Exploring the Possibilities of Artificial Intelligence with Examples

what is artificial intelligence with examples

What is artificial intelligence with examples: Developing intelligent machines that can perform tasks for human intelligence to complete.

Here’s a quick timeline of how AI has evolved over the past 60 years since its birth. 1956 – John McCarthy coined the term “artificial intelligence” and hosted the first AI conference.

1969 – Shakey builds the first multi-purpose mobile robot. You can now do things with specific goals instead of just a list of instructions. 1997 – The supercomputer “Deep Blue” is developed and beats the world chess champion in a match. The development of this great computer was a big milestone for IBM.

What is artificial intelligence with examples? The question of which answer is searched by many.
Artificial Intelligence Examples
  • Manufacturing robots.
  • Self-driving cars.
  • Smart assistants.
  • Healthcare management.
  • Automated financial investing.
  • Virtual travel booking agent.
  • Social media monitoring.
  • Marketing chatbots.

2002 – First commercially successful robotic vacuum cleaner is developed. 2005 – 2019 – Currently debuting speech recognition, robotic process automation (RPA), dancing robots, smart homes, and other innovations. Artificial intelligence with examples must be known.

2020 – Baidu released the LinearFold AI algorithm to medical, scientific and medical teams developing vaccines in the early stages of the SARS-CoV-2 pandemic. The algorithm can predict the viral RNA sequence in just 27 seconds. This is 120 times faster than other methods.

Purely reactive

These machines have no memory or data to work with and are dedicated to just one work area. For example, in a game of chess, a machine watches your moves and makes the best decision to win. Purely reactive is also an artificial intelligence with examples

Limited storage

These machines collect historical data and keep adding to their memory. They have sufficient memory and experience to make correct decisions, but their memory is minimal. For example, the machine can suggest restaurants based on recorded location data.\

What is Artificial Intelligence with Examples?

Artificial intelligence is a section of computer science. It aims at building smart machines.

Theory of Mind

This type of AI can understand thoughts and emotions and interact socially. However, machines based on this type have not yet been built. 4. Be confident The Confident Machine is the next generation of these new technologies. You will become intelligent, sentient and conscious. Theory of mind is also an example of artificial intelligence with examples.

How does artificial intelligence work in artificial intelligence with examples?

Simply put, AI systems work by blending large-scale algorithms with intelligent iterative algorithms. This combination enables AI to learn from the patterns and features of the analyzed data. Every time an artificial intelligence system performs a set of data processing, it tests and measures its performance and uses the results to develop additional expertise.

AI implementation method

Let’s consider the following possibilities that describe how to implement AI.

Machine learning in artificial intelligence with examples

Machine learning gives AI the ability to learn. It does this by using algorithms to discover patterns and glean insights from publicly available data.

Deep learning

Deep learning, a subcategory of machine learning, gives AI the ability to mimic the neural networks of the human brain. You can detect patterns, noise, and sources of confusion in your data. Here, we used deep learning to separate different types of images. This engine looks at different features in the photo and distinguishes between them using a process called feature extraction. Based on the characteristics of each photo, the machine classifies photos into different categories, such as B. Landscapes, portraits, etc is artificial intelligence with examples

The image above shows the three main layers of a neural network

input level
hidden level
output layer

Input Level

The image you want to separate is put into the input layer. An arrow is drawn from the image to each point in the input plane. Each white dot in the yellow layer (input layer) is a pixel in the image. These images fill the white dots in the input layer. As you work through this artificial intelligence tutorial, you should have a clear understanding of these three layers.

Hidden level in artificial intelligence with examples

Hidden layers are responsible for mathematical computations and feature extraction on the input. In the image above, the layers shown in orange represent hidden layers, and the lines that appear between these layers are called ‘weights’. They usually represent floats or decimal numbers multiplied by the input layer values. All weights are summed in the hidden layer. A point in the hidden layer represents a value based on the sum of the weights. These values are passed to the next hidden level.

You may be wondering why there are multiple hierarchies. Hidden layers act as an alternative to some extent. The more hidden layers, the more complex the input and generated data. The accuracy of the prediction output usually depends on the number of hidden layers present and the complexity of the incoming data.

Output layer

The output layer will give you a separate photo. Adding all the weights that the layers have entered will determine if the image is portrait or landscape.

Example – airfare forecast

This forecast is based on several factors, including:

airport of departure
destination airport
departure date

Starting with historical data about ticket prices for training machines. Once the machine is trained, share new data that predict costs. Earlier, when we learned about the four types of machines, we talked about machines with memory.

AI programming cognitive skills: learning, reasoning, and self-correction Artificial Intelligence emphasize the three cognitive abilities that the human brain has to some extent: learning, thinking, and self-correction. In the context of AI, we define these as:

Learning: Obtaining information and the rules necessary to use that information. Rationale: Use information rules to draw definite or approximate conclusions. Self-correction: The process of continuously fine-tuning AI algorithms to ensure they provide the most accurate results possible. However, researchers and programmers have extended and elaborated on AI goals as follows:

Logical thinking

AI programs enable computers to perform advanced tasks. On February 10, 1996, IBM’s Deep Blue computer won a chess match against former world champion Garry Kasparov. knowledge representation

Smalltalk is an object-oriented, dynamically typed, reflective programming language designed to underpin the “new world” of computing represented by the “human-computer symbiosis”.

Planning and navigation in artificial intelligence with examples

The process by which a computer gets from point A to point B. A prime example is Google’s self-driving Toyota Prius. natural language processing Set up a computer that can understand and process languages. Sensing Use your computer to interact with the world through sight, hearing, touch, and smell. new intelligence

Intelligence that is not explicitly programmed but that emerges from certain remaining AI capabilities. The vision for this goal is for machines to have emotional intelligence and moral reasoning. Tasks that AI-enabled devices perform include:

voice recognition

object detection
Solve problems and learn from given data
Plan your approach for future testing.

What is Artificial Intelligence: Applications of Artificial Intelligence in artificial
intelligence with examples

Machines and computers affect the way we live and work. Leading companies are continuously introducing revolutionary changes in how they interact with machine learning technology.

British artificial intelligence company DeepMind Technologies was acquired by Google in 2014. The company has developed a neural Turing machine that allows computers to mimic the short-term memory of the human brain.

Google’s self-driving car and Tesla’s autopilot feature are the introductions of AI into the automotive space. Elon Musk, CEO of Tesla Motors, said on Twitter that Tesla will be able to predict where owners want to go by using AI to learn their owners’ patterns and behaviours. suggested.

Additionally, Watson, a Q&A computer system developed by IBM, is designed for use in the medical field. Watson suggests different types of treatments to patients based on their medical history, which has proven to be very helpful.

Some of the most common commercial business applications of AI include:

1. Bank fraud detection

With rich data on fraudulent and non-fraudulent transactions, AI learns to predict whether new transactions are fraudulent.

2. Online customer support

AI is now automating most online customer support and voice messaging systems.

3. Cyber security in artificial intelligence with examples

Using machine learning algorithms and rich sample data, you can use AI to detect anomalies and adapt and respond to threats.

4. virtual assistant

Siri, Cortana, Alexa, and Google now use voice recognition to follow user commands. They collect information, interpret the questions asked, and provide answers through the data obtained. These virtual assistants will gradually improve and personalize the solution based on your preferences.

What is artificial intelligence with examples?

This question has been asked countless times in recent years as AI has become more prevalent in our lives. AI is a broad term that encompasses a variety of technologies and applications.


Simran Bhandari

Simran Bhandari

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