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 next step is the Chinese robot army.

One of China's priorities in AI is to create a robot army with advanced AI control. The difference between Western nations and China is that the military and security needs are always over the law. There are no rules or limits on how those authorities can collect personal information. 

The Chinese military plans to make an autonomous robot army. Those robots can use even Kung Fu. All robots do not look like humans. Robot dogs can be very versatile systems. Those systems can cooperate with drones that can carry them to roofs and other places where they can make unexpected things. In that case, those robots can operate as teams with quadcopters. 

The robot army is the next logical step in robot and AI development. SciFi writer Isaac Asimov introduced that horrible vision in his novel "The Naked Sun". In that novel, the fictional planet called "Solaria" created the robot mass-army. 

That vision is coming into reality. The AI or large language model, LLM, is a tool that can be used to command any robot in the world. The only thing that the robot requires is an Internet connection. The house-keeping robots like robot hovers are excellent tools for house-keeping. But the question is always: what else does the system make than just clean houses? 

The robot can transmit every single word that person says to the surveillance room. The LLM operates through the modified speech-to-text and text-to-speech applications. The system can select and link certain words to the third party. That party can be the security police. So you can ask yourself why Chinese authorities support a marketing policy, that every single Chinese must get their own tablet computer and own little robot at home. 

The humanoid robots or man-shaped robots are the Swiss army knives for people. Those robots can use any tool and weapon that humans use. The humanoid robots can operate in dangerous places like highly polluted areas. Those robots can operate as housekeepers and they can visit to shop for people. But those robots can also operate as fighter pilots. 

They can connect themselves to the aircraft's communication- and computing units. The humanoid robot can communicate with other systems like drones, satellite surveillance cameras, and even mobile telephones. The humanoid robot can operate as a bodyguard. The difference between people and robots is that robot's skills are computer programs. And robot's mass memories are not like human memory. The operator can erase mission recordings after the robot does its job. 

The robot with an image sensor can recognize any target from the streets. So when a robot recognizes the "enemy" it just can attack the target. And the biggest difference between humans and robots is this: robots have no conscience. That means the robot always does its mission. So, the bodyguard robot can also have a mission to deny things like leaps to the opposite side. So, if high-ranking people talk about prohibited things those robots can arrest them. 

The robot can have a so-called ghost protocol. That means that if the person who owns a robot acts against the state, that thing like wrong words activates that attack mode. Another risk is this: if the robot comes from a country that goes to war with the country where it's shipped the seller can simply download an attack program to the robot. The humanoid robot can look like a dummy or lay figure. When the operational order comes those dummies can jump through windows and march to the gun store. And that is one of the darkest visions in robotics. 

https://www.defenseone.com/technology/2025/04/chinas-military-aims-harness-coming-chatgpt-robotics/404811/

https://www.msn.com/en-ca/news/world/us-report-reveals-china-s-plans-to-develop-an-army-of-robot-soldiers-with-advanced-ai/ar-AA1DyCku?ocid=BingNewsSerp

https://www.newsweek.com/china-killer-robots-unitree-robotics-191756

The Chinese new humanoid robot is impressive.

"Iron is designed to perform complex tasks in smart factories and retail environments." (Interesting Engineering, Iron: China’s humanoid robot gets supercomputer-like brainpower, eagle-eye vision)

The Chinese new humanoid robot is impressive. It has supercomputer brain power and eagle-eye vision. This kind of robot can operate in many roles at home.  The robot can also operate for companies. And the government. 

The humanoid robots can act as cleaners, painters, and personal assistants. There is the possibility that the observers can use those systems as intelligence and surveillance tools. 

The robot shares its sensory data with supercomputers over the networks. That allows the government or private eye to use that robot to read papers. And listen to discussions or act otherwise as a spy.

(https://interestingengineering.com/innovation/china-humanoid-robot-brainpower-eagle-eye-vision?group=test_b)

We should realize this wisdom. It is more important to think of things that manufacturers or salesmen didn't tell than things that they told. 

If the marketing text says that the robot is suitable for cleaning and other things, we must realize that this thing limits only regular, private users. The government plays in different ways. In China, the government might want to use those systems for espionage and recon missions. 

The fact is this. The humanoid robot can make everything that humans can. The robot can have the microphone in its hands. So it can hear discussions through the wall. The system must put its hand on the wall. Then it can eavesdrop on people on opposite sides. The eagle-eye vision means that the operator can use VR systems with the robot. Those systems make the operator see and hear the same thing. What robot sees and hears. Those robots can act in man

The humanoid robots are excellent tools for work as soldiers and assassination missions. The humanoid robot can have similar target recognition software to the Javelin missile. When the robot sees a target it can activate its shadow protocol. Then it can make the mission. And after that, the robot can clean its memories. 

https://interestingengineering.com/innovation/china-humanoid-robot-brainpower-eagle-eye-vision

The bias in AI is a big problem.

The AI's problem is that it doesn't think. That is the thing that we usually repeat and repeat. That ability to get data without analyzing it causes bias. The thing that makes that model possible is that the AI doesn't know what the homepage involves. 

It sees words and their connections to something, but then the system doesn't realize what those words really mean. The AI, or large language model, LLM is programmed to give answers in a certain time. That means the LLM doesn't compare and search connections to every single word in the document. That saves time, but it decreases the data's trustworthiness. 

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The study put ChatGPT through 18 different bias tests. The results?

AI falls into human decision traps – ChatGPT showed biases like overconfidence or ambiguity aversion, and conjunction fallacy (aka as the “Linda problem”), in nearly half the tests.

AI is great at math, but struggles with judgment calls – It excels at logical and probability-based problems but stumbles when decisions require subjective reasoning.

Bias isn’t going away – Although the newer GPT-4 model is more analytically accurate than its predecessor, it sometimes displayed stronger biases in judgment-based tasks.

The study found that ChatGPT tends to:

Play it safe – AI avoids risk, even when riskier choices might yield better results.

Overestimate itself – ChatGPT assumes it’s more accurate than it really is.

Seek confirmation – AI favors information that supports existing assumptions, rather than challenging them.

Avoid ambiguity – AI prefers alternatives with more certain information and less ambiguity.

(ScitechDaily, More Like Us Than We Realize: ChatGPT Gets Caught Thinking Like a Human)

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The fact is that at least part of the results that the AI gets from the net are based on the search engine's page ranks. When we think like this: we teach AI we should give feedback on its results. 

If we tell that the AI gives bad answers that helps it to adjust the results that it uses. The problem is always that for giving trustworthy feedback to the AI we should sometimes be experts. Of the thing that we asked. 

The big problem with AI and other copilots is that those things are made for customers. The product must also please the user in some way. And that can cause the bias. When somebody writes about AI, that person should compare it with other LLMs. The most advanced AI "thinks" that it's the best of all. The algorithms tell it how impressive it is. The more advanced AI means that it's better than other AI's. 

When we think about AI and its operators and owners in the world we must realize that all those companies that develop AI are independent companies. That means those AIs don't have access to the competitor's statistics. So, those AIs are not under one dome. And if they should compare themselves with other AIs like "What is the best AI in the world"? 

Those systems cannot get trusted data. Like how many percent of their answers satisfy the users. That kind of data is not collected. The AI will not ask would the user like its answers or if are they good. Another thing is that if the regular user is not the same as some doctoral user. The AI requires specific commands that involve the right terminology. Without the right terminology, the AI is helpless. 

And then AIs cannot compare those percents with other AI's statistics. This makes the AI think. That it's better than it is. The AI can use Wikipedia. When it should use specific sources like CERN homepages. The AI requires that the person who uses it knows the terminology, and then the misuse of some term in the wrong place in a query can turn the AI's text into a grab. AI will not make a difference in the words "hall" and "hall effect". That thing can cause a situation in which the AI starts to talk about echoes or some aircraft hangars when it should start to talk about resistance in electric wires. 

 https://scitechdaily.com/more-like-us-than-we-realize-chatgpt-gets-caught-thinking-like-a-human/

New microrobots are game-changing.

The new biomimetic robots are awesome tools. They can deliver medicines precisely into the wanted cells. Or they can cut the targeted cells into pieces. The problem with those robot's medical use is in their control system. The medical robot must select the targets with a very high accuracy. 

The small-size robots can look like liquid mass. But that mass includes billions of independently operating robots that can carry miniaturized microchips. Those microchips create the network in that mass. Another way is to create artificial bacteria that uses artificial DNA as the program that allows it to find the right cells. 

The system can use the DNA bites that make the immune cells find harmful cells and then those DNA bites can also injected into the basils that can help those immune cells. Those hybrid organisms must have a self-destruction trigger in the DNA that orders them to die. Those genetically engineered cells can also produce medicals in the human body. 

Miniature robots can also carry things like cloned cells. Into the right points. The system can change the DNA in those cells. That transforms their nature immediately. 

New microrobots with liquid structures are tools that can revolutionize medical technology. Those robots can travel into the targeted cells or close blood vessels that transport nutrients to tumors, denying them the ability to receive nutrients. The liquid robots can also close poisonous molecules inside them and remove those poisons from their bodies. However, liquid robots can also operate in many other places. 

Those robots can also close leaks in the tubes. And they can clean organic and non-organic structures. Those robots' flexibility allows them to transport microchips into the right places. 

So they can also act as spying tools. They can cover some areas. And when something puts pressure on those microchips. They can send information to the support station. That kind of technology those microchips form the morphing neural network. 

Can give those robots a very high-power computing power. In the wrong hands, those liquid robots are the most dangerous tools in the world. They can slip into the targeted person's body and close blood vessels. 

"Animation of how the micro swimmer is coated with magnetic nanoparticles and how it swims in water and viscous liquids. Credit: MPI-IS" (ScitechDaily, Scientists Create Microscopic Algae Robots With Incredible Swimming Abilities)

The new algae robots are also incredible tools. They can be microchip or DNA-controlled. The system can also have hybrid control. There the microchip turns the DNA plasmids into the right position. The ability to create synthetic DNA makes those robots very effective. They can find certain cells and transport medicines to those cells. 

Magnetic microalgae have the ability to operate in the human body. Those systems are hybrid things that contain non-organic and organic materials. The hybrid biomimetic robot that connects miniature submarines and living organisms can be a new tool for destroying non-wanted cells The human nervous system can communicate with those biomimetic robots.

Those systems can also have microchips that take commands from the outside systems. The magnetic structure in those robots can act as an array.  Those algae robots can also have the ability to produce electricity themselves if those cells have the genome that makes them create electricity. Those systems require electricity in their microchips. 

 https://interestingengineering.com/innovation/cell-inspired-liquid-robots-south-korea

https://scitechdaily.com/scientists-create-microscopic-algae-robots-with-incredible-swimming-abilities/

Small robots can act as robot puzzles.

"A new ultra-light swimming robot mimics marine flatworms, using silent undulating fins for precise movement in tight aquatic spaces. It could revolutionize environmental monitoring and precision agriculture. Credit: EPFL-LMTS" (ScitechDaily, Scientists Develop Tiny 6-Gram Robot That Swims Through Tight Spaces With Ease)

The small robots can act as individual tools. But, they can also act as the bites in puzzles. Engineers made a six-gram robot. That can research its environment. Or a swarm of those small robots can cover large areas. The swarm of small robots can use non-centralized cloud-based neural networks. The robot can operate in water. But if it's the quadcopter shape that thing can also fly. 

In some models, the lasers or high-power radio waves can transport energy to those systems. The laser beam can transfer energy to the small photovoltaic cells. The small plutonium batteries or the cells from electric eels can create energy for those systems. 

The small robots can operate in their entirety. Each robot can have different sensors like laser spectrometers, microphones, seismic sensors, or cameras. The robot group can operate in small water areas or they can fly, if they are small quadcopters. They can search for pollution, and toxic chemicals, hear bird sounds, and go to dangerous places. 

In the military world, they can search and eavesdrop on enemy installations. The small-size robots can also make it possible to create new types of nuclear bombs. That is the robot swarm. In that robot swarms robots carry small neptunium or plutonium bites. And then they can go together forming a critical mass. 

"An artist’s depiction of a material-like collective of robots forming a rigid device. Credit: Brian Long, University of California Santa Barbara, edited" (ScitechDaily, Scientists Just Created Shape-Shifting Robots That Flow Like Liquid and Harden Like Steel)

(ScitechDaily, Scientists Just Created Shape-Shifting Robots That Flow Like Liquid and Harden Like Steel)

The robot amoeba is a group of very small robots. It can make even the T-1000 from Terminator movies possible. 

The shape-shifting robots can turn as hard as steel. And then they can take liquid form. Amoeba robot groups are fundamental devices that can make self-repairing structures and even make liquid, shape-chancing robots possible. That means those robots can transported to the operational area using the tanks. 

Or they can travel through tubes. The idea of liquid robots is simple. Those systems are like robot swarms. But they can form an amoebae-shaped structure. Small robots can use neural-network-based computing algorithms. 

Then, they can take any form as the programmer wants. And that can be a breakthrough in material development. Those robots can hide in the tanks in submarines, aircraft, or in spacecraft. Amoeba- robots can travel to the damaged point and repair damages.  And maybe in the future, those robot groups can make it possible to create structures that change their shape. 

When aircraft travel faster, or some car or other vehicle requires a new role liquid robots can take another shape. They can also transform into other tools. So, the robot amoeba can also take the shape of a screwdriver or spanner. The robot amoeba that takes the shape of everything that it touches can be closer than ever before. The ability to read the DNA makes it possible to take the shape of any person. 

https://scitechdaily.com/scientists-develop-tiny-6-gram-robot-that-swims-through-tight-spaces-with-ease/

https://scitechdaily.com/scientists-just-created-shape-shifting-robots-that-flow-like-liquid-and-harden-like-steel/

What is the deep-learning?

The chatbot software faces the ultimate limitations. One of those limitations is the limits of information and knowledge. We don't know many things that we think we know. We just guess those things and that is one of the most fundamental limitations that the large language model, LLM faces. The guess is another way to say that we have a theory about something. 

Another thing is that we have problems making deep-learning algorithms and deep-learning morphing networks. The problem is this: how to determine "deep learning". When we use some technical equipment we don't need to know what happens when we use that thing. The only needed things are the knowledge what happens when we push some control buttons. 

We can visit shops without knowledge of things like how barcodes and radio-frequency IDs called RFID work. They must only scan those bar codes and pay the bill. 

We can drive a car without any knowledge other than where we put the engine on, and then we must put the gear in the "D" position and then push the pedal. Or we can give orders where to drive to autopilot. We must know how to break. 

And that's it. Other things like washing windows etc. are also important. But we must not have any deep knowledge of what, really happens when we push the hammer. We must know that the car accelerates and slows its speed. We don't need to know the physics behind the engines or we don't need to know how the computer gets data for our screens. 

When somebody uses computers and LLMs they don't need information on how that kind of system learns things. When the LLM or AI accelerates an electric car it just thinks that it must increase the power input to the electric engines. When another sensor sees the value that is the speed limit, the AI will stop the acceleration when the system sees that the vehicle's speed is close to the target speed.  That is one version of the sense-and-response circuit. The AI handles everything by searching values and then it reacts when some values match. 

The camera or some other sensor like GPS can see the traffic signs. When it sees things like a "slow" sign that thing activates the program that can read the text and then that algorithm searches for matches from databases. There is a database that is marked as "slow" and then the system knows what it must do. 

Things like speed limits can also be in traffic maps and the GPS can locate the car. The robot car is one of the systems that can learn things. It can calculate time and other things like routes that a certain route takes. The system can select routes that are fastest and most economical. But the thing is the robot car must know anything that it can travel those routes. 

Deep learning means that the system, really knows what things like robot cars mean. The fact is that. The robot car can answer questions like "What are you" by saying that it's a robot. Then it can tell that it's an autonomous ground vehicle. But the other question is this: does the LLM understand what those things mean? The LLM can search homepages where there is text about autonomous vehicles and connect them. But also 10 years a child can make that thing. 

https://www.quantamagazine.org/chatbot-software-begins-to-face-fundamental-limitations-20250131/

The ant-shaped robots are moving large stones.

Robots are multipurpose tools. And even small robots can move large objects if they act as groups. Ant-shaped miniature robots are excellent tools for many purposes. They can take samples from ant nests and search for things like fungus between walls. The miniature robots can make chains and deliver information from cramped places. 

They can observe cables and search for damages from tubes and electric wires. The use of those robots is almost unlimited. They can act in medical operations where they can operate as miniature surgical tools. The jaws of those robots can act as surgeon knives. The miniature robots can carry miniature sensors that can search for many things. The cloud-based calculation systems are tools that can make miniature robots operate independently. 

The non-centralized data architecture makes it possible to turn those robot's computers into one entirety. And that turns those robots into a deep neural network where they share their calculation capacity. 

That gives those systems the ability to drive quite complex algorithms. This gives them very high independence. Maybe one part of those swarms doesn't have very high-power processors. But if they act as an entirety, those systems can be very effective.

Those robot ants can go inside houses and deliver information about the enemy headquarters. In the military world, those small robots can slip into the computer centers and then cut wires from those computers. Or they can deliver the oil spill response microbe to fuel storage. The same microbes can be used against oil damage. But in the fuel tank, those microbes destroy the fuel.  

Miniature robots can also act as testbeds for larger-size robots. Large robots can also operate in swarms. That makes the robot swarm technology suitable for large systems. The car or lorry-size robots can also operate as an entirety. 

The new robots can act as legos. They can form larger structures that can remove themselves. The self-assembly materials make it possible to create self-assembly and self-repairing surfaces and structures. In those structures, the material is formed of the separated robots that can touch each other. 

https://scitechdaily.com/watch-ant-like-robot-swarms-lift-heavy-objects-with-herculean-strength/

The new components make AI more multifunctional than ever before.

 

"The robots can adapt to different work tasks and production line layouts." (Interesting Engineering, China’s humanoid robot army turns factory into precision-packed powerhouse)

The new AI tool transforms geographic information systems, GIS into 3D maps and other things. The system can make many things. From game areas to the traffic and even city-scale simulations. The ability to make 3D maps and spaces makes it possible to make the operational areas for the robots that operate in the area. 

The AI that can make spaces by following spoken words can make it possible to create images for police. The AI-based robot drawer can revolutionize art and criminal investigations. The thing is that we must not expect too much from the AI. The CEO murder in NYC is an example of the limits of AI in face recognition. 

If the face recognition uses only visual images without IR systems that can see through the masks. The AI is helpless. And then another thing is that the person who doesn't do anything suspicious before the shooting is not marked for the system. That means the system will not follow the person who is not marked for it. 

Police say that the shooter used a 3D-printed pistol. That means that there is the possibility that the person has no official handguns. And that makes this case very hard to solve using traditional police methods. The problem is that anybody can own a 3D printer. It's impossible to track the 3D-printed pistol. 

But the AI is a tool. That can make many things. That is impossible for humans. 

The system that controls the robots in the area can learn things in seconds. The system can download the 3D maps to the robot group. And the AI can control things like sensor fusion. The robot group can connect their sensors into one entirety. And that makes them an ultimate tool for civil and military purposes. Another thing is that the robot is the tool. It cannot make anything dangerous if the operators don't order it to make those things.

The humanoid robots that operate in the Chinese warehouse can be tools that can turn into firemen or soldiers. The limit of those robots is their power sources. The robots that operate as an entirety can also interconnect their operational instructions like operation maps. When one robot learns the drawings of the buildings it can scale that information through the entire group. The humanoid robots can turn any ship or aircraft into a robot vehicle. 

And when we think about the policy of China, we must realize that Chinese people understand those robots' military value. The robots are tools that don't excuse their orders. That makes them dangerous. The person who controls robots must realize how dangerous they can be.  But as we know the same systems that can save lives can operate in a war zone. There are weapons. Like EMP impulses that affect only robots. There is the possibility of denying the robot's information exchange. But things. Like laser communication can avoid the ECM systems.

https://interestingengineering.com/innovation/ai-tech-builds-3d-maps

https://interestingengineering.com/innovation/magiclab-robot-army-in-factory

https://futurism.com/the-byte/ai-fail-uhc-killer-luigi-mangione

 

https://futurism.com/the-byte/ceo-killer-suspect-3d-printed-pistol

Machine learning and nanotechnology.

"In-situ liquid-cell transmission electron microscopy electrodeposition of PtNi nanoparticle films on a carbon electrode during cyclic voltammetry. The electron beam (here in green color) illuminated the electrode (here in orange color) submerged in the platinum and nickel salt solution, enhancing the growth of the PtNi nanoparticle film (grey color) on the electrode. The film thickness increases with each cycle and by the fourth cycle reaction-rate limited growth of branched and porous structures were observed. Credit: Weronika Wojtowicz, water background from freepik" (ScitechDaily, Inside the Nano Factory: Real-Time Insights Into Nanostructure Creation)

Machine learning makes it possible to predict the structures of materials. And that makes it possible to create more effective tools for nanotechnology. Nanotechnology means that the systems can create complex synthetic chemical structures. And those structures can turn into fundamental chemistry and mechanical tools. Machine learning makes it possible to create always similar conditions. 

Then it can make very accurate mixtures of chemicals into the reaction chamber. The AI can search and model things that happen in the cells when they create the complex organic molecules those systems can create the cloned cells. Or they can create a chemical factory that emulates living cells. In some cases, the ultra-sharp systems can remove cell organelle from the cells and then activate it using nutrient injections. 

The term fundamental chemistry means. The system can manipulate and control single atoms in molecules. That allows to creation of structures with atom-sharp accuracy. The fundamental chemistry in nanotechnology makes it possible to create graphene or fullerene graphene structures. In the last one, the structure is the fullerene molecules that nanotubes connect into their entirety. That material can be very strong and lightweight. The nanosystems can make many things. Like synthetic proteins and enzymes. 

"By learning from millions of crystal descriptions, CrystaLLM predicts new material structures faster, aiding in the rapid development of technologies. Credit: SciTechDaily.com" (ScitechDaily, AI Decodes Crystal Patterns To Power Tomorrow’s Innovations)

The biomimetic systems can emulate things like slime molds. The slime mold is an organism that can learn things without neurons. And that means that the same proteins and enzymes that make slime mold to learn things can be installed into the silicone structure. The ability to follow thousands of objects at the same time. 

Make it possible to find out, what makes the slime mold learn. Another way is to use the microchips that pull and push the protein fibers. And then it can use the method to control things like liquid robots. Liquid robots are tools that can be used in medical work to clean blood vessels or close them to stop the blood leak. Those systems can also analyze things like water tubes. The liquid, but non-organic robots can also search for things like incipient fire. And then those robots can cover those flames. 

The nanotechnology is one of the biggest things in human history. The nanosystems require very precise and accurate information about the materials and their formation. The system can use the most modern microscopes for analyzing the process and the environment. Where the system creates those complicated molecular and sub-molecular structures.  

https://scitechdaily.com/ai-decodes-crystal-patterns-to-power-tomorrows-innovations/

https://scitechdaily.com/inside-the-nano-factory-real-time-insights-into-nanostructure-creation/

Drones have new missions. From Jupiter's moons to a depth of oceans.

"In the Sensing With Independent Micro-Swimmers (SWIM) concept, illustrated here, dozens of small robots would descend through the icy shell of a distant moon via a cryobot – depicted at left – to the ocean below. The project has received funding from the NASA Innovative Advanced Concepts program. Credit: NASA/JPL-Caltech" (ScitechDaily, Could NASA’s Tiny Robots Discover Life on Europa?)

The most impressive mission for drones or independently operating miniature submarines will be the search for life from Jupiter's moon Europa. The thing is that also two other large moons, Ganymede and Callisto could have similar oceans under their icy surfaces. 

And the third Galilean moon, Io has sulfur volcanoes that are also interesting geological objects. But the main object for that mission could be Europa, the icy moon with icy geysers. The probe can slip the small submarine into those geysers and maybe they can reach the ocean under that icy surface. The done can communicate with the surface unit by using sonars. 

"After completing testing, the Robotic Servicing of Geosynchronous Satellites (RSGS) payload resides in the cryogenic thermal vacuum chamber at the U.S. Naval Research Laboratory’s Naval Center for Space Technology in Washington, D.C. Oct. 8, 2024. Once on-orbit, the RSGS payload will inspect and service satellites in geosynchronous orbit. Credit: U.S. Navy photo by Sarah Peterson" (ScitechDaily, DARPA’s Robots to the Rescue: Transforming Satellite Maintenance in Space)

Large-size drone swarms can cover large areas under the icy surface. They can have only a limited number of sensors. But those drones make sensor fusion. And the drone swarm behaves like one bigger platform. This means. Those drones can carry similar sensors. As one large probe or aircraft. But the difference is that those sensors are under different independently operating bodies. And if one of those drones is gone, that doesn't make the failure to the entire mission.  

And that nuclear-powered unit will find a strange water world that is interesting even if there are no living organisms. But those small, long-lasting, independently operating drones can also have missions on Earth. The small AI-controlled drones can also operate in icy lakes under the Antarctean and Greenland icy shells. Things like closed caves and underwater water routes can also be places. That those drones can map. 

"In this illustration, a NASA space exploration concept called Probe using Radioisotopes for Icy Moons Exploration, or PRIME, is depicted being deployed from a lander on the frozen surface of an ocean world. The nuclear-powered probe, also called a cryobot, glows red in the subsurface ocean while connected via a communications tether to a lander miles above on the icy crust. Wedge-shaped, cellphone-size robots – another concept, called Sensing With Independent Micro-Swimmers, or SWIM – are seen traveling off underwater to conduct science beyond the heat of the probe. Credit: NASA/JPL-Caltech" (ScitechDaily, Could NASA’s Tiny Robots Discover Life on Europa?)

They can collect information about the closed ecosystems. That can be isolated even for thousands of years. But the same systems. That can map and research insects. Also, can collect data from other things. Drones can collect information about underwater systems like submarines. The new radar systems can follow underwater acoustic communication. The same systems can also search for information from the targeted people's discussions. 

The radars can search for things like pressure waves from air or water. And they can used to record the things that people say. Water carries sound at a very long distance. And the system that can measure the oscillation of the water surface can break the privacy of people, who are not careful. The submarine that travels in the water lines can eavesdrop on people in their houses and even the army headquarters. 

The new innovative robots can act as maintenance missions for spacecraft. They could repair the unmanned satellites and probes if they face problems. The repairing robot is the tool that can make the things like large-size, nuclear-powered drones more effective. They can be sure that the expensive system can fulfill its mission.  But similar robots can also fix other underwater drones and structures. The undersea robot can also make it possible to return unmanned systems that return from intelligence or strike missions. 

 https://interestingengineering.com/innovation/eavesdropping-underwater-messge-transmission

https://scitechdaily.com/could-nasas-tiny-robots-discover-life-on-europa/

https://scitechdaily.com/darpas-robots-to-the-rescue-transforming-satellite-maintenance-in-space/

New robots learn things by watching videos.

Do we create puppies that can serve us? 

The biggest question is this. "What does the word "we"? Do the word "we" mean regular people? Does that word mean some company leaders? Or, does that mean military high command? When we say that robots take our jobs, we forget to ask, what kind of jobs do robots take? Are they wanted jobs, well-paid jobs, or what they are? We all know that war is an inhumane thing. 

But still, we have armies. We all know that the mission of high command is to defend the country. Everybody wants to be company leaders and members of military high-commanders. But nobody wants to be a worker. Nobody wants to be private. And that is the problem. The leader sends henchmen to work and then sits on a chair in the office. And that happens in the rain or the sunshine. 

When we say that robots take the jobs of medical doctors we don't think about people who live in remote areas in places like Australia. When happens something the doctor can come there in hours. The robot that has the medical kit can recognize the injury and do the job in minutes. If it can recognize and react to the injury. The same robot can act as a gardener and surgeon and its mission depends on program modules. And that robot can also act as a military operator. 

(ScitechDaily, Robot That Watched Surgical Videos Now Operates With Human-Level Skill)

"By utilizing imitation learning, researchers have enabled a surgical robot to execute complex procedures as proficiently as human surgeons." (ScitechDaily, Robot That Watched Surgical Videos Now Operates With Human-Level Skill)

So, we cannot always do good things. We know that we must defend our countries. And robots are the ultimate tools also for those things. But when we think about robots we face things that the same robots that protect a country can also attack to other countries. 

The robot surgeon performed its operation like a human surgeon. That thing is not a very big surprise. But the very big surprise is how the machine learns those skills. That robot just watched videos. The breakthrough in machine learning is the robot that learns like humans. The thing that made this robot interesting is that it just watched videos. And then that system could make surgeons like humans. 

When we discuss the use of robots in health care those robots can leave room for social interactions between patients and nursing staff. When we think about human-shaped robots that can use videos to learn things, we face one thing. The robot can use any film to learn things. And in some ideas, the military robots can use things like action movies to learn new skills. The human-shaped robot can act as a cleaner, but the same system can act as a robot warrior. This means when we want to create puppies, we can create one of the biggest threats in the world. 

That kind of technology can be a new tool for robot science, which is one of the fastest-advancing technologies in the world. Learning machines can learn things faster than any human can do. Another thing that we must realize is that computers can scale their skills to all systems, that are connected to the network. That means that if one robot looks at the film and copies those skills into itself, it can transfer those skills to all similar robots in the network. And that is the biggest thing in AI-based technology. 

...or, do we create Frankenstein? 

The learning machine that learns from videos can be the revolution in technology in all its sectors from everyday warehouse workers to military drones and robots. The human-shaped robot that can learn like a human is the tool, that can change the world forever. We can say that this kind of system is the modern Frankenstein. If we want to use those robots as weapons it's our business. 

Of course, we can use them for more productive things than killing other people. We can use learning robots for making moon stations, we can use them to close damaged nuclear reactors. We could turn our gardener robots into surgeons that could save our lives in remote areas. But then everything that we want to see is negative things. Otherwise, we see what happens when some other nation attacks on us. The problem is that everybody wants to be generals in the army. Nobody wants to be in a pothole at the front. Robots are one answer to that problem. 

Even if robots cannot make surgical operations they can work as cleaners, warehouse workers, and soldiers. The man-shaped robots can turn all aircraft into drones. The same robots can also operate as infantrymen. And that is the most advanced, promising, and frightening scenario in the world. Learning drones can beat man in air combat. The fact is that the same robots that go to radioactive places and maybe operate for years in the deep sea and outer planets can be the biggest opportunity and threat for humans. 

The learning robots can be the things that travel to Mars and Jupiter a long time before humans. The thing that people must realize when researchers make new robots is that the robot is not human. Skills that robot has are like modules. If we think of things like neural networks or deep learning networks. Robots can also act as workstations in those systems. In that model, all participants of the deep-learning neural network can watch different movies. Then those systems share their data over the network. And that means: that humans cannot respond to that kind of thing. 

https://scitechdaily.com/robot-that-watched-surgical-videos-now-operates-with-human-level-skill/

The tiger awakens.

The new and powerful technology is the tool, that is one of the most dangerous things in the wrong hands. Wrong hands are our counter-players in the global theater. The image in the middle of the text introduces the new Chinese large-size sea drone. The robot ship can be the tool for next-generation naval power. The ship itself looks like some kind of yacht, but it's armed and dangerous. Fast and powerful sea drones that use things like Mach-6-10 railguns are feared things. 

The Chinese military is interested in AI. It is a tool that can make many systems more trusted than manned systems. The problem with manned submarines. A and warships is that they are out of control when they are at sea. That is problematic for the People's Republic of China. The authoritarian communist party causes hate, and especially new high-accurate weapons make warships dangerous for the nation's leaders. The Chinese military has modernized its weapons and other systems. The new tools are large-scale surface and underwater drones. 

"China unveils ‘Killer Whale’ stealth drone ship. The vessel which has a range of more than 7,000km will go on display alongside a collection of aerial drones at the Zhuhai air show" (SCMP, China unveils ‘Killer Whale’ stealth drone ship"

Those large- or full-size surfaces and underwater robots are following predictions. The large-size warships and nuclear submarines have space and electricity for highly advanced computers. That the AI is required to control those systems. The predictions about the full-size nuclear submarine drones that can patrol years underwater were made over 20 years ago. Those nuclear submarines can host any supercomputers. 

"A new photo has emerged of China’s mysterious stealthy corvette or light frigate, an intriguing design with low-observable features, which you can read more about here. In fact, the latest photo raises more questions than it answers, in particular, the presumed HQ-10 surface-to-air missile launcher at the rear of the deckhouse apparently being something else entirely." (TWZ.com, Our Best Look At China’s Stealthy Experimental Corvette)

The new robot surface combatants are a demonstration of the ideas and innovations. The People's Liberation Army wants to introduce the Western navies. When it demonstrates its power. The Chinese military uses industrial spying to steal information. That makes it possible to create new tools for the PLA. The PLA's new stealth corvette looks very much like Swedish Visby class corvettes. The thing is that things like magnetic rail guns that accelerate the ammunition to the speed of Mach 6-10 are things that make those corvettes deadlier than any Western vessels. Those railguns can sweep bunkers out from the beach and damage even large vehicles. 

"China’s rail gun sends smart bomb into stratosphere at hypersonic speed, then something goes wrong. Winged projectile achieves Mach 5, reaching altitude of 15km in test but was sent off course by rotation speeds, investigation shows. Lu Junyong and his team identified the cause of the problem with the help of artificial intelligence and propose solutions in peer-reviewed paper" (SCMP. China’s rail gun sends smart bomb into stratosphere at hypersonic speed, then something goes wrong)

The underwater systems that can shoot missiles, including hypersonic missiles are a very bad threat to Western navies. Those, possibly, nuclear-powered systems can hide underwater even years. And then they can also wait at the enemy, or predict enemy coasts to attack. The large-size robots can carry smaller robots that can slip into the enemy area. 

The new advanced systems are tools that can bring global politics and U.S. support to a critical point. The new advanced systems require more advanced counter systems than predicted. This means that the Pentagon must share also its latest equipment with the Far East and European theaters. 

https://interestingengineering.com/military/china-claims-breakthrough-in-electromagnetic-rail-gun

https://www.scmp.com/news/china/science/article/3262607/chinas-rail-gun-sends-smart-bomb-stratosphere-hypersonic-speed-then-something-goes-wrong

https://www.scmp.com/news/china/military/article/3285955/china-unveils-killer-whale-stealth-drone-ship

https://www.twz.com/sea/our-best-look-at-chinas-stealthy-experimental-corvette

https://en.wikipedia.org/wiki/Visby-class_corvette

The Cybathlon: Bionic prostheses are coming to sports.

"SFU researchers work with para-athlete Danny Letain on building a better "bionic hand." (Simon Fraser University / CC BY 2.0 Flickr" (Big Think, The Cybathlon: Bionic athletes compete for the gold — and push assistive technologies forward)

"In the international competition, people with physical disabilities put state-of-the-art devices to the test as they race to complete the tasks of everyday life." (Big Think, The Cybathlon: Bionic athletes compete for the gold — and push assistive technologies forward)

The bionic prostheses require the ability to code and decode the neural signals. 

Bionic athletes help develop bionic systems, which can help handicapped people. The new bionic prosthesis can have a sense of touch. They can act and look like natural limbs. 

The system requires electricity, and the user must load the batteries. A system called an isotopic battery or radioisotope thermoelectric generator (RTG) could solve the energy problem. 

Developers can use bionic prostheses to create systems that can revolutionize science, entertainment, and the military. The bionic space suits allow the astronauts to feel things that they touch. The virtual reality helps to see what they should do. If there are cameras in the space suit gloves. 

Those bionic prostheses can also send visual images to the brains. The system can use neuroimplants to create a neurological connection between the prosthesis and the brain's visual center.

The system can communicate with the neural system. And take movement commands from natural neuro tracks. That normally transfers information between the brain and hand. 

The problem is that the hand's neural tracks are not connected with the visual center. The solution can be the neuro-implanted microchip that sends electric impulses to the visual center. That tool can use a nano-size optical cable to communicate with the prosthesis. 

Those bionic systems can also make it possible to create remotely controlled robots. That can send their sensory data to the remote controller operators. Those operators see, hear, and feel everything that the robot feels and hears and sees if they use brain-computer interface, BCI, 

The BCI makes it possible to use robots as external bodies. This technology brings next-generation tools to people that they can use in everyday work. Or in special situations. 

And that is a big advance that can also have some negative uses. But those robots can save lives and minimize risks when people sometimes land on the red planet or at a longer distance from the solar system. 

The problem with possible harbors of life is this: if an astronaut breaks the suit, the surface of the planet or the moon is polluted. And if the ice cab of the icy moon or carbon dioxide ice vaporizes under the astronaut's feet, that causes a horrible situation. 

https://bigthink.com/the-present/cybathlon/

Are we ready for AGI, and robot combination?

Artificial general intelligence AGI is one of the things that cause discussions. Somebody says that it releases low price people. But somebody says that the AGI causes very big problems. The fact is that all changes cause problems. If we want to use some new things, we must learn how to use them right. 

The AGI is a tool that can make many things. Or it should be that tool. 

We can say that AGI is a group of action modules around the LLM. And that makes it one of the most powerful things. 

The thing is that. Nobody knows the limits of modern LLM-based AIs. 

And that causes another thing, that we should think about.

Do we already have the AGI? We can collect almost every kind of action package around the LLMs. And the limit is that there should be a tool that can interact with the LLM. In the AGI model, the LLM takes the order. And then it transfers the mission to the module responsible for that action. 

If we want AI to cook food for us that tool requires an actor that operates in the physical world. The medium between computers and humans is robots. The man-shaped robot is one of the most interesting tools that we can imagine. That tool can affect society stronger than ever before. The LLM-based AI is not even five years old. And it started a revolution, especially in the ICT industry. So, what kind of revolution can the AI that controls robots in independent actions like cleaning? 

That means the requirement for calling things like robot vehicles to the door requires that the LLM has the socket that allows it to call robot vehicles. Or it must have a robot that takes the car. The human-looking robots are tools that can download any type of action package. And that makes those things act as chefs, cleaners, drivers, or anything that the user wants. 

But are we ready for those tools? The AGI is impressive. It learns faster than any human. The thing is that. This kind of system can revolutionize the world. The same robot that can act as a chef or cut our grass and drive our children home can operate as a merciless weapons. Those systems are dangerous in the wrong hands. The problem is that even if there are some kind of laws and other things that limit the AI use as a weapon controller those systems require very high-level data security. Things like organized crime can also use robots for their purposes. 

The thing that makes robots a powerful tool for the underworld is that those people can erase their memories. If we think the man-shaped robots that look some certain people, we face one problem. The problem is that some people can make full-size copies of bank managers. Those robots can walk in the banks. And then make money transactions for hackers. 

When we think about the first-person view robot, that looks like a human, we are facing one of the most interesting things. The hacker can operate that kind of robot using VR glasses and other input tools like data gloves. Then hackers can put that robot play things like cleaner. And when that robot slips in the office hackers can use it as a remote tool to control the computer. That is one of the illegal activities that this kind of robot can make. And those robots can also operate on the battlefield and cover operations. 

Robot taxis and other robot vehicles are coming.

Robot vehicles like delivery robots are everyday tools in traffic. The small delivery robots are pathfinders for the next big step to AI-controlled traffic. 

The next-generation tools for traffic are robot taxis or full-size robot vehicles. Robot taxis that can carry humans are one thing that can improve our traffic. 

Or, full-size vehicles that can carry humans and bigger cargo. Things like electric vehicles accelerate robot vehicle's generalization. In many images, we can see that robots drive vehicles. 

Robot taxis can drive themselves using internal computers. Network-based structure makes it possible for those computers can share their calculation power with each other. The system can also scale new rules like changes in speed limits for every vehicle that is part of that network system. 

But those systems can involve human-looking robots. That can assist customers. 

Those man-shaped robots can carry packages. And help with other things. And they can also protect those customers against things like robbery. 

The robot vehicle can load itself automatically from the loading station simply. Putting the manipulator with a plug into the socket. Electric vehicles are the most effective tools in limited areas like in cities where they can operate in well-calculated areas. Where they know precisely the distance to loading stations. 

There are also plans to create robot buses and lorries that can operate independently. Things like GPS and mesh protocol in data transmission make it possible to drive the AI. That controls those vehicles. The customer gives the orders to AI through the LLM, a large language model. Then the system selects the route to that destination. The system follows certain parameters to make selections and those parameters include things like how heavy traffic is. 

Diagram of a fully connected Mesh network

And where the customer can jump out of the vehicle. The central computer can follow those vehicles that can also operate as drone swarms.  If some of those vehicles are in a shadow area the system can search it by using the assistance of the other members of the network. 

https://bigthink.com/the-future/the-robotaxis-have-arrived/

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