Why is Artificial Intelligence Important

Artificial intelligence is extending its frontier in technology and knowledge. Wherever you see, people are discussing machines with intelligence that improve our lives. A lot of applications and concepts remain highly technical and can be a little confusing if you're not strong at your foundation part. I am here to make you master the basics of artificial intelligence and help you conquer the AI world. This article will introduce you Why is Artificial Intelligence Important?

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What is Artificial Intelligence?

Artificial Intelligence

Artificial Intelligence is a subject of Computer Science aimed at building machines and computers that can enhance logical operations. AI systems have the ability to execute tasks naturally associated with human intelligence, like speech recognition, decision-making, visual perception, and translating languages.

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Algorithm

An algorithm is a set of instructions for accomplishing a task. If we want a computer to understand how to do something, we need to give it an algorithm. We probably use algorithms in our day-to-day life, the power of the algorithm comes from the fact that computers can follow the steps quickly and precisely. Algorithms are used for data processing, calculations, and automated reasoning. 

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Machine Learning

Machine Learning is one of the widely used algorithms of AI. The learning process involves the enhancement of new declarative knowledge, the advancement of cognitive and motor skills through practice or instruction. Since the beginning of the computer era, researchers and scientists have been trying to implant such abilities in computers. Solving this issue has been, and remains, m most fascinating and challenging long-term goal in AI.

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Deep Learning

Deep learning is a subfield of machine learning; it is one of the most powerful and fastest-growing applications of AI. Deep learning is used to solve problems that are previously considered too complicated and involve a large amount of data. Deep learning occurs through the use of neural networks, which are layered to recognize patterns and complex relationships in data. The application of deep learning requires a vast dataset and mighty computational power to work.

Natural Language Processing

NLP is a method in which computers are made to understand, execute and manipulate human language. To reach this goal, a computer should be able to “understand” a large amount of data – from grammar syntax and rules to various accents and colloquialisms. Whereas a speech recognition system, for example, manual speech becomes audio data, which then turns into text data, a complex process itself. This text data can be implemented in an “intelligent” system for different applications such as controlling devices or translators.

Computer Vision

Computer vision is the science of manipulating or understanding videos and images. It has many applications, comprising augmented reality, autonomous driving, and industrial inspection. The implementation of deep learning for computer vision can be differentiated into many categories: detection, generation, segmentation, and classification, both in videos and images.

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What is it exactly that makes artificial intelligence such an essential and peculiar technology right now?

Artificial intelligence and deep learning expert Andrew Ng probably said it best when he described artificial intelligence as the new electricity. In saying this, he demonstrated his belief that AI will soon power most of our activities in society and business, drastically changing the ways we work and live.
 
I believe that learning how AI works and understanding its implications for our lives is at least as important as learning to read and write. In other words, I recognize that we are now beginning to live in an era of AI, so it’s important to learn as much as we can about it early on.

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While there are many reasons to prioritize learning about AI, here are a few that I believe are most important:

The speed of AI Implementation: 

New AI technologies are being introduced at an incredibly fast pace, and it can be challenging to keep up. At this point, only a handful of people truly understand all of the implications these quickly evolving technologies will have for our world. Naturally, these rapid changes will generate some challenges.

Large tech companies giving priority to AI:

Even Google, a company that used to say that mobile was its priority, has shifted its focus toward AI. Nearly every tech company is heavily investing in AI research and development, which demonstrates the importance that AI, holds for businesses in general.

Lack of Knowledgeable Workers:

Because AI is overgrowing, there is a great need for more data scientists, machine learning experts, and other technical professionals who can build out AI solutions and services. There is also a shortage of other professionals, such as teachers and consultants, to help to explain the implications of the growth of AI, which will, in turn, help businesses and individuals adapt to the new realities.

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Legal Implications Worldwide:

In almost every country, laws and regulations will need to be reviewed and updated to incorporate the new trends of the AI era. There is also a demand for information on the ways that societies can benefit by applying AI to various fields like healthcare and transportation.

Advantages and Opportunities:

People who work for tech companies tend to offer the most positive outlook on the future opportunities that will be afforded by AI. However, outside of that sector, people often have negative impressions about AI tools due to a lack of understanding. Sharing information about the benefits offered by AI will be an essential factor in helping people to feel comfortable with adopting these new technologies. 

In the future, the most productive members of society will work together with AI, forming robot-to-human partnerships, making their endeavors much more efficient. It is important to share knowledge with everyone on how this can be done correctly.

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Collaboration between Private and Public Sectors:

Research and development of AI should not only be taking place in large tech companies. Instead, there needs to be open and robust collaboration internationally, as well as between companies of all sizes, and between the public and private sectors.

Conclusion

I hope that as you read through the topics covered in this article, you will not only become more interested in AI, but will also be challenged to speak more openly and often about it, and perhaps even begin to work with new AI tools for yourself.