Applications of Data Science, Deep Learning, and Artificial Intelligence

Data science, deep learning, and Artificial Intelligence (AI) have all been subject to much research and consideration in the last decade. The current use of these three forms and an expected increase in their future applicability means that they will correlate with each other to form the basis of a smart society.

To understand the differences between the three and how they correlate with each other, it’s imperative to comprehend what they are and how they work towards creating a more technologically advanced society.

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Artificial Intelligence

The term “AI” is used so often nowadays that we have a basic understanding of what it means: a computer’s ability to perform tasks such as visual perception, speech recognition, decision-making, and language translation. AI has progressed rapidly over the last few years, but it is still nowhere near matching the vast dimensions of human intelligence. Humans make quick use of all the data around them and can use what they have stored in their minds to make decisions. However, AI does not yet boast such abilities; instead, it is using huge chunks of data to clear its objectives. This ultimately means that AI might require huge chunks of data for doing something as simple as editing text. 

Also Read: Understanding Artificial Intelligence

Data Science

Data science is much more than just simple machine learning. Data here may not have been obtained through a machine, and it may not even be for learning purposes. Put, data science tends to cover the whole spectrum of data processing as we know it. Data science is not just related to the statistical aspect of the process, but it feeds the process and derives benefits from it through data engineering. Data engineers and data scientists have a huge role to play in propelling AI forward.

Deep Learning 

Deep learning is machine learning’s most powerful technique for making the future happen. Much like the neurons in our brains, deep learning is the connection or the powerhouse present between data science and AI. Both machine learning and its subtype, deep learning, incorporate the process of learning from the data over time. While it is not the only thing connecting the two, deep learning is a type of machine learning that works best to strengthen the process of AI and data science. Deep learning can be defined as a machine learning technique that endeavors to teach computer systems things that come naturally to humans. For example, we can naturally interpret what a stop sign on the road means, but for a machine to locate this sign and interpret it, it needs a lot of learning and implementation. This stage of learning is called deep learning. Once we understand the concepts behind deep learning, we'll understand that it is indeed deep learning that shapes the reality behind driverless cars and voice control that we have become accustomed to. 

Also Read: What is Deep Learning?

Broad Applications of Deep Learning, Data Science, and AI 

The use of deep learning, data science, and AI in tandem has opened the door for myriad opportunities. AI has a significant role to play in shaping the benefits that we may enjoy in the future. 

Here are some of today’s technologies and services that use deep learning, data science, and AI. 

  • Expert Systems

    Watson by IBM is a perfect example of how expert systems can benefit from the collaboration between deep learning, data science, and AI. The computer, which is powered by AI, can collect, absorb, and process data much quicker than humans. Watson can not only display a solution quickly, but it can also diagnose cancer with an unbelievable accuracy of 90 percent due to its vast knowledge. In contrast, well-trained doctors know only around 20 percent of the updates present in the diagnosis. 
  • Speech Recognition

    Thanks to the use of AI and numerous endeavors by smartphone manufacturers, you can ask speech recognition software to locate the nearest ice-cream shop or order pizza, without typing a word. It is the creation of artificial neural networks that enforces the understanding computers have of what you say. It takes exhaustive machine learning to do this through AI. 
  • Google

    Google is pleased to have made use of enhanced deep learning and data science algorithms that make sure to provide users with content deemed relevant for them. The search engine uses machine learning algorithms to find out a plethora of data regarding what people are searching for and combs through more than a billion pages to rank the ones that are best for you first. All of this is done within the matter of microseconds. Amazing, right? 
  • Robotics

    A lettuce production company by the name of Spread has revealed its plans to equip robots for handling affairs within the farms. By harvesting 30,000 lettuce heads every day, robots will drastically increase efficiency. The processors within these robots have been fed a high plethora of data regarding the process it takes to harvest lettuce. Not only will this AI revolution increase efficiency, but it will also open doors to new possibilities. 

You can learn more about the implementation of AI, deep learning, and data science here

About the Author

Ronald Van LoonRonald Van Loon

Named by Onalytica as the world's #1 influencer in Data and Analytics, Automation, and the Future Economy (Tech), Ronald is one of the top thought leaders in Data Science and Digital Transformation. He’s a popular keynote speaker and an author for numerous leading Big Data & Data Science websites.

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