IF MACHINES ARE INTELLIGENT, HOW DO THEY ACTUALLY LEARN? | BRIEF DESCRIPTION ON MACHINE LEARNING

Knowasis

The purpose of this video is to provide:
1. A brief description of how Machines learn
2. An Example of a Chatbot application

In the previous video, we discussed the fundamentals of artificial intelligence and how it impacts our daily life. Now, let’s discuss an important question that many people have but are reluctant to bring up.
Can Machines Think? is a question posed by Alan Turing that, in my opinion, continues to drive the advancement of AI today. Actually, his test’s idea is essential in determining whether a robot is capable of reasoning like a human. You have three participants in the test. A human at one end asking a series of questions while being unable to see the his participants. On the other end you have another human and a trained machine. The individual will ask the respondents questions about a particular topic while keeping to a specified format and context. And determine which respondent was a human and which was the machine after a series of questions. If the examiner cannot distinctively identify the human from the machine, the machine is said to have passed the intelligence test

We are all aware that various layers of artificial intelligence are used by the applications we use today, such as Google Maps, Siri, and weather apps, to provide us with the best results. We established previously that these intelligent agents/machines are taught by human experts.

There are three components to effectively train any machine
1. Input: The inputs may include text, numbers, photos, or other types of organized, unstructured, or semi-structured data. E.g. You want to create a website where users can upload photos of their dogs. To prevent anyone from attempting to post a picture of a cat, you will require an agent capable of identifying any alternate image. I think I use dogs and cats as examples far too frequently. This implies that in order for the machine to accurately identify and categorize your images and recognize when a wrong image is being uploaded, you will have to train it by showing it several images of dogs.

2. The second component is the Expected output.

3. Learning Algorithm: This is a set of instructions used for training the machine to carry out the specified task
It was important to explain this a bit to give you an understanding of how these machines are created. An example is a Chatbot; This is a machine designed to simulate conversation with human users. Following the explanation, you should now know they have been fed with literally thousands or millions of text data questions and responses.

The amusing aspect is that Josh Pigford trained this bot to respond in a slightly disrespectful manner. Given that it is a financial chatbot that frequently provides ridiculous responses, one shouldn’t take it seriously. I’ll say it truly: DO NOT TAKE IT SERIOUSLY OR LISTEN TO ITS FINANCIAL ADVICE PLEASE. You are welcome to investigate and test it out on your own if you choose. Enjoy a little of my dialogue with this robot.

You can also try it out yourself. In my next video, I will be showing this time a bot that I think will do exploit. This one gives accurate answers, can generate stories, blog post, and business ideas. I have to say I was impressed testing it out. You want to put on your notification for that one. Don’t forget to like, subscribe, and share your comment. See you soon.

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CREDITS
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MUSIC
Downloaded from Pixabay: https://pixabay.com/music
Joker Boy by Serge Quadrado at Taketones.com
Education by Audio Coffee
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IMAGES AND VIDEOS
UNSPLASH: https://unsplash.com/
PIXABAY: https://pixabay.com/
PEXELS: https://www.pexels.com/
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LINKS
https://www.producthunt.com/products/rupert?utm_source=badge-featured&utm_medium=badge#rupertgrint
https://www.ibm.com/in-en/cloud/learn/machine-learning#toc-how-machin-NoVMSZI_
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