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Basic Block Diagram of Computer for Kids
A computer is a complex electronic device that performs various tasks using hardware and software components. Here's a basic block diagram of computer simplified for kids:
Brain (Central Processing Unit - CPU): This is the computer's brain. It thinks and processes information. It's like the boss of the computer.
Memory (RAM): This is the computer's short-term memory. It helps the computer remember things while it's working on them. It's like a sticky note pad.
Storage (Hard Drive or SSD): This is where the computer stores all its important stuff, like pictures, games, and documents. Think of it as the computer's filing cabinet.
Input Devices: These are things you use to tell the computer what to do. Like a keyboard to type, a mouse to click, or a touchscreen to touch.
Output Devices: These show you what the computer is doing. Like a screen where you see pictures and words, and speakers that play sound.
Software: These are like the computer's apps and games. They tell the computer how to work and what to do.
Motherboard: This is like the computer's body. It connects all the parts and makes sure they work together.
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Computer Vision
Garner valuable insights from images, videos, sensors and geo to discover endless possibilities using Artificial Intelligence and Machine Learning
Computers have changed the world drastically and societies are more technologically advanced than ever. However, even the most advanced machines struggle to interpret what it sees. A computer cannot differentiate between a discarded takeaway bag and a piece of stone on a road or distinguish a frown from a smile on the same face. Computer Vision (CV) is the part of artificial intelligence (AI) that enables computers or machines to analyze and understand images. Computer Vision provides inputs to machines to make sense of the different images it is fed with. By reconstructing, recognizing, and re-organizing inputs, it guides machines to interpret objects, actions, events, and relations in the image.
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TOP APPLICATIONS OF QUANTUM COMPUTING EVERYONE SHOULD KNOW ABOUT
WHAT IS QUANTUM COMPUTING?WHY DO WE NEED QUANTUM COMPUTERS?ARTIFICIAL INTELLIGENCE & MACHINE LEARNINGCOMPUTATIONAL CHEMISTRYDRUG DESIGN & DEVELOPMENTCYBERSECURITY & CRYPTOGRAPHYFINANCIAL MODELINGLOGISTICS OPTIMIZATIONWEATHER FORECASTIMPROVE CANCER TREATMENTOPTIMIZING TRAFFIC FLOWPORTFOLIO OPTIMIZATIONSIMULATE MOLECULESMAKE AI MORE HUMAN-LIKECUSTOMIZED ADSCONCLUSION
https://technologyfullshow.com/top-applications-of-quantum-computing-everyone-should-know-about/
Top Applications Of Quantum Computing Everyone Should Know About. With the growth of exponential computing power, quantum computing is preparing for its closure. Quantum computers are well suited to solve complex problems. Which are difficult for older computers but easier to install on quantum computers. Such progress creates a world of opportunities, in all aspects of modern life.
In fact, Google has recently made headlines announcing the success of mass media. Where computers can do a job that ordinary people can never do. It is also making noise about their big, fast-paced computers. So, we often wonder what these things really do and what are their global uses?
Quantum theory is a field of study that focuses on attempting to explain a phenomenon of power and issue on a scale of quantity.
Add that to computer applications, and we get the Quantum computer. Which uses the principles of quantum theory to create computer technologies.
This in itself is a small area of quantum information science; quantum computing is a learning environment that combines quantum cryptography and quantum communication.
Computing computers are expected to have computer technology much larger than that of abacus and modern supercomputer.
Following the laws of physics, quantum computers will have greater power. As they will be able to be in multiple locations simultaneously and perform tasks using all possible permissions simultaneously.
The possibilities of using quantum computing are endless. Here are a few of the quantum computing applications from the larger possibilities.
Quantum computing technology is rapidly emerging that utilizes the rules of digital computing to solve complex problems for older computers.
Today, Quantum manufactures real quantum Hardware – a device that scientists began to speculate 30 years ago – available to thousands of manufacturers. Our delivery engineers are constantly powered by multiple superconducting quantum processors from time to time. Building-specific quantum computer speeds and capabilities needed to change the world.
These technologies are very different from the old computers that have been around for more than half a century. Here is the first one in this technological revolution.
When scientists and engineers encounter complex problems, they turn to larger computers. These computers are very old-fashioned, often with thousands of class CPUs and GPU cores. Thus, even big computers have trouble solving some kind of problem.
If a supercomputer is disabled, it may be because a large class machine has been asked to solve a problem with a wide range of complexity. If old computers fail, it usually happens due to complexity
Complex problems have many variations that interact with complex processes. Comparing the structure of each atom in a molecule is a complex problem because all the different electrons interact. Designing the right methods for a few hundred global networks sending tanks is also difficult.
In this section, we will discuss some of the advanced quantum computing applications in the real world.
Artificial intelligence and machine learning are some of the most popular areas right now. As emerging technologies have penetrated all aspects of human life. Some of the most common applications we see every day are in word, image, and identity recognition. Thus, as the number of applications increases, it becomes a difficult task for traditional computers, to compare orderly and faster. And, that’s where quantum computing can help in solving complex problems in a very short time. It would have taken old computers thousands of years.
It is believed that the quantum number states that, even the smallest molecule, is very large, and therefore difficult for normal computer memory to fix. The ability of computer quantum to detect the presence of 1 and 0 at the same time can give great power to the machine to successfully map its molecules, which will open up opportunities for drug exploration. Some of the serious problems that can be solved through quantum computing are – improving nitrogen-fixing mechanisms to produce ammonia-based fertilizer; making room-temperature superconductors; removing carbon dioxide for a better climate, and manufacturing government batteries.
Designing and developing drugs is the most challenging problem in quantum computing. Usually, drugs are developed through trial and error. Which is not only very expensive but also a risky and challenging task to complete. Researchers believe quantum computing could be an effective way to understand drugs and their reactions in humans. This, in turn, could save drug companies a lot of money and time. These advances in computing can dramatically increase efficiency, by enabling companies to do more drug discovery to uncover new medical treatments for the better pharmaceutical industry.
Today’s online security space is quite vulnerable due to the increasing number of cyber attacks happening all over the world, every day. While companies are building the necessary security frameworks within their organizations, the process is becoming daunting and cumbersome for classic digital computers. And, because of that, cybersecurity continues to be an important concern around the world. With our increasing reliance on digitization, we are becoming more and more vulnerable to this threat. Quantum computing with the help of machine learning can help in developing various techniques to combat this cybersecurity threat. In addition, Applications Quantum Computing Know can help in creating encryption methods, also known as quantum cryptography.
For the financial industry, finding the right mix of worthwhile investments based on expected returns, associated risks, and other factors is essential to staying in the market. In order to achieve that, the ‘Monte Carlo’ simulation technique continues to be run on conventional computers. Which in turn consumes a lot of computer time. However, by applying quantum technology to perform these large and complex calculations, companies can not only improve the quality of solutions but also reduce the time to develop them. Because financial leaders are in businesses dealing with billions of dollars, even a small increase in expected returns can mean a lot to them. Algorithmic trading is another potential application where the engine uses complex algorithms to automatically trigger stock transactions by analyzing market variables, which is an advantage, especially for high-volume transactions.
Enhanced data analysis and robust modeling will indeed enable various industries to optimize their logistics and scheduling workflows related to their supply chain management. The operating model needs to continuously calculate and recalculate optimal routes for traffic management, fleet operations, air traffic control, transport, and distribution, and that can have a severe impact on applications. Usually, to perform these tasks, conventional computing is used; however, some of them may turn out to be more complex for an ideal computational solution. Whereas a quantum approach may be able to do so. Two general quantum approaches that can be used to solve this problem are — quantum annealing and universal quantum computers. Quantum annealing is an advanced optimization technique that is expected to go beyond traditional computers. In contrast, universal Applications of Quantum Computing Know capable of solving all kinds of computational problems, are not yet commercially available.
Currently, the process of analyzing weather conditions with traditional computers sometimes takes longer than the change in the weather itself. But the ability of quantum computers to process large amounts of data, in a short period of time, could indeed lead to improved modeling of weather systems that allow scientists to predict changing weather patterns in a short period of time and with great accuracy — something that is important for now. when the world is experiencing climate change.
Weather forecasts include several variables to consider, such as barometric pressure, temperature, and air density. Which makes it difficult to predict accurately. The Applications Quantum Computing Know machine learning can help in improving pattern recognition. Which in turn will make it easier for scientists to predict extreme weather events and potentially save thousands of lives every year.
We’ve all faced times when we see a sunny weather forecast, and as soon as we step outside, the weather starts to drop. Weather forecasts are never 100% accurate.
In 2017, a researcher from Russia published a paper proposing the possibility Quantum computers predict the weather more accurately than classical computers.
There are certain limitations that our computers face today in predicting all the complex weather changes. The main problem in predicting the weather correctly is the involvement of large amounts of data.
With the help of the Dynamic Quantum Clustering (DQC) methodology, Applications Quantum Computing Know expects to speed up data processing to give us more accurate weather forecasts.
If recognized at an early stage, some forms of cancer treat.
The main factor in treating cancer with radiation therapy is the optimization of the beam. The radiation given to the patient kills the cells in the region, which it affects.
Often, along with the cancer cells, some parts of the surrounding healthy cells are also destroyed.
Various radiation methods develop in the last decade using our classic computer.
However, in 2015, researchers at the Roswell Park Cancer Institute proposed a new way to optimize radiation beams using annealing quantum computers.
Traffic is one of the main problems we face today. Google has tried to solve this problem by suggesting alternative routes and by highlighting places with moderate and high traffic.
However, it does not solve the problem of traffic on the highway. In 2017, Volkswagen tried to tackle the traffic problem by handling the traffic itself.
They used the QUBO-Quadratic Unconstraint Binary Optimization technique in conjunction with an annealing quantum computer to find the optimal route for a number of cars in addition to all the possible routes considered.
To date, they have tested around 10,000 taxis in Beijing to prove how this method optimizes traffic faster than a classic computer can.
Knowing which assets to invest in and which assets to divest is a challenge that cannot solve using modern computing.
Ensuring your portfolio is healthy will be the difference in the capital you achieve in the future.
Portfolio optimization is concerned with selecting the best assets to invest in, which balances risk with the expected return.
Problems that are difficult to solve for conventional computers, but quantum annealing can help answer them in an instant.
Molecular simulation helps us understand the structure of molecules and the nature of their interactions with each other.
Although classical computers are capable of simulating molecules, they have limited complexity in the simulations they can handle.
Quantum computers are able to overcome this limitation. To date, quantum computers have been able to simulate small molecules such as beryllium hydride (BeH2).
Even if this looks small now, the fact that it is a 7-qubit chip simulating this molecule has significance because if there were more qubits at our disposal, it would be possible to simulate larger molecules.
The processing capability of a quantum computer increases with an increase in the number of qubits.
Researchers have been trying to develop an AI, which is more human-like. Machine learning and neural networks are the underlying technologies behind AI.
An artificial neural network uses a data set based on a matrix for computational purposes, which uses matrix algebra.
Applications Quantum Computing Know itself works in such a way that matrices often used to determine the states of qubits.
So basically, any computational process performed on a neural network would be similar to applying a transformational quantum gate to a qubit (a quantum gate is a basic circuit that operates on a small number of qubits).
This makes quantum computers very suitable for implementing AI.
https://technologyfullshow.com/top-applications-of-quantum-computing-everyone-should-know-about/
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"[D] Any class recommendation for a student?"- Detail: Hi, I am currently a master student at GaTech. I was a game developer after I graduate from Pitt in Computer engineering. I am completely new to this realm. So, could you guys recommend some classes? There are just too many of them. And I only have eight classes left to finish.Here is the course list. Classes that are in bold text are what I selected.Algorithm(Pick one or more):Computability, Algorithms, and ComplexityComputational Complexity TheoryDesign and Analysis of AlgorithmsGraph AlgorithmsApproximation AlgorithmsRandomized AlgorithmsComputational Science and Engineering AlgorithmsCore(Pick one or more):Machine LearningComputational Data Analysis: Learning, Mining, and ComputationElective(Pick three or more):Big Data Systems & AnalysisComputer Vision Markov Chain Monte CarloSpectral AlgorithmsMachine Learning TheoryPattern RecognitionBehavioral Imaging Deep Learning Machine Learning for TradingNatural LanguageWeb Search and Text MiningData and Visual AnalyticsComputational StatisticsBayesian MethodsStochastic OptimizationSpecial Topics(Pick Less than four):Interactive Robot LearningML with Limited SupervisionMath Foundations Mach Learning. Caption by inexistentme. Posted By: www.eurekaking.com
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When you help your mother with her homework. #mom #learningcomputers #thisiswhyIhaveadegree #IT (em Alverca, Lisboa, Portugal)
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Best part of the whole fuckin movie right here. #learningcomputer #noproblemodickwad
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Blues Clues Electronic Learning Computer, 2000 Mattel Toys
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