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  • Amruta Bhaskar
  • Jan 21, 2020
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Artificial intelligence (AI) has received increased attention in recent years. Innovation, made possible through the Internet, has brought AI closer to our everyday lives. These advances, alongside an interest in the technology’s potential socio-economic and ethical impacts, brings AI to the forefront of many contemporary debates. Industry investments in AI are rapidly increasing, and governments are trying to understand what the technology could mean for their citizens. In the modern technology landscape, artificial intelligence is divided into two key areas. The first one is general AI, which is based on the concept that a system can handle tasks like speaking and translating, recognizing sounds and objects, performing business or social transactions etc. The other one has applied AI that refers to concepts like driverless cars.




It is a rapidly advancing technology, made possible by the Internet that may soon have significant impacts on our everyday lives. AI traditionally refers to an artificial creation of human-like intelligence that can learn, reason, plan, perceive, or process natural language. These traits allow AI to bring immense socioeconomic opportunities, while also posing ethical and socio-economic challenges.


It is a technology that is already impacting how users interact with and are affected by the Internet. In the near future, its impact is likely to only continue to grow. AI has the potential to vastly change the way that humans interact, not only with the digital world but also with each other, through their work and through other socioeconomic institutions – for better or for worse.


The collection of “Big Data” and the expansion of the Internet of Things (IoT), has made a perfect environment for new AI applications and services to grow. Applications based on AI are already visible in healthcare diagnostics, targeted treatment, transportation, public safety, service robots, education and entertainment, but will be applied in more fields in the coming years. Together with the Internet, AI changes the way we experience the world and has the potential to be a new engine for economic growth.


Working together with AI


Artificial intelligence is not here to replace us. It augments our abilities and makes us better at what we do. Because AI algorithms learn differently than humans, they look at things differently. They can see relationships and patterns that escape us. This human, AI partnership offers many opportunities.

It can:

·         Bring analytics to industries and domains where it’s currently underutilized.

·         Improve the performance of existing analytic technologies, like computer vision and time series analysis.

·         Break down economic barriers, including language and translation barriers.

·         Augment existing abilities and make us better at what we do.

·         Give us better vision, better understanding, better memory and much more.  


Current Uses of AI:


Although artificial intelligence evokes thoughts of science fiction, artificial intelligence already has many uses today, for example:

·         Email filtering: Email services use artificial intelligence to filter incoming emails. Users can train their spam filters by marking emails as “spam”.


·         Personalization: Online services use artificial intelligence to personalize your experience. Services, like Amazon or Netflix, “learn” from your previous purchases and the purchases of other users in order to recommend relevant content for you.


·         Fraud detection: Banks use artificial intelligence to determine if there is strange activity on your account. Unexpected activity, such as foreign transactions, could be flagged by the algorithm.


·         Speech recognition: Applications use artificial intelligence to optimize speech recognition functions. Examples include intelligent personal assistants, e.g. Amazon’s “Alexa” or Apple’s “Siri”.


A real-life example of this is Google’s Search Engine.

Google’s search engine is a product of data science


·         It uses predictive analysis, a system used by artificial intelligence, to deliver intelligent results to the users.


·         For instance, if a person types “best jackets in NY” on Google’s search engine, then the AI collects this information through machine learning.


·         Now, as soon as the person writes these two words in the search tool “best place to buy,” the AI kicks in, and with predictive analysis completes the sentence as “best place to buy jackets in NY” which is the most probable suffix to the query that the user had in mind.


How are Data Science, Machine Learning and Artificial Intelligence related to each other?

For a simpler view on the relation between these technologies, artificial intelligence is applied based on machine learning. And machine learning is a part of data science that draws features from algorithms and statistics to work on the data extracted from and produced by multiple resources. Thus, you can say data science merges together a bunch of algorithms obtained from machine learning to develop a solution, and during the process, lots of ideas from traditional domain expertise, statistics and mathematics are borrowed.





Author: Bharani G R




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