Writings about astronomy and technology.

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-sc

Above: Image By Gemini.  When we talk about the collapse of language models. We talk about the phenomenon where artificial intelligence starts to recycle data through it. In many models, the AI that uses certain data sources starts to raise their page rank in the web index. That means that it's possible. That data starts to travel in the ring of the most used LLMs This thing causes an effect called data degeneration. The data degeneration means that as DNA will not be completely copied in living organisms in networks data will not stay perfectly in its shape.  There are always some kind of errors. And some turbulence in the networks. The network sometimes lost a byte or two. That thing causes the loss of information that travels in the networks. At the beginning of that process, outsiders do not recognize anything. But when there are enough lost bytes or bits that thing causes the effect, that there are lots of missing parts in data. So that means that data is degenerating in the n

The AI participates in new microchip development. New large language models, LLM, require a new microchip architecture that can drive and handle bigger data masses. When the AI drives a large data mass, the AI compiles the input data with databases. There are descriptions of how the AI should react to some situations. If details or parameters match with some database, that database begins a reaction.  The problem is that things like machine view require that the system analyze lots of data in a short moment. If the system has a neural network in use, it can share data with lots of computers. Image 2 is the neural network model and every single point between lines can be the independently operating microchip. The problem with a 2D neural network is that the data begins to travel from machine view through the system. In this linear model, the system shares data with processors one after one.  That a kind of linear model. Where data travels in a system like a wave. That system is quite sl

When man meets AI, the man is more intelligent. That means that the creative AI is not creative at all. The man who uses the AI is creative. The thing that we should understand is this: what we see as an example of "fuzzy logic" is a large number of precise reactions or precise logical points.  That means that there are multiple words. Or otherways saying:  multiple triggers. That is connected with a certain operation. This allows users to use dialect words or literally while using the AI.   The dialect words and literary words are both connected to certain operatios. That gives the user freedom in the form of language. What the person uses to command the system.  In this model, users can use both, dialects and literary words. That makes the AI more flexible than if the user must use precise literal words.  We can say many ways something that launches the action. The words, connected with certain operations are called logical points. Developers can connect each action with mu

Linux enthusiast Linus Thorwalds said that 80% of AI is marketing, and 20% is true. That is the normal relation in computer applications. The news about "doomsday AI": or, AI that destroys the world, makes AI look alike more fascinating than it is. But the fact is that the AI and its ability to generate the code should cause re-estimation in data security.  The neural network can attack systems with powerful methods. In neural networks. The AI can change the attacking computers. And their IP's all the time. The AI-based systems also make it possible to use dynamic IPs that make it harder to track those computers. The large-scale neural networks can also operate as the artificial general intelligence, AGI.  The news about the AI's ability to make code and even essays brings new users to those systems. Also, things like weapons and other kinds of stuff make the AI news interesting. Networks are things that make the AI real. They allow the AI to search data from the net.

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

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 custome

"An illustration of the 2D perovskite material that was studied by the researchers. The yellow parts illustrate the linker molecules while the purple and pink parts show the perovskite layer. Credit: Chalmers University of Technology | Julia Wiktor" (ScitechDaily, Unlocking the Future of Solar Cells: Scientists Discover Key to Stable Perovskites) Wikipedia determines quantum materials like this: "Quantum materials is an umbrella term in condensed matter physics that encompasses all materials whose essential properties cannot be described in terms of semiclassical particles and low-level quantum mechanics. " (Wikipedia, quantum materials) "These are materials that present strong electronic correlations or some type of electronic order, such as superconducting or magnetic orders, or materials whose electronic properties are linked to non-generic quantum effects – topological insulators, Dirac electron systems such as graphene, as well as systems whose collective

The combination of pressure and low temperature makes it possible to create new types of superconductors. That thing allows researchers to create new fundamental quantum computers. And as you see advancing of quantum computers advance their advance. When quantum computers participate in quantum computer research and development, that thing makes them more advanced than ever before.  Another thing is that: quantum computers advance slower or less dramatically than the first quantum computers. The quantum computers are the most advanced tools that we can imagine. When we think about their role in high-power computing, those systems will become more and more effective. When more people and laboratories participate in those quantum computer R&D processes. That makes them more effective than before.  The "less dramatic" advance means that. Quantum computer advances happen in places. Where the users cannot see. That thing is the increase in the qubit states. Or making more adva

Sometimes, researchers say that the developers of the AI lost control of their product. The reason for that is that the AI advances so fast. But they don't answer questions about why AI advances so fast. The answer is that the AI takes part in the AI development. The other thing is that the AI is the tool, that almost everybody can use.  The AI is not a tool that everybody can use automatically. The system requires that the user gives commands using good grammar. So learning to give commands in the right way to AI takes time. And the AI use requires practice. Or everything can go wrong.  The ability to use AI to make new solutions and new applications increases the number of solutions, that use the large language models, LLM, or can communicate with LLM through some other applications. That means that. Many more or less official enthusiasts use AI for software development. And that causes the effect. That the AI-using developers will create many new more or less legal applications.

Image: ScitechDaily This is the breakthrough in the AI and its development. The AI that searches for things like cancer is the tool that can make new waves in medical work. This kind of search is the tool that leaves more time for doctors to talk and discuss with patients. And maybe that returns the medical work to its roots. Or in the worst case that gives a reason to kick more doctors off their work. Decision is in the hands of the people, who control social politics.  The AI is neutral, and it doesn't make mistakes. The AI can collect data from many data sources into one entirety. And that makes it the ultimate tool for this kind of work. AI can search for cancer using DNA, antibody analysis, and X-ray images. And it can make that search a routine operation. If the cancer is detected in the early stage, It increases the ability to heal from that disease.  When we think about the Chat GPT-type assistants that operate with doctors we must understand one thing. Its purpose is to ma

The main problem with computing is when developers make something. There is needed new solutions almost immediately. Those new solutions make the application interesting. And many times. Those new solutions mean new abilities for applications. New skills require new libraries. And that thing cumulates the size of the program.  The new libraries require more space and more effective computing. The thing is that AI is going to more detailed program code. When we think about the first AI "chatbots" the simple programs that asked people some questions, and then the program gave some pre-programmed answers, we must realize that those programs looked intelligent.  One example of those programs is a program that asks:  Are you a boy or a girl? A: Boy What's your name"? A: John How old are you? A: 23 Where do you live? Bristol Then the program said:  Please to meet you:  You are a boy, whose name is John. You are 23 years old, and you live in Bristol. And I'm your servan

  The AI can make programming more effective than ever before. However, the quality of the code can decrease. In the same way, AI can make inflation into computer art.  Maybe AI will not destroy the world. But it will change it forever. Things like creativity are now possible without a long time and drawing skills. And that makes the AI a fundamental tool for publishers. The images below this part of the text are AI-created. The creation of those images took about 30 minutes. And that thing tells how easy is to use the AI. That is a fantastic and sad thing. The creation of nice images doesn't require any kind of drawing skills.  The user must only describe those images to the AI and then it creates those images. AI is a tool that can kill real creativity.  I think that the images that Bing created are examples of how people will start to make things using AI. The AI is effective. Business life respects effective people. Even if we think. That AI will not advance anymore. Or advanci

    Researchers possibly found carbon from Jupiter's Europa-moon ocean.  But first thoughts about the journey to Jupiter.  Maybe AI-controlled robots make the first journey to the Jupiter system and they can collect samples from those moons. The flight time to Jupiter is long even if we would use nuclear thermal propulsion. So before we can even think that we could send a manned flight into Jupiter.  We must wait for fusion and antimatter engines that will open the path into the entire solar system. In Jupiter's system, the probe or spacecraft operates with smaller shuttles that collect samples from those moons. The researchers must confirm that there are no harmful organisms in those oceans before they make the site.  In some visions, the astronauts who travel to Jupiter in the future would live in a space station that hovers in those hyacid oceans. In those visions, water in those oceans can be used as drinking water and as a fuel source. There is a vision that the electrolys

     Darpa's Exacto bullets are the next step in the R&D of laser and GPS-guided projectiles.  The Excato (Extreme Accuracy Tasked Ordnance) is the new tool for sniping. The bullet is guided ammunition that acts similar way to larger GPS and laser-guided artillery munitions. The guided bullet itself is not a new idea. And it has been tested a couple of times. But modern nanotechnology makes guided ammunition for rifles possible. The Exacto ammunition is highly classified.  However, the information that is given to the public tells that Exacto is following the scope movement. And that thing tells that Excacto is laser-guided. The bullet can turn its route. It uses wings for that purpose. Or the Exacto can use the nanosize scales that are rising on the side, where the bullet needs to turn.  The Barrett M81A1 (Wikipedia/Barrett M82) .50 Browning.  Surely, DARPA develops guided bullets also for smaller calibers than .50 Browning. And maybe, quite soon the smart bullets are coming i

   The Chat GPT is a pathfinder but in the future, smaller and more specific AI systems change the game.  The Chat GPT,  Bing, and many other AI-based chatbot versions are massive systems that should fit every situation. The problem with common AI is that these kinds of systems require lots of capacity, and there are lots of sources that those systems must use.  This thing means that the trustworthiness of sources is problematic. The reason for this thing is that the AI doesn't think. It collects data by following certain parameters. That thing makes those systems vulnerable in cases where they should search for information that is not very common.  The smaller-size specific AI-based systems that can use the same engines with Chat GPT and Bing are more suitable for things like scientific writing. The AI is an ultimate tool if it has a pre-programmed list of trusted and estimated sources. If a writer wants information about some very uncommon things like quantum mechanics. The AI ca

  The biggest difference between machine learning and human is that human uses fuzzy logic. The machine uses precise logic for its actions. When a machine operates, it uses precisely described action chains. The problem is that no pre-programmed action chain has a match for a real-life situation.  On the streets are some surprises. Like suddenly coming cars are everyday situation. Nobody can predict all possible situations that robots can face in real life. And that makes the system hard to program.  Precise logic means that programmers must describe every single thing that requires notice or reactions to the machine. The machine cannot operate. If something is missing from its code.  When the learning system will face that kind of situation it says "unknown situation". And then ask for orders from the human operators.  The reason. Why ChatGPT passed the U.S. medical examination, but the AI cannot recognize U.S. marines that closed the base because the type of information tha

There are two versions of AI or Artificial intelligence.  *Software-based AI. That is the software that emulates some intelligent- or intelligent-looking actions.  *The Iron-based AI. That system is the physical system that learns things. Those iron-based AI systems are like brains. They are learning like the brain.  The organic version of those systems is the laboratory-grown neurons. That is connected to machines. The idea of iron-based AI is that there is no need for any kind of special software. The system is cognitive and it learns to be like the human brain.  Most modern AI solutions are algorithms. And that means they are software-based systems. But new knowledge of the brain. And especially neural interconnections are making it possible to create "iron-based" artificial intelligence.  The "iron-based" artificial intelligence is the system that we can describe as the "artificial brain". But the problem with the human brain is that the neurons have m

When researchers are making AI which purpose is to make complicated observations. They are facing one problem. The AI makes dangerous shortcuts. And the reason for those shortcuts is that making the observation is a more complicated process in the brain. Then just some neural signal transfer through the brain.  In the brain, all senses, like the sense of balance, view, audition, touch, and other things are taking part in the observations. And that means the observation is always the sum of signals from different senses. But then we are always forgetting one thing. Those signals travel from the mixed with memories.  So the observations are:  *Signals from real-time senses that are connecting with  *Memories.  And that makes observation modeling for AI mode more difficult than researchers thought. The problem is that the complicated situations the AI must make precise observations so that it can create the right reaction and response for the systems.  The problem is how to model senses.