Learn AI. Artificial Intelligence Tutorial for Beginners.
What is AI or Artificial Intelligence?
In short, we can understand the term Artificial Intelligence.
A machine with the ability to perform cognitive functions such as perceiving, learning, reasoning and solve problems is deemed to hold artificial intelligence.
Artificial intelligence exists when a machine has the cognitive ability. The benchmark for AI is the human level concerning reasoning, speech, and vision.
Introduction to AI Levels.
Basically, A.I has 3 main types of Artificial Intelligence to make sure easy for beginners to understand and also working areas.
- Narrow AI. Or Artificial Weak/Narrow Intelligence. A.N.I.
- General AI. Or Artificial General Intelligence A.G.I.
- Strong AI. or Artificial Strong Intelligence A.S.I.
Definitions and examples.
- Narrow/Weak AI: Artificial intelligence is said to be narrow when the machine can perform a specific task better than a human. The current research of AI.
- General AI: An artificial intelligence reaches the general state when it can perform any intellectual task with the same accuracy level as a human would.
- Strong AI: An AI is strong when it can beat humans in many tasks.
A.N.I or Narrow A.I Example.
- Rankbrain by Google / Google Search
- Siri by Apple, Alexa by Amazon, Cortana by Microsoft and other virtual assistants
- IBM’s Watson
- Image / facial recognition software
- Disease mapping and prediction tools
- Manufacturing and drone robots
- Email spam filters / social media monitoring tools for dangerous content
- Entertainment or marketing content recommendations based on watch/listen/purchase behavior
- Self-driving cars
Nowadays, AI is used in almost all industries, giving a technological edge to all companies integrating AI at scale.
According to McKinsey.
AI has the potential to create 600 billion dollars of value in retail, bring 50 percent more incremental value in banking compared with other analytics techniques. In transport and logistic, the potential revenue jump is 89 percent more.
A Brief History of Artificial Intelligence.
Artificial intelligence is a buzzword today, although this term is not new. In 1956,
A group of avant-garde experts from different backgrounds decided to organize a summer research project on AI.
Four bright minds led the project; John McCarthy (Dartmouth College), Marvin Minsky (Harvard University), Nathaniel Rochester (IBM), and Claude Shannon (Bell Telephone Laboratories).
The proposal of the summits included.
- Automatic Computers.
- How Can a Computer Be Programmed to Use a Language?
- Neuron Networks.
It led to the idea that intelligent computers can be created. A new era began, full of hope – Artificial intelligence.
Type of Artificial Intelligence
Artificial intelligence can be divided into three subfields:
- Artificial intelligence.
- Machine learning.
- Deep learning.
Machine learning is the art of the study of algorithms that learn from examples and experiences.
Machine learning is based on the idea that there exist some patterns in the data that were identified and used for future predictions.
The difference from hardcoding rules is that the machine learns on its own to find such rules.
Deep learning is a sub-field of machine learning. Deep learning does not mean the machine learns more in-depth knowledge; it means the machine uses different layers to learn from the data.
The depth of the model is represented by the number of layers in the model. For instance, the Google LeNet model for image recognition counts 22 layers.
In deep learning, the learning phase is done through a neural network. A neural network is an architecture where the layers are stacked on top of each other.
AI vs. Machine Learning.
Most of our smartphones, daily device or even the internet use A.I.
Very often, AI and machine learning are used interchangeably by big companies that want to announce their latest innovation.
However, Machine learning and AI are different in some ways.
AI- is the science of training machines to perform human tasks.
The term was invented in the 1950s when scientists began exploring how computers could solve problems on their own.
Where is AI used? Examples
AI has broad applications-
- A.I is used to reduce or avoid the repetitive task. For instance, AI can repeat a task continuously, without fatigue.
- In fact, AI never rests, and it is indifferent to the task to carry out
- A.I improve an existing product. Before the age of machine learning, core products were building upon hard-code rule.
- Firms introduced A.I to enhance the functionality of the product rather than starting from scratch to design new products. You can think of a Facebook image.
- A few years ago, you had to tag your friends manually. Nowadays, with the help of AI, Facebook gives you a friend’s recommendation.
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