Top 5 Computer Technologies in 2021- Every Computer Science Student Should Know

SHASHANK SHAHARE
Live to learn
Published in
5 min readFeb 1, 2021

It has become appallingly obvious that our technology has exceeded our humanity.

The world is surrounded by computers and technologies are going so fast that we can’t even imagine. There was a time when personal computers were the biggest deal for tech companies. After personal computers, there was a problem for a large amount of computation, after dealing with the hardware there was trouble finding an efficient Operating System that could utilize the hardware and give the great software experience.

Today we have the fastest supercomputer Fugaku which has nearly 7.3 million cores and a speed of 415.5 petaFLOPS. That is 1⁰¹⁵ times faster than Intel’s flagship processor i9, the technology is growing that fast that even this amount of computational power is not enough. We will see the top 5 technologies which could change the world entirely.

1. Artificial Intelligince

This is one of the hottest topics since 2016, more and more developers and computer science students are enthusiastic about AI. There was a time when this technology was only used by the companies which work on Robotics or Space agencies for developing high tech robots that can survive the environment of space or other planets and researchers can do their research with the help of that machine. But now AI is not just something for big companies everyone is using AI in their smartphone in the form of Alexa, Google Assistant, etc.

AI is a technology that gives the ability to the machine to make decisions and does tasks as the intelligent brain can do. It is just a mimic of a human brain. According to the news By 2030, AI automation can generate about 70 million jobs but the negative point is it might wipe out 21 million jobs at the same time. This is technology is worth learning if you want to secure your job in the future.

Important Topics in Artificial Intelligence

  1. Machine Learning
  2. Data Science and Data Analysis
  3. Computer Vision
  4. Deep Learning (Advance concept)

2. Smart Applications

Smart application is a new concept introduced in 2018 which suggests that the application which can make a decision by itself and organized the data of users. For example, if someone is using the Netflix app for streaming the smart app will personalize user recommendations by computing a person’s watch time, genre, content, etc. With the help of this concept, the user will not have to send their data to any company it will be computed locally.

There are some smart applications already built which we use in our day to day life like Alexa, Google Assistant, Siri, etc. This concept can be integrated into every application to enhance the user experience. The small App can be a personal assistant that will help a person in his/her day to day life. This technology will generate jobs in a high amount in the future by big tech companies like Google, Amazon, Oracle, etc.

3. BlockChain

A blockchain originally block-chain, is a growing list of records, called blocks, that are linked using cryptography. Each block contains a cryptographic hash of the previous block, a timestamp, and transaction data (generally represented as a Merkle tree). By design, a blockchain is resistant to modification of its data. This is because once recorded, the data in any given block cannot be altered retroactively without the alteration of all subsequent blocks.

This technology is used in Bitcoin, Ethereum, and other Cryptocurrencies. Blockchain is not just for cryptocurrencies, recent study and research suggests that this technology will revolutionize the way the data security works. The principle of Decentralize is the most valuable asset for data security. There is no one server where one’s data will be stored or there is no chance anybody can see or hack the data present in the ledger. By statistics, this technology will use as widely for other scopes by 2030 which will generate millions of jobs.

4. Internet of Things

The Internet of things (IoT) describes the network of physical objects — “things” — that are embedded with sensors, software, and other technologies to connect and exchange data with other devices and systems over the Internet. It is predicted that more than 41 billion devices powered by IoT will be used by 2025.

This technology is used in applications like Smart Home, Elder Care, Medical and Healthcare, Transportation, V2X communication, Home automation, Agriculture, etc. This will help people to have remote access to all the products they use daily like you leave the house and forgot to switch off the oven with the help of IoT you can switch it off using a smartphone from anywhere.

Learning IoT technology secure jobs such as:

  1. IoT Product Designer
  2. IoT Cloud Engineer
  3. IoT Product Manager
  4. IoT Research Developer

5. Virtual Reality

Virtual reality (VR) is a simulated experience that can be similar to or completely different from the real world. Applications of virtual reality include entertainment (e.g. video games) and education (e.g. medical or military training). Other distinct types of VR-style technology include augmented reality and mixed reality sometimes referred to as extended reality.

Facebook’s Oculus Rift, Sony’s PlayStation VR (PSVR), and the HTC Vive are already in the game of VR.

The global augmented reality (AR) and virtual reality (VR) market is forecast to reach 72.8 billion U.S. dollars in 2024. This would be an increase of 54 percent five-year CAGR overspending.

Learning this technology will help to find the jobs such as

  1. AR and VR Content Producer
  2. VR Engineer
  3. UI and UX designer
  4. 3D model developer
  5. Software Engineer

Conclusion

There is more technology I didn’t put on the list but definitely dominates the market and worth learning.

  1. Data Science
  2. Robotic Process Automation
  3. Edge Computing
  4. Cloud Computing
  5. Quantum Computing
  6. Cyber Security
  7. 5G

The technology trend depends on the market and demands. The rank I have given above for technology trend is analyzed by Github, Stackoverflow, and FAQ on several Blogs and Forums.

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