What is Artificial Intelligence: Types, History, and Future

Artificial intelligence (AI) is currently one of the hottest buzzwords in tech and with good reason. The last few years have seen several innovations and advancements that have previously been solely in the realm of science fiction slowly transform into reality.

Experts regard artificial intelligence as a factor of production, which has the potential to introduce new sources of growth and change the way work is done across industries. For instance, this PWC article predicts that AI could potentially contribute $15.7 trillion to the global economy by 2035. China and the United States are primed to benefit the most from the coming AI boom, accounting for nearly 70% of the global impact.This Simplilearn tutorial provides an overview of AI, including how it works, its pros and cons, its applications, certifications, and why it’s a good field to master.

What Is Artificial Intelligence?

Artificial Intelligence is a method of making a computer, a computer-controlled robot, or a software think intelligently like the human mind. AI is accomplished by studying the patterns of the human brain and by analyzing the cognitive process. The outcome of these studies develops intelligent software and systems.

A Brief History of Artificial Intelligence

Here’s a brief timeline of the past six decades of how AI evolved from its inception.

1956 - John McCarthy coined the term ‘artificial intelligence’ and had the first AI conference.

1969 - Shakey was the first general-purpose mobile robot built. It is now able to do things with a purpose vs. just a list of instructions.

1997 - Supercomputer ‘Deep Blue’ was designed, and it defeated the world champion chess player in a match. It was a massive milestone by IBM to create this large computer.

2002 - The first commercially successful robotic vacuum cleaner was created.

2005 - 2019 - Today, we have speech recognition, robotic process automation (RPA), a dancing robot, smart homes, and other innovations make their debut.

2020 - Baidu releases the LinearFold AI algorithm to medical and scientific and medical teams developing a vaccine during the early stages of the SARS-CoV-2 (COVID-19) pandemic. The algorithm can predict the RNA sequence of the virus in only 27 seconds, which is 120 times faster than other methods.

Types of Artificial Intelligence

Below are the various types of AI:

1. Purely Reactive

These machines do not have any memory or data to work with, specializing in just one field of work. For example, in a chess game, the machine observes the moves and makes the best possible decision to win.

2. Limited Memory

These machines collect previous data and continue adding it to their memory. They have enough memory or experience to make proper decisions, but memory is minimal. For example, this machine can suggest a restaurant based on the location data that has been gathered.

3. Theory of Mind

This kind of AI can understand thoughts and emotions, as well as interact socially. However, a machine based on this type is yet to be built.

4. Self-Aware

Self-aware machines are the future generation of these new technologies. They will be intelligent, sentient, and conscious.

How Does Artificial Intelligence Work?

Put simply, AI systems work by merging large with intelligent, iterative processing algorithms. This combination allows AI to learn from patterns and features in the analyzed data. Each time an Artificial Intelligence system performs a round of data processing, it tests and measures its performance and uses the results to develop additional expertise.

Ways of Implementing AI

Let’s explore the following ways that explain how we can implement AI:

Machine Learning

It is machine learning that gives AI the ability to learn. This is done by using algorithms to discover patterns and generate insights from the data they are exposed to.

Deep Learning

Deep learning, which is a subcategory of machine learning, provides AI with the ability to mimic a human brain’s neural network. It can make sense of patterns, noise, and sources of confusion in the data.

Consider an image shown below:Here we segregated the various kinds of images using deep learning. The machine goes through various features of photographs and distinguishes them with a process called feature extraction. Based on the features of each photo, the machine segregates them into different categories, such as landscape, portrait, or others.

Let us understand how deep learning works.

Consider an image shown below:

The above image depicts the three main layers of a neural network:

Input Layer

Hidden Layer

Output Layer

Input Layer

The images that we want to segregate go into the input layer. Arrows are drawn from the image on to the individual dots of the input layer. Each of the white dots in the yellow layer (input layer) are a pixel in the picture. These images fill the white dots in the input layer.

We should have a clear idea of these three layers while going through this artificial intelligence tutorial.

Hidden Layer

The hidden layers are responsible for all the mathematical computations or feature extraction on our inputs. In the above image, the layers shown in orange represent the hidden layers. The lines that are seen between these layers are called ‘weights’. Each one of them usually represents a float number, or a decimal number, which is multiplied by the value in the input layer. All the weights add up in the hidden layer. The dots in the hidden layer represent a value based on the sum of the weights. These values are then passed to the next hidden layer.

You may be wondering why there are multiple layers. The hidden layers function as alternatives to some degree. The more the hidden layers are, the more complex the data that goes in and what can be produced. The accuracy of the predicted output generally depends on the number of hidden layers present and the complexity of the data going in.Output Layer

The output layer gives us segregated photos. Once the layer adds up all these weights being fed in, it'll determine if the picture is a portrait or a landscape.

Example - Predicting Airfare Costs

This prediction is based on various factors, including:

Airline

Origin airport

Destination airport

Departure date

We begin with some historical data on ticket prices to train the machine. Once our machine is trained, we share new data that will predict the costs. Earlier, when we learned about four kinds of machines, we discussed machines with memory. Here, we talk about the memory only, and how it understands a pattern in the data and uses it to make predictions for the new prices as shown below:AI Programming Cognitive Skills: Learning, Reasoning and Self-Correction

Artificial Intelligence emphasizes three cognitive skills of learning, reasoning, and self-correction, skills that the human brain possess to one degree or another. We define these in the context of AI as:

Learning: The acquisition of information and the rules needed to use that information.

Reasoning: Using the information rules to reach definite or approximate conclusions.

Self-Correction: The process of continually fine-tuning AI algorithms and ensure that they offer the most accurate results they can.

However, researchers and programmers have extended and elaborated the goals of AI to the following:

Logical Reasoning

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

Knowledge Representation

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

Planning and Navigation

The process of enabling a computer to get from point A to point B. A prime example of this is Google’s self-driving Toyota Prius.

Natural Language Processing

Set up computers that can understand and process language.

Perception

Use computers to interact with the world through sight, hearing, touch, and smell.

Emergent Intelligence

Intelligence that is not explicitly programmed, but emerges from the rest of the specific AI features. The vision for this goal is to have machines exhibit emotional intelligence and moral reasoning.

Some of the tasks performed by AI-enabled devices include:

Speech recognition

Object detection

Solve problems and learn from the given data

Plan an approach for future tests to be done

What is Artificial Intelligence: Advantages and Disadvantages of AI

Artificial intelligence has its pluses and minuses, much like any other concept or innovation. Here’s a quick rundown of some pros and cons.

Pros

It reduces human error

It never sleeps, so it’s available 24x7

It never gets bored, so it easily handles repetitive tasks

It’s fast

Cons

It’s costly to implement

It can’t duplicate human creativity

It will definitely replace some jobs, leading to unemployment

People can become overly reliant on it

Let us continue this article on What is Artificial Intelligence by discussing the applications of AI.

What is Artificial Intelligence: Applications of Artificial Intelligence

Machines and computers affect how we live and work. Top companies are continually rolling out revolutionary changes to how we interact with machine-learning technology.

DeepMind Technologies, a British artificial intelligence company, was acquired by Google in 2014. The company created a Neural Turing Machine, allowing computers to mimic the short-term memory of the human brain.

Google’s driverless cars and Tesla’s Autopilot features are the introductions of AI into the automotive sector. Elon Musk, CEO of Tesla Motors, has suggested via Twitter that Teslas will have the ability to predict the destination that their owners want to go via learning their pattern or behavior via AI.

Furthermore, Watson, a question-answering computer system developed by IBM, is designed for use in the medical field. Watson suggests various kinds of treatment for patients based on their medical history and has proven to be very useful.

Some of the more common commercial business uses of AI are:

1. Banking Fraud Detection

From extensive data consisting of fraudulent and non-fraudulent transactions, the AI learns to predict if a new transaction is fraudulent or not.

2. Online Customer Support

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

3. Cyber Security

Using machine learning algorithms and ample sample data, AI can be used to detect anomalies and adapt and respond to threats.

4. Virtual Assistants

Siri, Cortana, Alexa, and Google now use voice recognition to follow the user's commands. They collect information, interpret what is being asked, and supply the answer via fetched data. These virtual assistants gradually improve and personalize solutions based on user preferences.Different Artificial Intelligence Certifications

1. Introduction to Artificial Intelligence Course

Simplilearn's Artificial Intelligence basics program is designed to help learners decode the mystery of artificial intelligence and its business applications. The course provides an overview of AI concepts and workflows, machine learning and deep learning, and performance metrics. You’ll learn the difference between supervised, unsupervised and reinforcement learning, be exposed to use cases, and see how clustering and classification algorithms help identify AI business applications.

2. Machine Learning Course

Simplilearn’s Machine Learning Course will make you an expert in machine learning, a form of artificial intelligence that automates data analysis to enable computers to learn and adapt through experience to do specific tasks without explicit programming. You'll master machine learning concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms and prepare you for the role of a Machine Learning Engineer.

3. Artificial Intelligence Engineer Master’s Program

Simplilearn's Masters in AI, in collaboration with IBM, gives training on the skills required for a successful career in AI. Throughout this exclusive training program, you'll master Deep Learning, Machine Learning, and the programming languages required to excel in this domain and kick-start your career in Artificial Intelligence.

4. Simplilearn’s Artificial Intelligence (AI) Capstone Project

Simplilearn’s Artificial Intelligence (AI) Capstone project will give you an opportunity to implement the skills you learned in the masters of AI. With dedicated mentoring sessions, you’ll know how to solve a real industry-aligned problem. You'll learn various AI-based supervised and unsupervised techniques like Regression, Multinomial Naïve Bayes, SVM, Tree-based algorithms, NLP, etc. The project is the final step in the learning path and will help you to showcase your expertise to employers.

Reasons to Get an Artificial Intelligence Certification: The Key Takeaways

Here are the top reasons why you should get a certification in AI if you’re looking to join this exciting and growing field:

1. Demand for Certified AI Professionals will Continue to Grow

The McKinsey Global Institute predicts that approximately 70 percent of businesses will be using at least one type of Artificial Intelligence technology by 2030, and about half of all big companies will embed a full range of Artificial Intelligence technology in their processes. AI will help companies offer customized solutions and instructions to employees in real-time. Therefore, the demand for professionals with skills in emerging technologies like AI will only continue to grow.

2. New and Unconventional Career Paths

A Future of Jobs Report released by the World Economic Forum in 2020 predicts that 85 million jobs will be lost to automation by 2025. However, it goes on to say that 97 new positions and roles will be created as industries figure out the balance between machines and humans.

Because of AI, new skill sets are required in the workforce, leading to new job opportunities. Some of the top AI roles include:

AI/machine learning researcher - Researching to find improvements to machine learning algorithms.

AI software development, program management, and testing - Developing systems and infrastructure that can apply machine learning to an input data set.

Data mining and analysis - Deep investigation of abundant data sources, often creating and training systems to recognize patterns.

Machine learning applications - Applying machine learning or AI framework to a specific problem in a different domain and for example, applying machine learning to gesture recognition, ad analysis, or fraud detection

3. Improve Your Earning Potential

Many of the top tech enterprises are investing in hiring talent with AI knowledge. The average Artificial Intelligence Engineer can earn $164,000 per year, and AI certification is a step in the right direction for enhancing your earning potential and becoming more marketable. Start your AI journey with our AI & Machine Learning Bootcamp.

4. Higher Chances of a Discussion

If you are looking to join the AI industry, then becoming knowledgeable in Artificial Intelligence is just the first step; next, you need verifiable credentials. Certification earned after pursuing Simplilearn’s Machine Learning Course will help you reach the interview stage as you’ll possess skills that many people in the market do not. Certification will help convince employers that you have the right skills and expertise for a job, making you a valuable candidate.

Artificial Intelligence is emerging as the next big thing in technology. Organizations are adopting AI and budgeting for certified professionals in the field, thus the growing demand for trained and certified professionals. As this emerging field continues to grow, it will have an impact on everyday life and lead to considerable implications for many industries.

FAQs

1. Where is AI used?

Artificial intelligence is frequently utilized to present individuals with personalized suggestions based on their prior searches and purchases and other online behavior. AI is extremely crucial in commerce, such as product optimization, inventory planning, and logistics. Machine learning, cybersecurity, customer relationship management, internet searches, and personal assistants are some of the most common applications of AI. Voice assistants, picture recognition for face unlocking in cellphones, and ML-based financial fraud detection are all examples of AI software that is now in use.

2. What are the social benefits of AI?

Artificial intelligence has the potential to significantly increase workplace efficiency and supplement the job that people can undertake. When AI takes over monotonous or risky duties, it frees up the human workforce to focus on tasks that need creativity and empathy, among other things. AI reduces the time required to complete a task. AI allows for the performance of previously complicated activities at a low cost. AI functions continuously and without interruption, with no downtime. AI improves the capacities of people with disabilities.

3. What Are the 4 Types of AI?

The current categorization system categorizes AI into four basic categories: reactive, theory of mind, limited memory, and self-aware.

4. How Is AI Used Today?

Machines today can learn from experience, adapt to new inputs, and even perform human-like tasks with help from artificial intelligence (AI). Artificial intelligence examples today, from chess-playing computers to self-driving cars, are heavily based on deep learning and natural language processing. There are several examples of AI software in use in daily life, including voice assistants, face recognition for unlocking mobile phones and machine learning-based financial fraud detection. AI software is typically obtained by downloading AI-capable software from an internet marketplace, with no additional hardware required.

5. How Is AI Used in Healthcare?

NLP tools that can comprehend and categorize clinical documents are frequent use by artificial intelligence in healthcare. NLP systems can evaluate unstructured clinical notes on patients, providing remarkable insight into quality understanding, improved methodologies, and better patient outcomes.

6. How is AI helping in our life?

AI and ML-powered software and gadgets mimic human brain processes to assist society in advancing with the digital revolution. AI systems perceive their environment, deal with what they observe, resolve difficulties, and take action to help with duties to make daily living easier. People check their social media accounts on a frequent basis, including Facebook, Twitter, Instagram, and other sites. AI is not only customizing your feeds behind the scenes, but it is also recognizing and deleting bogus news. So, AI is assisting you in your daily life.

7. Why is AI needed?

As a result of artificial intelligence technology, the software is capable of performing human functions, such as planning, reasoning, communication, and perception, more effectively, efficiently, and at a lower cost. Artificial intelligence speeds up, improves precision, and increases the efficacy of human endeavors. To predict fraudulent transactions, implement rapid and accurate credit scoring, and automate labor-intensive tasks in data administration, financial institutions can use artificial intelligence approaches.

8. What is artificial intelligence with examples?

Artificial intelligence involves replicating human intellectual processes through machines, especially computers. There are many applications of AI, such as expert systems, natural language processing, speech recognition, and machine vision.

9. Is AI dangerous?

Aside from planning for a future with super-intelligent computers, artificial intelligence in its current state might already offer problems.

10. What are the advantages of AI?

The advantages of AI include reducing the time it takes to complete a task, reducing the cost of previously done activities, continuously and without interruption, with no downtime, and improving the capacities of people with disabilities.

11. Is artificial intelligence the future?

Artificial intelligence plays a significant role in virtually every field of human endeavor. It is already the primary driver of developing technologies such as big data, robots, and the Internet of Things, and it will continue to be a technical pioneer in the foreseeable future.

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