Difference between Artificial Intelligence and Machine Learning
Hello, Guys today I will tell you the difference between Artificial Intelligence and Machine Learning. We all have been hearing about AI and ML but most of us do not know that both of them are different. Let us first know what is ML and AI.
What are AI and ML?
What do you understand by Artificial intelligence, an artificial program created by human to do intelligent stuff which is done by humans? AI is a program written by humans so that it can be implemented into the system, and the system could perform intelligent task like taking decision similar to human. I have written a post on What is artificial intelligence (AI) please refer to that for more information.
What do you understand by ML, is a form of application which learns from experience without being explicitly programmed. ML is a program that reads the data and analyzes the patterns to perform future predictions without human intervention. It is an Algorithms whose performance improves as they are exposed to more data over time
From this, we saw that both of them are going to perform tasks without a human need. ML is a subset of AI.
The Key difference is
| ARTIFICIAL INTELLIGENCE (AI) | MACHINE LEARNING (ML) |
|---|---|
| AI stands for Artificial intelligence, where intelligence is defined as acquiring knowledge and the ability to apply it. | ML stands for Machine Learning which is defined as the acquisition of knowledge or skill |
| The aim is to increase the chance of success and not accuracy. | The aim is to increase accuracy, but it does not care about the success |
| It leads to developing a system to mimic human and to respond in circumstances. | It involves creating self-learning algorithms. |
| The goal is to simulate natural intelligence to solve a complex problem | The goal is to learn from data on certain tasks to maximise the machine’s performance on this task. |
| AI is decision making. | ML allows the system to learn new things from data. |
| AI will go for finding the optimal solution. | ML will go for the only solution for that whether it is optimal or not. |
Some example of AI and ML which will clear where it is used and a proper idea about the concept.
Machine Learning examples
- Google Maps
- Google Search
- Gmail
- PayPal
- Netflix
- Uber
- Siri and Cortana
Artificial Intelligence examples
- Google Self driving car, Tesla autopilot and Audi A7 self-driving car
- Fraud Detection, especially online transaction fraud
- Online customer support, many live chats on the website are done by AI
- You can generate simple articles, using this app Wordsmith software. It is an AI that gives you simple articles that don’t require a lot of syntheses
- Security surveillance, using AI here would improve the security and security algorithms can take input from security cameras and determine whether there may be a threat—if it “sees” a warning sign, it will alert human security officers
- Music and movie recommendation, apps like Netflix and Pandora recommend according to the interest and past usage
You might be wondering some examples are the same in both i.e. is because ML is a subset of AI and without ML you cannot create AI. A machine has to learn first where ML comes to play then only it can do intelligent tasks. I think this would have cleared some doubts in your mind if not free feel to ask a question or do a little search on your own.
Also, read this post about Salesforce Cisco integration tenfold.
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