Data Science and Artificial Intelligence

Artificial Intelligence For Data Science


Artificial Intelligence (AI) can be described as intelligence unveiled by machines. It is an incredibly exciting and powerful Machine Learning-based technique. The current trends in the field promise that every enterprise will be data driven and will accumulate the capability to access Machine Learning in the cloud to power Artificial Intelligence apps.

Tech giants like Microsoft, Amazon, Google, Intel, IBM, and others are scrupulously investing in R&D as well as in Marketing over a bundle of Cloud and AI. A recent report by Accenture research quotes that the impact of AI in 12 developed economies divulges that, AI could double annual economic growth rates by 2035. The reason being the change in the essence of work and the novel relationship between man and machine. The impact of AI technologies on business is has a probability of spiking up labor productivity up to 40% and let humans efficiently utilize time.

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Recent Trends In Artificial Intelligence

It’s wouldn’t be a mistake to state that Artificial Intelligence will be responsible for a massive transformation in the way people perceive and interact with technology. Machines are smarter than ever before. They perform tasks beyond human expectations and, in many cases, doing a better job of it than humans. So here are a few trends that will see in 2018 and in the years to come.

  • Artificial Intelligence (AI) revenues will see a surge up to $47 billion by 2020, from $8.0 billion last year, as per the International Data Corporation (IDC).
  • In their recent report, Venture Scanner unveils that there are around 1500 AI start-ups with over $9.1 billion in total funding across 73 different countries.
  • By 2018, it is expected that most of the world’s largest companies will exploit intelligent apps to improve customer experience and refine their offers.
  • The Gartner research report for the year 2016 reveals that by 2020, at least 30% of companies globally will use AI in at least one fragment of their sales processes.

Application Of Artificial Intelligence

Artificial intelligence exists in multiple fields which includes medicine, stock trading, robot control, law, Power system stabilizers (PSSs) Design, scientific discovery, and gaming. Nick Bostrom the Swedish Philosopher and a connoisseur in artificial intelligence research say, “A lot of cutting edge AI has flown into general applications, often without being called AI because once something becomes useful enough and common enough it’s not more considered as AI”.

AI technology has become popular than ever before in the 21st century and is a part of various larger systems. According to a survey by BofA Merrill Lynch, the Robots and Artificial Intelligence solutions market will experience gain in terms of revenue up to $153 billion dollars by 2020 – comprising 70 billion dollars for AI-based analytics.

Benefits Of Artificial Intelligence

AI is the purpose of the next-generation workplace. This includes seamless collaboration between enterprise and individuals. Human resources are not made obsolete, but rather, their efforts are reinforced with emerging tech. In fact, AI provides organizations with the luxury of freeing up resources for higher-level tasks.

Following are some of the benefits of AI:

  • AI reduces the time taken to perform a task. It enables multitasking and eases the workload for existing resources.
  • AI completes mundane tasks through automation, leading to increased productivity.
  • Cognitive technologies with AI will help in faster decision-making and perform actions more rapidly.
  • AI augments the capabilities of differently able individuals.
  • There is a mass market for AI and it has the potential to establish itself across industries.

 Role of AI In Data Science

Artificial Intelligence is sneaking into every angle of Data Science. This is because Artificial Intelligence is an incredible asset for handling large amounts of data. Also, as AI is transformational across end-markets from enterprise to consumer platforms and from cybersecurity to robotics. The demand for Data Scientists is growing exponentially. The pace at which AI technology is evolving is creating a need for Data Scientists. Nevertheless, the demand is far ahead of the supply of proficient professionals.

Future Of AI In Data Science

The traditional approach towards Data Science is no longer valid. The gap between the quantity of data that to analyze and scarcity of Data Scientists is huge. Tedious classic methods are both resource and time exhaustive. They take longer to yield results and are time-sensitive. It does require data scientists to set up and monitor initially. Once the initial requests are taken care off by Data Scientists, then algorithms can produce real-time analytics usable by the layman. Thus, Artificial Intelligence will possibly bridge the gap between data production and interpretation in gaining actionable insights.

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Pavithra Vasist

Pavithra Vasist is a Content Writer working with Aeon Learning Pvt Ltd. She was previously working with MetricFox, a marketing outsourcing firm as a Copy Writer. She holds a bachelor's degree in Electrical and Electronics Engineering. Besides writing, she's fascinated with electronic gadgets and mostly spends her spare time drawing or traveling. She resides in Bangalore.

3 Comments

  1. The blog is so helpful for the novice that they are taking more interest in the artificial intelligence. It will be great for the users to know about the best things and interest them to work for it also. It is so helpful for those who are interested in the data science and work on it also.

  2. Thank you for sharing useful information for all the candidates of Datascience Training who want to kick start these career in this field

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