These latest computer science technologies are emerging fast in 2022.
What’s Technology’s Future?
We live in a digital world. Everything is becoming online and we are using machines instead of humans to make our lives easier. But how far can you tell what’s going to be the future of tech? What will technology become in computer science in the next five years?
Let’s get some answers from data scientists! As a developer of several machine learning software, I am always asking myself questions like “Will I use it or not?” The majority of human beings imagine that there is no modern technological development every year, but truly there are numerous breakthroughs taking place. Here is the list of ones.
1. Bigger Computers
Big computers can handle the most complex problems, and data has never been so easy to collect. All your dreams come true because of big powerful machines. For example, Google Tensor Machines can do 1000 times better than traditional statistical computing models.
2. Artificial Intelligence
AI is taking over the entire industry. We have already seen its application in various fields, for example, self-driving cars, chatbots, fraud detection, etc. So, AI is also one of the biggest advances in the field of technology! Also, with machine learning, you can predict things like if someone is going to fire a gun or whether they are about to open an umbrella! This technology is changing every area, including security. You should not even worry about these kinds of predictions because they are made by artificial intelligence! Isn’t that amazing? The possibilities are endless! How many applications do you see now? Artificial intelligence is the top technology in computer science.
3. Quantum Computing
Now, what does quantum computing mean? Well, it means storing information without a memory. When you store information as you used to when you were a kid, you don’t need it again. This might sound very weird, but once in a while, you should know the difference between classical and quantum computing technology in Computer Science.
4. Neuromation
Neuromation is another name that means neuromorphic chips. These chips are similar to human brains (which are made up of biological brains) but have much more powerful components. Neuromation has three main capabilities: 1. Neural networks 2. Deep learning 3. Memory 4. Hardware 5. Security 6. Robotics Wearable devices 8. Gaming. 9. Wearables 10. Image, Neuromation is also a new technology in computer science.
Neural networks and deep learning are very important tasks in the modern era. Let us take a look at how it works! Each neural network consists of several layers. They are similar to synapses in electrical circuits. As you can see, the weights of each layer determine its output. If you want to pass the same information to several networks, you have to add many layers. Then you have to train them! But wait, I have only given you an example of neural networks. You can apply both neural networks and deep learning. There are many more advanced models!
Neural networks and deep learning are quite complicated networks, so we have to understand them. Now how do you solve them? Let us consider a simple problem: training a neural network to identify birds from images. One way is to start with a set of pixels, which are colored squares. Then you connect them with lines representing edges to form a network, and then you feed in images of birds. And as you see, after feeding lots of examples, you can do a pretty good job with that network.
However, this process is slow and expensive and takes forever to solve. Another approach to solving neural networks and deep learning is to use mini-batches. A lot of training data is stored in one place. So, you have to split it into smaller chunks and run training on each chunk. That was quick. So, what is wrong with it? It is faster than previous approaches. But why? because the computation needed for this algorithm is also quite high and doesn’t require millions and millions of samples. Yes, you still have to save lots of time, but the quality of it is way higher.
Neuromation chips may sound absurd, but they could be game-changers! Think of a world with thousands of different neural architectures! Imagine how difficult it will be for you to select the right model for any application or problem. Maybe that is already possible. Perhaps we won’t need to spend so much money to develop one-to-one minions of neural networks. Or maybe in the future, everything will be automated.
Bioinformatics
Bioinformatics professionals study the storage and analysis of biological information. A multidisciplinary subfield that combines computer science and biological bioinformatics to find patterns in sequences of genetic material such as DNA, RNA, and proteins. Bioinformatics workers develop methods and software applications that accomplish these tasks.
Medical and pharmaceutical industry environments, government information technology fields, and information technology fields benefit greatly from bioinformatics and computer science techniques. Bioinformatics helps doctors in preventive and precision medicine detect diseases early and provide effective targeted therapy treatments.
PayScale reports that as of June 2021, the average annual salary for a bioinformatics scientist is $96,230. From 2019 to 2029 the BLS expects employment growth for bioengineers and biomedical engineers to be above average.
Major employers of bioinformatics professionals include the Bureau of Land Management Department of Defense hospitals and research laboratories. Administrative teaching and supervisory positions may require a master’s or doctoral degree.
Cybersecurity
Cybersecurity focuses on defending computer systems and networks from cyber coercion and attack. As companies continue to store information on the cloud and conduct business online, the need for improved cybersecurity also grows.
Individual businesses and governments suffer significant financial losses from cyberattacks. For example, a ransomware attack in the eastern US in May 2021 cost Colonial Pipeline about $5 million and drove up gas prices for consumers.
Most industries, as well as healthcare organizations, financial organizations, and insurance companies, need better cyber security technology to defend their proprietary and customer data. Due to this demand, the BLS expects employment growth for information security analysts to reach 31% from 2019 to 2029. In information security, as of 2020, the median annual salary for analysts is $103,590.
Cybersecurity specialists work in consulting firms, computer companies, and commercial and financial organizations. Apple, Lockheed Martin, and Capital One are exemplary employers. The greatest employment in cybersecurity needs a bachelor’s degree, but some organizations prefer a master’s.
Summary:
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