Artificial intelligence is no more a science fiction concept. Rather it is very much real and unfailingly lets us know its presence. Artificial intelligence has invaded many aspects of human life and without it keeping up with time can become a challenge for the most. As the world shifts towards automation of mundane tasks and eradication of human error from most of the daily operations. Ai research keeps on thriving in accordance with the human urge for more value and fewer errors. New developments in the field are a usual phenomenon these days.
From the very beginning of this century, AI researchers have given us invaluable gifts. And despite all the ethical obstacles artificial intelligence is being accepted by humanity with arms wide open. Today AI research is one of the most funded fields of research and is expected to draw more financial attention in the near future. AI enthusiasts looking towards a career in research but are unsure of the topic in AI might find this article interesting. This article will discuss the most prominent and popular areas of AI research. Enlightening the reader in the process, regarding the opportunities they can avail to being an AI academician.
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Neuromorphic computation
Neuromorphic computation involves microcomputers designed to mimic the human brain in terms of hardware. Just like the components of a brain, these chips perform by forming synapses and regional data exchanges. These processors are the fastest to date, due to their ability to utilize the stored data at will. Data is processed and stored at the same chip, during the same time as it acts like the human brain. Thanks to its enormous capabilities it can sufficiently implement neural networks. Research in this field is spearheaded by companies like Intel and the field is very well funded as well.
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Internet of things
‘Things’ here in the title means gadgets and objects able to connect and communicate with the internet. The internet of things is designed for enabling things to communicate with each other and act with the help of an AI. The Internet of things, if implemented correctly, can affect not just small apartments and offices, it can render entire buildings into smart buildings.
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Recommendation systems
Recommendation systems are almost an integral part of most online services. In areas like e-shopping, dating, e-booking of tickets recommendation systems benefit both the service provider and consumer. The recommendation systems are not easy to build and train. These classes of artificial intelligence require a lot of data in order to learn and act with minimal to no supervision. Marketing ventures are especially benefited by the emergence of these AIs. By assessing one’s buying habits and spending patterns and well trained AI can recommend the right products to the right people. Ensuring the success of a marketing campaign and good sales in the process.
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Computer vision
Computer vision is no longer just an idea. It is achieving miracles in fields like traffic policing and healthcare. Computers do not see and perceive the world around them as we do. But when they are trained to do so, they can act and perform better than human beings in certain areas, like recognition and memorization. The computers can see with the help of cameras and recognize patterns in a picture in order to extract relevant information from the files. In healthcare, the use of computer vision is mostly seen in the case of histological diagnosis. And in the case of traffic policing, Computer vision can detect rogue drivers and cars and assign fines or cases to them.
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Natural language processing
Natural language processing is the ability of machines to understand human spoken and written languages. Additionally, an NLP system can take up the tasks of speech recognition, natural language processing, text detection, and translation of the speech. The most prominent use case of NLP is modern chatbots. These chatbots can interact with human beings unsupervised and figure out the needs and requirements of a user.
Conclusion
Choosing a topic in AI in order to plan a sustainable academic career is somewhat difficult. It is hard to choose from a plethora of options an enthusiast might get while choosing. Funding in all these areas are equally lucrative and there is enough room for diversification. A graduate student can infant get into jobs and non-academic employment instead of pursuing further research. In any case, the career promises are huge and making a decision is all that an enthusiast needs.
