Artificial Intelligence vs Machine Learning

What is AI or Artificial Intelligence?

AI or Artificial Intelligence is a term that consists of two words “Artificial” and “Intelligence.” These two terms are enough to give a gist of the entire concept, i.e. an intelligent system that can replicate human intelligence. 

The systems on which Artificial Intelligence is implemented run on algorithms, i.e. the systems use these algorithms with their intelligence and hence do not need programmed software. These systems provide extraordinary outputs for each assigned task and are expected to evolve more, especially at an emotional level, in the times to come. 

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What is ML or Machine Learning?

ML or Machine Learning can be referred to as an application or a subset of Artificial Intelligence. Now, to define Machine Learning, it is the process in which the machine learns on its own, without any programming. It enables the system to improve from experiences and learn automatically from them.

It is an application of Artificial Intelligence that uses mathematical models to help the computer system learn. Also, the system can learn and improve on its own as it continues to experience more and more. 

Understanding the basics of both Artificial Intelligence and Machine Learning, it is now important to know why one should choose any of these.

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Why should you choose Artificial Intelligence and Machine Learning?

Artificial Intelligence and Machine Learning are one of the most booming fields in the technical world today. So, there are a lot of reasons that you can choose them.

Let’s have a look at these reasons one after the another:

• Bright Career
  AI and ML are in great demand today. Every old or new organisation is trying to move toward Artificial Intelligence and Machine Learning as it opens an entirely new pool of opportunities. It enables companies to be well versed with everything going around and most importantly can be implemented in any type of industry, like pharmacy, computer security, finance etc.
• Highly Paid
  If you look towards the job opportunities in the field of AI and ML, you would find ample jobs. The biggest plus here is not the demand in the market for these skills but the average salary that an entry-level AI or a fresher in Machine Learning is higher than several other jobs.
• Important for rapid growth 
  Artificial Intelligence and Machine Learning are important for an organization to sustain itself. As technological advancements are happening at such a rapid rate and digital transformations are extremely common, companies need to adopt AI and ML for their rapid growth.
• Relation between Data Science and Machine Learning 
  Machine Learning is often considered the shadow of Data Science, and that is because of the intricate relationship that they share. Once you begin with both of these, you realise that now you can just not analyse huge amounts of data but can also extract values and draw insights from that data chunk.
• Helps the society
  Not just on an individual or organisational level, Artificial Intelligence and Machine Learning help society as a whole. From healthcare to emergency relief, these two fields enable people to understand the trends that may come forth and how they might impact their work. For example: being informed about adverse weather conditions or analysing a set of data on a huge population. 

Now, when you know why AI and ML are so much in demand, another important segment is to understand how they are different from each other.

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Difference Between Artificial Intelligence & Machine Learning

Above you saw the basics of both, ML and AI, now let’s have a look at the major differences between the two.

• AI which stands for Artificial Intelligence is something that enables a machine/system to act like a human. ML which stands for Machine Learning is something that enables a machine/system to learn from past experiences and doesn’t require programming to do so. 
• The goal of AI is to make computers intelligent or smart so that they can perform tasks and make decisions like humans. The goal of ML is to make computers perform a certain task or give an accurate result concerning learning from the previous data.
• Machine Learning and Deep Learning are datasets of Artificial Intelligence, and hence AI has an extremely wide scope. Machine Learning is a subset of Artificial Intelligence, Deep Learning is a subset of Machine Learning, and hence ML has a limited scope. 
• Now, if you talk with respect to accuracy, Artificial Systems are functioned to achieve a successful run. Machine Learning systems focus on accuracy and patterns. 
• In terms of dealing with this kind of data, AI deals with unstructured, semi-structured, and structured data. Machine Learning doesn’t deal with unstructured data, just structured and semi-structured data. 
• Artificial Intelligence can be divided into three types based on its capabilities:

• Weak AI 
• General AI 
• Strong AI

Machine Learning can also be divided into three types:

• Supervised Learning 
• Unsupervised Learning
• Reinforcement Learning

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Advantages of Artificial Intelligence

• Handle Complex issues 
  AI systems are built to handle complicated issues and that’s just not it, they can handle multiple tasks at the same time without any lags. 
• Handle chunks of data
  Artificial Intelligence systems don’t lag or show any glitches when it comes to handling a huge quantity of data. No matter the scale of an organisation, AI is preferred when it comes to handling big data.
• Imitating human mind
  One of the biggest advantages Artificial Intelligence systems have is their imitation of the human mind. These devices can function as a human and have the intelligence of a human mind. 

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Advantages of Machine Learning

• Pattern Visualisation
  Machine Learning enables the system to visualise patterns and figure out relationships in the data. This enables the system to learn different aspects of that data and the main feature here is that all of this process is automated. 
• Data-Driven Models
  ML works on Data-Driven Models which means if there is data, the system can process that within no time, with utmost efficiency and accuracy. 
• Highly scalable
  Machine Learning systems are highly scalable which enables them to ingest huge chunks of semi-structured and structured data.

Applications of Artificial Intelligence

Artificial Intelligence is being used in several verticals. Every organisation that dreams of growing at a rapid rate is trying to move towards AI and make the most of it. Several complex operations cannot be handled unless you have AI-powered systems.

These systems are used in different fields like they are used in Astronomy to figure out the intricacies of the universe. Then they are used in the field of healthcare, where several complex processes like human cognition and decision making are needed. 

Apart from that, they are used in Businesses when it comes to having an effective roadmap by analysing several business trends and market growth. Similarly, AI can be utilised in the Sales and Marketing domain to understand the market trends and figure out what could be the latest sales pitch.

 Applications of Machine Learning

Machine Learning is one of those things that you would use in your daily life and with the advancements happening every day, now more than ever. There are things that you would think are running on the normal internet, but that’s not true, it is actually Machine Learning at your aid.

Common applications like Image Recognition which is too common these days to identify objects or faces work on ML. Then there’s Speech Recognition when you speak something on the mic and it comes instantly or when you are using the maps and you see Traffic prediction, that is all Machine Learning is doing for you. 

Watch something on a streaming application or shop something online, and you begin to get recommendations, it is again the work of ML. Also, the email spam or email filter option that has become common these days is all powered by Machine Learning. 

Some of the most common examples of Machine Learning include Google Maps, Cortana, Alexa, Google Assistant etc.

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Conclusion

By now, you would know that Artificial Intelligence and Machine Learning may be related to a great extent but they are different. Now, you know that Artificial Intelligence has a wider range as compared to Machine Learning and ML is a subset of AI.

In the process to understand the difference between AI and ML, you first saw their basics and once you were clear with the basics you went on to see how they make a difference in this fast-moving world. After the basics were clear you saw how they are different from each other, even if they are concomitant. 

Once you were able to distinguish between Artificial Intelligence and Machine Learning, you moved on to learn about the advantages that they bring with them. Furthermore, you learnt their applicability and how they impact our daily life. 

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