What is Artificial Intelligence?
The field of artificial intelligence attempts to understand various intelligent entities which are generally related to humans. It is capable enough to calculate , perceive relations and analogies , learn from experiences , store and retrieve information from memory , solve problems and comprehend complex ideas. With various advancements , the sole objective of AI is to mimic the human mind by incorporating Problem-Solving, Decision-Making, and Reasoning abilities into machines.
Types of Artificial Intelligence
This field of study is further divided into three following types:
1. Artificial Narrow Intelligence(ANI):
This is the simplest form of AI that allows the system to solve one single problem at a time with maximum efficiency. They have basic features that enable a user to solve a specific task but in a very controlled environment.
2. Artificial General Intelligence(AGI):
This type primarily focuses on building a machine with a human based intelligence encompassing a variety of features like Language Processing, Image processing, and ability to compute complex to easy problems.
3. Artificial Super Intelligence(ASI):
It is the most advanced level of Artificial Intelligence. According to this theory this field will surpass human thinking capability in the near future by regular evolution of features that would be capable enough to perform multiple tasks at once. Although AGI is still a theory and is mostly likely to be achieved in the next few years.
Purpose of Artificial Intelligence
The main objective of this terminology is to aid human capabilities and cater their needs in the technical sector by predicting the vast results that the human brain fails to comprehend. AI has been a great boon to mankind so far and has actually managed to reduce various problems of humans , bringing them ease with its advanced features. Artificial Intelligence in Data Science is also an advancement in the technical sector that has similar working and features.
What is Data Science?
Now , moving further let us understand the working of Data science. Data is considered as the fundamental unit of almost all organizations. It is the most important raw material of a company that has to be processed efficiently to unlock the vast benefits of any technology applied . The study of Data, its source , and its segregation from other useless stuff is termed as Data Science. In simpler terms , when we study the vast data which is fed into a system to extract valuable information for its further processing , keeping in mind the goals of the business is what is defined as Data Science.
Life-Cycle of Data Science:
There are certain set methods that are followed while dealing with data . In order to achieve maximum efficiency these methods are defined in advance and are known as the Life Cycle of Data Science. These include:
- Capture the Data
- Maintain the Data
- Process the Data
- Analyze the data
- Communicate the Results
Purpose of Data Science:
The primary objective of AI Data Science is to find patterns within the data. As the quantity of data is increasing day by day and handling it becomes difficult , this is when this field of Data Science came into existence . It is used to gain insights and understand the repeating patterns in the data using several parameters and techniques. The existing data and data stored primitively in the system are analyzed together to predict future trends in the business.
It is further used in several other fields like:
- Transport: The study of consumption of fuel , intelligent features of self driven cars , proper processing and monitoring of the driving patterns can all be understood by keeping Data Science as the base of these technologies. The use is not only restricted to the vehicle , but is also extensively used in GPS and other mapping tools.
- Banking and data security: Data Science helps to reduce data redundancy , this enables Banks to make changes in real time and use the resource efficiently. Not only this , but it also includes proper risk management and helps to keep the data secure.
- Understanding market trends: It allows us to monitor various patterns in the data that helps to predict future trends and helps in optimizing the quality and capacity of data.
Artificial Intelligence in Data Science: Understanding the Relationship:
The prior information of both the fields which we have discussed in this article will help us to understand the interdependency of both these technologies.
Data Science and Artificial Intelligence are extensively co-related. As we all are aware that data is the most basic unit that is fed into the system. Data which is entered in the system undergoes various steps that include Extraction, Transformation, and Storing of data. All these processes collectively are known as Data Engineering. Artificial Intelligence and its various concepts are applied in Data Science once the data is processed .
Role of Artificial Intelligence in Data Science:
As we have abundant data to process and annalyse application Data Science alone can be quite a difficult task , therefore Artificial Intelligence is used to aid and fasten the entire process.Â
AI in Data Science plays a major role in the enhancement of the capabilities of Data Science. In simple language we can say that Data Science aims at discovering hidden trends in large amounts of data whereas AI in Data Science manages the data autonomously using intelligent features . The correlation can be further explained by taking examples of :
- Â Â Â Machine Learning: It is a terminology that is created by combining features of both AI in Data Science. In this version a set amount of data is fed into the system to predict the probability of future trends. Various Machine Learning algorithms like Regression and Classification are used for the same.
- Â Â Â Understanding the role: Artificial Intelligence is a tool for Data Science that helps to enhance the capabilities of the basic features of data science . Both these technologies when used simultaneously aim to produce efficient and most optimum results.
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FAQs on AI and Data Science
What is an AI Assistant?
An AI assistant is a virtual assistant that are basically software programs that help you ease your daily tasks such as showing weather reports, creating reminders, setting alarms by simply responding to your commands . These are powered by machine learning that can respond to you and provide information , perform tasks as per your requests.
Compare the goals of AI and Data science. Are these similar?
The goals are based on similar grounds i.e ease out human efforts but both these technologies work on separate principles.The main goal of Data Science is to analyze data and similar patterns to find a suitable problem statement, keeping in mind the business requirements whereas Artificial Intelligence’s aims to to imitate human intelligence using computers so that machines can make smart decisions.
What challenges do data scientists face?
Data scientists face several challenges like Balancing Data Security and Accessibility, handling large volumes of data , maintaining quality of data , difficulty in Ensuring Clean and Accurate Data etc.
What are the concerns related to data security?
Data security is a critical concern for organizations handling sensitive and confidential information like banks , hospitals etc. With advancement in methods of data storage like cloud computing , the majority of data is present on a shared common platform that can be accessed by several users including illegitimate users that might exploit the data . This is one of the major concerns related to data privacy.
