Fiber drones are deadly tools.

FPV drones are deadly tools in the Ukrainian war. The Russian-developed optical drone is a fiber controlled which makes it immune to regular ECM systems. The control transmission travels through optical fibers, allowing the drone to operate in heavy jamming environments. Thin optical fiber makes it possible for a drone can operate 20-30 kilometers away from the operator. Dropping drones with regular ECM is not possible. So they can beat any jamming. 

But things like higher-power radio and microwave systems that burn those drone’s electrics can be the answer. The fiber-controlled drone is theoretically easy to destroy if somebody finds the control fiber and cuts it. If the defender finds the fiber normal scissors would be enough to cut the fiber. And one answer for that deadly problem can be a drone that is equipped with wire cutters. 

But the real answer can be the laser system that engineers can mount to cars and other vehicles. The laser ray can cut the optical fiber quite easily. The industrial laser can just grope the drone and its environment. And if the optical fiber is cut the control signals cannot reach the drone. The laser system can include lidar and weapon systems, or modes. When the system is in a surveillance model, it uses a large cone. And when the system cuts those optical fibers and destroys drones it uses the cutting laser beam. 

There is a theoretical possibility that if the opponent system can search and locate the command wire benefiting the light that is leaked from that fiber, that system can follow the optical fiber using a light amplifier. That leaked light can make it possible for the counter system to send drones to locate the operators or the drone support station where the optical signal has its origin. But that requires quite expensive tools. And the optical fiber must also leak light. 

Drones are a good example of how the improved weapon faces an improved defender. In early war large-size drones that were like remote-controlled combat aircraft ruled the battlefield. But the R&D work brought smaller, and cheaper FPV-kamikaze drones to the battlefield. The ECM, or electronic countermeasure signals made those drones useless. And the remote-control systems are easy targets for artillery that can locate them using their radio signals. The ECM can cut those signals easily. 

So the answer was the wire-controlled drones that were and are immune against ECM. The new solution could be a laser weapon that cuts those command wires. The next step is the independently operating drones that can search and attack targets independently. Those drones are tools that are cheap. And cheap prices make their advance fast. Drones along with the AI will revolutionize warfare. AI is cheap to use. If the algorithm is well done, operators must only load necessary programs to them. 

https://www.ga.com/advanced-weapons-technology/laser-weapon-systems

https://kyivindependent.com/as-russias-fiber-optic-drones-flood-the-battlefield-ukraine-is-racing-to-catch-up/

https://www.sustainability-times.com/energy/laser-powered-weapons-are-here-u-s-military-abandons-cables-in-radical-shift-that-could-revolutionize-battlefield-tech-forever/

https://www.twz.com/news-features/inside-ukraines-fiber-optic-drone-war

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

The new solutions in the computer systems emulate human brains.

"A joint university project funded by the NSF aims to create atomically tuned memristors for neuromorphic computing. The focus is on simulating brain functions for AI with high speed and efficiency. Credit: SciTechDaily.com" (ScitechDaily, Revolutionizing AI: The Tiny Tech Powering Brain-Like Computers)

There are many ways in which the computer can emulate human brains. The neuromorphic networks can begin their operations. Same time at different points. That means the neuromorphic networks must not stop before they take on another mission. And then another thing is that neuromorphic computers can use their calculation power to solve multiple problems at the same time. Or the systems can focus their energy on one single solution. 

That makes that kind of network faster than traditional computers that use only one processor that must stop before the next mission. Another way is to use the living neurons that can cooperate with new microchips. The ability to make neurons interact with microchips is one of the most effective ways to create computers that support large language models, LLM better than modern computers. The thing that neuromorphic networks must not stop before the next mission makes them suitable to control things like robots. 

"Researchers at the University of Minnesota have created a transparent conducting material that significantly boosts electron speed and efficiency in high-power electronics, potentially transforming fields like AI, computing, and quantum tech. (Artist’s concept.) Credit: SciTechDaily.com" (ScitechDaily, Transparent New Material Paves the Way for Advanced Electronics and Quantum Devices)

Temperature is the biggest problem with highly advanced microchips.

Before we can create room-temperature quantum computers we must use binary computers. And even if we would have room-temperature quantum computers, we would need binary computer to transmit data to the quantum system. Compact quantum computers require room-temperature superconductors. And researchers work hard with those things. Researchers search for new materials to replace silicon. And the promising thing is gallium nitride. 

The silicone microchips are at the end of their road. New materials like gallium-nitride metal alloys pave the road to the new processor technology. Those metal alloys cause less disturbance to the system. And that allows the system to keep a higher clock frequency than in silicon microchips. Those metal alloys also take less temperature. And that helps the system to keep the temperature low. The temperature causes problems with computers because oscillation disturbs signals.

"If you ever put your hands on a mobile phone charger, they’re warm and that’s the energy being wasted in the silicon,” Rachel Oliver, director of the Cambridge Centre for Gallium Nitride, told Freethink. “A gallium nitride charger will feel a lot cooler to the touch — it’s wasting a lot less energy.” (FreeThink, Silicon chips are no longer sustainable. Here’s what’s next.)

"Gallium and gallium compounds have been used in tech for decades — they’re in LEDs, lasers, military radars, satellites, solar cells, and more — but gallium nitride is currently a major focus of researchers looking for ways to make tech more powerful and energy efficient. " (FreeThink, Silicon chips are no longer sustainable. Here’s what’s next.)

"So why is the microchip industry built around silicon, if gallium nitride is superior in various ways and has been around for a while? The answer, as usual, is cost: gallium nitride chips are more expensive and complicated to manufacture. Getting costs down while scaling up production is going to take time, but the US government is trying to help jumpstart the nascent industry. " (FreeThink, Silicon chips are no longer sustainable. Here’s what’s next.)

The problem in superconductors is simple, how to control the electric flow? And another thing is that until researchers can create room-temperature superconductors those systems require powerful coolers. But maybe someday in the future, we can have superconducting computers on our tables. 

Superconductors are things. That can give answers to the new requirement for new microchips. The problem is that superconducting materials don't have resistance. So when the system tries to load information to the normal temperature systems. The wave that impacts electricity forms between those systems will travel backward in the superconductors. 

Another thing is superconducting microchips. The superconductor technology is quite a new thing. The superconducting materials can act like normal traditional semiconductors. But there is one big difference between those superconductors and traditional semiconductors. There is no resistance in the superconductor. That means things like resistors cannot work like they work in normal semiconductors. 

It's possible to adjust the superconducting ability of the material by using lasers. Lasers can increase the temperature at some points of the superconducting materials. When the temperature rises the material loses its superconducting ability. And that kind of system can adjust the superconducting by switching it on and off. 

https://www.freethink.com/the-material-world/gallium-semiconductors

https://scitechdaily.com/revolutionizing-ai-the-tiny-tech-powering-brain-like-computers/

https://scitechdaily.com/transparent-new-material-paves-the-way-for-advanced-electronics-and-quantum-devices/

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.