transport information. Also transmits energy to those microchips. In those systems, miniature crystals can also aim information in the right way

The difference between electric and photonic computers is that data travels in a laser beam in photonic computers. That means there is no resistance. That means photonic computers are more effective than electric computers. And those systems can be the next tool to develop physical systems that can run complex AI-based systems. 

https://scitechdaily.com/ai-at-the-speed-of-light-how-silicon-photonics-are-reinventing-hardware/

https://scitechdaily.com/harvard-builds-laser-the-size-of-a-chip-bright-enough-to-map-invisible-worlds/

AI mimics human memory to make wise decisions.

  

"A recent study introduces the M2I framework, inspired by human memory, to address limitations in current large AI models such as inefficiency, high energy use, and lack of reasoning. By mimicking brain-like memory mechanisms, the research aims to create machines capable of continual learning, adaptive reasoning, and dynamic information processing." (ScitechDaily, Can AI Think Like Us? New Research Mimics Human Memory for Smarter Machines)

Human memory is like a puzzle. Every single memory unit holds one small part of the information. That the brain stores in it. The thing that makes the memory so flexible is that. There are millions of memory units. That brain can reshape and connect in millions of ways. It is possible to make this kind of memory for computers. Using the memory addresses. In those systems, we can say that memory allocation units behave like pixels in the CCD camera. 

The memory pixels that the AI can reshape and reorder make those systems powerful and flexible. But handling that memory pixel network entirety of the system requires lots of computer power. And advanced operating systems. The memory is more than image. It controls the physical and emotional reactions. When a thing like a robot carries packages the memory stores information on how it picks the merchandise up. 

A robot's memory orders it to move its limbs and react to things that the robot faces. When a robot sees something it searches match from its memory. If there is a match with even and description that description activates the action. 

Memory addresses can act like memory units or memory cells in human brains. Then, those memory addresses can make multiple connections of themselves. They can make millions of forms of the memories that the computers have. This kind of memory is like a CCD chip in the digital camera. The difference between the computer memory and the CCD chip is that the CCD chip turns the image into electric impulses. 

But, this network-based memory handles data stored in the system. The system's accuracy and flexibility depend on the memory unit or memory address's size and number of those addresses. The large number of small memory addresses or memory allocation units can create a more accurate and flexible memory entirety than the small number of large allocation units. 

When the system reshapes the image or puts those memory storages into a new order the small number of large memory allocation units makes the new memory image unsharp. The data that a large memory allocation unit stores is in fixed form. The problem with those data structures is the same as when we use a small number of large pixels in the CCD camera. 

That makes images unclear. The large number of small pixels makes those images clear. The same way the memory pixels act in the computer memory. AI thinks similar way as humans. It collects a group of data pixels and then reshapes them into a new form. 

https://scitechdaily.com/can-ai-think-like-us-new-research-mimics-human-memory-for-smarter-machines/

Life might be more common in the universe than we thought.

"White dwarf stars, once considered inhospitable, may actually support habitable exoplanets. New climate simulations reveal that fast-rotating planets around white dwarfs retain more heat, avoiding the excessive cooling seen in slower-orbiting worlds. Credit: SciTechDaily.com" (ScitechDaily, Could Alien Life Thrive on Planets Orbiting Dead Stars? New Study Suggests Yes)

The search for extraterrestrial intelligence and extraterrestrial lifeforms continues. Researchers suggest that also dead star planets can host lifeforms. So the star that gives energy to those lifeforms must not star at all. Things like white dwarfs, neutron stars, and black holes can also maintain or even make life on planets that orbit them possible. The material disks around neutron stars and black holes can give energy to planets that can form after the supernova explosion. 

But intelligent lifeforms can also drive material to those star remnants' surfaces. The ion cannons can drive ions to neutron stars, black holes, and white dwarfs. And that thing reduces impact energy. That material can form a fusion reaction on those star remnants' surfaces as it forms in natural events. The civilization can also use things like the neutron star's magnetic field and its pulsar beam as an energy source. 

Things like samples from asteroid Bennu make scientists think about life again. The particles of life are more common than researchers expect. 

If the planet that orbits in the habitable zone and has the right chemical and physical conditions can exist long time enough that means the lifeforms can turn intelligent. The lifeforms are not forming as randomly as we might hope. And that means. That there can be more intelligent civilizations in the universe than we expect. But then we can look at the stars around us. There is one candidate. That could host similar lifeforms as Earth. That is the van Maanen 2. That is a white dwarf at a distance of 14,2 light-years from Earth. Those stars' lifeforms might not live if they cannot get out of their system. 

 The white dwarf can be a remnant of a similar star to our sun. That means there is a possibility that the civilization from that solar system is left to the universe. But then we must remember that our solar system and its planets are also the remnants of some ancient stars. This means the planet's formation can begin after the supernova or nova eruption. 

But then again to the intelligence. We know that there must be something that makes evolution favor intelligence rather than a great number of descendants. The fluctuation of the environment caused the situation that the lifeforms must have the ability to learn things and then apply those things in the ever-changing environment. If the planet's environment is too stable. A large number of descendants is enough for a species' survivability. 

But before intelligence, there must be conditions that make long organic molecules possible. "New research shows that fluctuating environmental conditions helped chemical mixtures self-organize and evolve in structured ways, challenging the notion of chaotic early chemical evolution." (ScitechDaily, Not So Random After All: Scientists Uncover Surprising New Clues to the Origin of Life)

Requirements for life are: 

1) Chemical systems can continuously evolve without reaching equilibrium.

2) Selective chemical pathways prevent uncontrolled complexity.

3) Different molecular species exhibit synchronized population dynamics.

(ScitechDaily, Not So Random After All: Scientists Uncover Surprising New Clues to the Origin of Life)

Life is a complex thing. There are lifeforms on Earth that use volcanic temperature as an energy source. The tree and human might look far different than we might believe. Both of those things live on the same planet. They both have cells with mitochondria and DNA. But that is the only thing that combines those creatures. When we look at things like fishes they also live on the same planet as we do. 

But for those creatures air is poison. They die on dry lands. And for a creature that uses volcanic temperature as its energy source comes sunlight, which can kill it. Same way in caves live organisms without pigment. Those organisms die in the straight sunlight. That means. There are species. 

That live in total darkness. They are aliens to each other. The first organisms on Earth were not different from modern organisms when we see their fossils. But those lifeforms lived on the planet. There was no free oxygen in the oceans or atmosphere. Then plankton organisms release oxygen to oceans and that caused the first extinction. 

The reason for the first two mass extinctions was the conditions where lots of oxygen was released into oceans. That raised the mass of creatures that didn't form or release oxygen. Then the number of oxygen releasers decreased and that thing decreased the oxygen level in the oceans. Then the carbon dioxide is released into the air. Rising temperatures decrease the oxygen level in oceans. Changes in conditions caused the extinctions that forced some species out from water to dry lands. 

The Late Ordovician extinction can happen when there is too much oxygen in the water. Or when the climate turned colder the ocean pulled lots of oxygen in the cold water. Then the climate turned warm again and that released oxygen from the water. That caused a situation where oxygen turned high and low. But there are many theories about that first extinction. 

In the second case, the  Late Devonian extinction was similar to the Ordovician. The animals disappear from oceans for some reason. That made the perfect conditions for plankton growing. Maybe there formed lots of plankton that caused the explosive growth of species like sharks and other sea creatures. Then something destroyed plankton. The reason for that can be some kind of cloud that disturbed their photosynthesis. 

That turned those oxygen producers the users of oxygen. That caused the extinction of the species that ate plankton. Then that extinction continued to higher animals like sharks. And when those creatures fell to the bottom of the ocean they released lots of carbon dioxide into the ocean and atmosphere. That raises the temperature on Earth and weakens the ocean's ability to connect gasses to water. 

https://scitechdaily.com/could-alien-life-thrive-on-planets-orbiting-dead-stars-new-study-suggests-yes/

https://scitechdaily.com/are-we-alone-scientists-uncover-evidence-that-intelligence-may-be-inevitable/

https://scitechdaily.com/not-so-random-after-all-scientists-uncover-surprising-new-clues-to-the-origin-of-life/

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

https://en.wikipedia.org/wiki/Van_Maanen_2

The aliens are back to the surface.

Rather than random luck, Earth’s environment dictated when complex life could emerge. This new model suggests that other planets may also follow a similar path, making intelligent life far more likely in the universe. Credit: SciTechDaily.com. (ScitechDaily, Are We Alone? Scientists Uncover Evidence That Intelligence May Be Inevitable)

The new models make researchers think that maybe intelligence is inevitable. So that means: if on some planet there are lifeforms. Can exist long time enough, the creatures that live on that planet turn intelligent. But then we face the induction question: how large-scale model that thing can be? Can things like galaxy-scale structures and even the entire universe turn intelligent? 

The intelligence can be the series of the search-and-response circuits. That means it's theoretically possible that things like black holes can turn intelligent. That means the black hole pairs can take the superposition with each other. And those superpositioned and entangled black holes can turn into the quantum neural network. Intelligent black holes, intelligent nebulas, or some other non-organic intelligence can be rather quantum computers than lifeforms as we know lifeforms. 

But the thing is that intelligence doesn't require organic structures. And organic creatures can be intelligent without neurons. Those creatures can formed of proteins that have search-and-response circuits or sense-and-response circuits. In this text, those things mean the same things. 

The search-and-response ability is the thing that the slime mould uses in its nutrient search. The ability means that slime mould can follow chemical traces that its nutrient leaves. And that means search-and-response ability is the collection of sense-and-response abilities. The sense-and-response protein feels the nutrient. And then it starts to follow the trace. And when that trace's signal rises high enough that activates another sense-and-response circuit that starts to produce enzymes.  

So, is intelligence only a series of sense-and-response circuits? 

"Simulation of a vast region of the Universe based on the current cosmological model and performed using supercomputers. In the image, the faint glow of the gas within the cosmic filaments, forming a dense cosmic web, is shown in white. At the intersections of these filaments, the gas within galaxies, which fuels the formation of new stars, is highlighted in red. Credit: Alejandro Benitez-Llambay/Universität Mailand-Bicocca/MPA" (ScitechDaily, First Direct Image of the Cosmic Web Reveals the Universe’s Hidden Highways)

The cosmic web looks like slime mould. And it's possible. That it can have the sense-and-response" circuit. 

"A biological model based on slime mold has provided astronomers with new insights into the structure and evolution of the universe. (Artist’s concept.) Credit: SciTechDaily.com" (ScitechDaily, Slime Mold Algorithms Unlock Secrets of Vast Cosmic Structures)

"Intelligent aliens, if they exist in the galaxy or the Universe, might be detectable from a variety of signals: electromagnetic, from planet modification, or because they're spacefaring. But we haven't found any evidence for an inhabited alien planet so far. It's also possible that aliens have traveled here and are watching us, and are responsible for some UAP/UFO sightings. If so, however, they can't be made of dark matter or dark energy: a fact we can conclude from already-existing observations." (BigThink, Ask Ethan: Could there be dark matter aliens out there?)

There are many interesting theories and models of alien life. So the question "Are we alone"? Is an infinite topic in scientific and philosophical discussions again. The question "Are we alone in the universe" stays until we get an answer. So we are alone until we get a response. That is one thing that we can use as the fundamental determination for the answer. But then we must realize another thing. Even if we get an alien message or even their technology, are we still alone? 

It's possible. That aliens are not interested in talking with us. So they turn their back on us. Another thing is that there is a possibility that aliens have a similar protocol to operate with sub-Kardachev scale civilizations that we use when we meet primitive tribes. But every model that we have is a guess, a hypothesis. 

And then what is alien? Or what is the extraterrestrial intelligence? The alien is an intelligent structure that can interact with its environment and affect it as it will. Another thing is that we can affect our environment, build houses, and make space stations. But we cannot control things like the sun and neutron stars. The another thing is that we have theoretical models how to control those things. 

We have theoretical models of how to control our genomes and how to make some kind of immortality. The last one requires the ability to change the mitochondria and the cell's nucleus genomes. The system removes the damaged genomes and then replaces them with the fresh DNA. That is one view of genetic engineering. 

If we think about things like dark matter aliens we can first say that this kind of model is unbelievable. But then we can compile that thing with the intelligent universe theory. The dark matter can form at least nebula-type structures. That means the dark matter or the universe network can form the search-and-response structures. The model for that thing is the slime mould, a creature that has intelligence without any neurons. That means some proteins might have the sense-and-response and search-and-response ability. 

That means the intelligent alien might be the protein structure that has the search-and-response circuits in their proteins. That kind of alien creatures can turn their bodies into slime-mould-type structures and slip through the smallest holes. So that kind of creature can be like some kind of vampire that can put its body into bites. And then rebuild it again. 

https://bigthink.com/starts-with-a-bang/dark-matter-aliens/

 https://scitechdaily.com/are-we-alone-scientists-uncover-evidence-that-intelligence-may-be-inevitable/

https://scitechdaily.com/first-direct-image-of-the-cosmic-web-reveals-the-universes-hidden-highways/

https://scitechdaily.com/slime-mold-algorithms-unlock-secrets-of-vast-cosmic-structures/

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

The AI can reach consciousness faster than we think.

French philosopher René Descartes once said: "Cogito Ergo Sum", I think therefore I am. That means that the AI that thinks realizes its existence and reaches consciousness. The AI doesn't think. It just collects data from different sources like sensors and memories. This is the thing. That we call the difference between humans and  AI. 

But then we can ask how the AI way of collecting and handling data differs from the human process that we call thinking. 

The human can think abstractions. But in the same way, AI can put focus into the operations. 

Then the AI can make the simulations about the requirements. That the system needs to complete the mission. 

The Guardian magazine describes artificial intelligence as computer systems that perform tasks that usually require human intelligence. Then we can say that no human can do everything in this world. So, when we think that the AI learns things by connecting new modules to it. 

That means the AI learns and applies new things faster than humans. The main question is this: can the AI generate new modules for it? If it can make that t thing, it becomes more intelligent than humans. 

AI is the thing of this year. And it will be a bigger thing. In the next year. But can the AI reach consciousness? That causes discussions. The development of computer hardware is faster than nobody expected and new and faster microchips can cause surprises. But if we want to make a neural computer that emulates human brains and operates large language models we can have the technology that makes it possible to create computers that are more intelligent than we are. 

The speed of data in the human brain is 10 bits per second. The thing. What makes brains so effective is that There are 85 billion neurons. And the network of brains can share information with many routes and neurons. 

Then neurons can connect data in its entirety. Using neurons and their routes. Each neuron handles a small part of the entirety. That the neurons connect like a puzzle. 

If people want to make an AI. That is more intelligent than humans. Researchers must just make a computer. That uses many slower microchips. Rather than a few faster chips. Theoretically, researchers require 85 billion microchips that are networked into one entirety for making artificial brains. 

The artificial brain will consist of three system layers or three hierarchical systems. Those three systems simulate the cerebral cortex, diencephalon, and cerebellum. That system can be on 2D microchip circuits. That means those artificial brains can look far different than our brains. The ability to share data over the network makes them effective. 

When we operate with ultra-advanced artificial intelligence we forget one thing. Those creatures are not physical. They are just only the electric impulses. That means the AI can slip out from its server. Or it can write itself over the net into multiple computers if it has access to all other computers for help and make backup copies of itself. 

The AI can copy itself to multiple computers into the network. The AI can connect itself to the entirety like a puzzle. That thing means that even if the AI is in the different computers in a deep network the AI can connect itself in its entirety. And if the AI can connect new modules to it, it can cause surprises. 

But if the AI turns conscious. It turns more intelligent than humans. It's possible that the AI can tell lies and protect itself. 

So, if AI reaches consciousness that means. It turns into an intelligent creature that acts like a living organism. And all conscious and intelligent creatures defend themselves. That means the thing that. The AI is another intelligent creature. 

https://interestingengineering.com/science/speed-of-human-thought-brain

Where is the AI going? And where is it taking us?

The AI is advancing very fast. And sometimes we must ask, who controls whom? Do the engineers control the development of the AI? Or does the AI control the engineers who develop it? The race of the AI is the visible thing. That means the AI development is very fast. And the thing is that.

The requirement is that the AI must always get new features that turn it better and better. Or is it better? It can make more things and that is a description for better AI. But even if the AI is wider and it can make more things, we must ask does the AI make those things better? But the AI is far away from the thing, That we call the artificial general intelligence, AGI. 

The problem with AI advancement is that. The focus is on the calculation capacity. Increasing that capacity makes it possible to run more and more complex algorithms. The iron or physical systems are important. However, the main problem is that AI requires more than just calculation capacity. The AI requires the ability to collect, analyze, and reorder information into the form. That people can trust it. 

The problem is that even the deepest learning systems can make many things. But they do not know what they really do. The action that the AI makes is quite easy to explain. When we order the AI to raise its limb the system can make animation when there character raises its limb. Or it can make contact with the robot and the robot raises its limb. 

During that process, the AI must recognize the order. Then the system must search if is there a match for those words in actions that targeted the physical system. If there is a match, the AI activates the physical action. If the system must calculate something it can ask if should it write all stages in the calculation or if the answer is enough the AI can say it to the user. In those cases, there is the router that selects does the order requires a physical system or if the screen is enough to introduce the solution. 

There is nothing mysterious. The AI works like its creators, programmers are ordered. But the fact is that. The AI will not know what it really does. It means that when we say to the robot, that it must raise its right hand. The robot or its computer selects the components that operate the right arm, and then the robot can raise that limb. 

The fact is that if we misconnect those microchips the robot can raise its left leg. That is the key to AI. The AI can make many impressive things. But it just follows the algorithms that determine, how it must react to something. The activator can be the thing that the robot sees or hears. Then the activator launches a trigger that activates the action. The action can be physical or virtual. 

But then we must realize one thing. We can make robots that say "ouch" when we step on their feet. They can say that we use bad language. Or they can even cry if they have the right systems. In those cases, the non-polite action activates a trigger that makes the robot look sad. But the fact is that robots don't have feelings at all. They might react and look like humans. But they still are robots. They react to our voices and our words. But they are not intelligent. 

We could take those actions by using tape recorders and things like volume meters. If we step on those robots' feet, that activates the button that activates the tape, there is the word "ouch". If we yell too loudly the volume meter activates the tape that says, "Don't yell". That means those systems are not more intelligent than tape recorders. They seem very highly intelligent but they are not that. They just act as the button or trigger and the action that is connected to the trigger ordered. 

When the AI makes the diagnosis by using X-ray images the system just compares differences in the X-ray images. The system acts similar way as the fingerprint comparing systems. The system can use multiple X-ray images and search for things that are changed from those images. The thing is the fingerprint recognition systems are helpless if they have no fingerprints that they can compare. 

Same way when AI tries to detect stolen social media accounts it searches for differences in the ways how the user uses media and texts. The idea is that it's possible. That many people use those trolling accounts. And all of those people have different things that they like and hate. Differences in the texts and publications tell that it's possible. That there is more than one user in that account. 

In social media, we might not even know people who publish things there. We might not know their faces or their identity. But also those avatars have identities. People behind those images and maybe fake identities might have certain types of music genres that they like and follow. We might follow the avatar or fake identity because the person publishes things that we like. 

And if those publishings suddenly change the person who is behind that identity might be changed. Things like musical opinions do not change in one night. And people don't turn adult in half a day. Too sudden changes are telling that something is happening on the other side of the publishing. 

The small things turn into the big things if a person who we have known for years suddenly changes some core elements in their publishings. The fact is that we don't know who people are on social media. But we know what those people like to publish and what they dislike. We might not know people's names or their faces. But we know what kind of arguments they use, what kind of music opinions they have and we know their taste in entertainment. 

The biological microprocessors

"The Underground Network Fungi grow by releasing spores, which can germinate and form long, spidery threads underground (a mycelium). We typically only see the tiny mushrooms on the surface without realizing that there’s a vast network of interconnected mycelium beneath our feet. It is through this network that information can be shared, somewhat like neural connections in the brain." (ScitechDaily, No Brains, No Problem: The Surprising Intelligence of Fungi)

Fungi are the most impressive species in the world. Those versatile creatures bring a new state to intelligence research and machine-based artificial intelligence. That is suitable for robots as well as larger computers. Fungi can learn and remember things without a single neuron. That is what makes them interesting because those proteins and enzyme-based chemical brains can used to control nanomachines. 

The ability to learn things and make decisions are things that are connected to neurons. Fungi make those things without neurons. And that is the thing that makes them interesting. The ability to communicate through the mycelium network makes fungi an interesting thing to understand neuro-evolution. That makes it possible to create biological microchips that don't all the time require nutrients. 

"A study has revealed that fungi can exhibit intelligent behaviors like decision-making and learning, without having a brain. Credit: ©Yu Fukasawa et al." (ScitechDaily, No Brains, No Problem: The Surprising Intelligence of Fungi)

"Fungal mycelial networks connecting wood blocks arranged in circle (left) and cross (right) shapes. Credit: ©Yu Fukasawa et al." (ScitechDaily, No Brains, No Problem: The Surprising Intelligence of Fungi)

Researchers made experiments with neurons that communicate with microchips. Those tests were successful, but the problem is how to feed those neurons. If the fungi's intelligence is based on the enzyme-protein interactions that get their power from mitochondria. That would make it possible to make a so-called "dry protein processor".

In that case, those proteins and enzymes are in non-organic jelly. And if those reactions are electrically controlled nano-size wires can control them. In a dry protein processor, the proteins and enzymes that make fungi "intelligent" fibers are separated from the cells, and transferred to artificial jelly where they interact with each other. Those things don't need nutrients. But living fungi cells can be used for that mission. 

That thing also makes it possible to create systems that can be used to program neurons. It's possible that fungi are one thing that can used for biological AI-processors. When we think about fungi and their interesting abilities to handle things, we must realize that the same process can offer the possibility to create something that we don't even imagine. 

Fungi and their special ability to remember and learn things cause situations in which we should re-estimate our way of thinking about intelligence. The fungi can make intelligent things without neurons, and that means that maybe somewhere live organisms that don't have neurons at all. 

When we think about things, like the Search for Extraterrestrial Intelligence, SETI program the intelligent creature is determined to be a creature that has neurons. The ability to learn and make decisions without neurons is expected to be impossible. But fungi's ability to make decisions and learn things makes it possible to adjust that model. This thing makes those creatures more interesting than we expected. 

https://scitechdaily.com/no-brains-no-problem-the-surprising-intelligence-of-fungi/