What is artificial intelligence and its uses?

What is Artificial Intelligence? How does AI work, Types and Future of it?

The intelligence demonstrated by machines is known as Artificial Intelligence. Artificial Intelligence has grown to be very popular in today’s world. It is the simulation of natural intelligence in machines that are programmed to learn and mimic the actions of humans. These machines are able to learn with experience and perform human-like tasks. As technologies such as AI continue to grow, they will have a great impact on our quality of life.

Introduction to Artificial Intelligence

The short answer to What is Artificial Intelligence is that it depends on who you ask.
A layman with a fleeting understanding of technology would link it to robots. They’d say Artificial Intelligence is a terminator like-figure that can act and think on its own.
If you ask about artificial intelligence to an AI researcher, (s)he would say that it’s a set of algorithms that can produce results without having to be explicitly instructed to do so. And they would all be right. So to summarise, Artificial Intelligence meaning is:

Artificial Intelligence Definition

An intelligent entity created by humans.
Capable of performing tasks intelligently without being explicitly instructed.
Capable of thinking and acting rationally and humanely.

How do we measure if Artificial Intelligence is acting like a human?

Even if we reach that state where an AI can behave as a human does, how can we be sure it can continue to behave that way? We can base the human-likeness of an AI entity with the:

• Turing Test
• The Cognitive Modelling Approach
• The Law of Thought Approach
• The Rational Agent Approach

Let’s take a detailed look at how these approaches perform:

What is the Turing Test in Artificial Intelligence?

The basis of the Turing Test is that the Artificial Intelligence entity should be able to hold a conversation with a human agent. The human agent ideally should not able to conclude that they are talking to an Artificial Intelligence. To achieve these ends, the AI needs to possess these qualities:

Natural Language Processing to communicate successfully.
Knowledge Representation to act as its memory.
Automated Reasoning to use the stored information to answer questions and draw new conclusions.
Machine Learning to detect patterns and adapt to new circumstances.

Cognitive Modelling Approach
As the name suggests, this approach tries to build an Artificial Intelligence model-based on Human Cognition. To distil the essence of the human mind, there are 3 approaches:

Introspection: observing our thoughts, and building a model based on that
Psychological Experiments: conducting experiments on humans and observing their behaviour
Brain Imaging: Using MRI to observe how the brain functions in different scenarios and replicating that through code.
The Laws of Thought Approach
The Laws of Thought are a large list of logical statements that govern the operation of our mind. The same laws can be codified and applied to artificial intelligence algorithms. The issues with this approach, because solving a problem in principle (strictly according to the laws of thought) and solving them in practice can be quite different, requiring contextual nuances to apply. Also, there are some actions that we take without being 100% certain of an outcome that an algorithm might not be able to replicate if there are too many parameters.

The Rational Agent Approach
A rational agent acts to achieve the best possible outcome in its present circumstances.
According to the Laws of Thought approach, an entity must behave according to the logical statements. But there are some instances, where there is no logical right thing to do, with multiple outcomes involving different outcomes and corresponding compromises. The rational agent approach tries to make the best possible choice in the current circumstances. It means that it’s a much more dynamic and adaptable agent.
Now that we understand how Artificial Intelligence can be designed to act like a human, let’s take a look at how these systems are built.

How Artificial Intelligence (AI) Works?
Building an AI system is a careful process of reverse-engineering human traits and capabilities in a machine, and using it’s computational prowess to surpass what we are capable of.
To understand How Aritificial Intelligence actually works, one needs to deep dive into the various sub domains of Artificial Intelligence and and understand how those domains could be applied into the various fields of the industry.

Machine Learning : ML teaches a machine how to make inferences and decisions based on past experience. It identifies patterns, analyses past data to infer the meaning of these data points to reach a possible conclusion without having to involve human experience. This automation to reach conclusions by evaluating data, saves a human time for businesses and helps them make a better decision.
Deep Learning : Deep Learning ia an ML technique. It teaches a machine to process inputs through layers in order to classify, infer and predict the outcome.
Neural Networks : Neural Networks work on the similar principles as of Human Neural cells. They are a series of algorithms that captures the relationship between various underying variabes and processes the data as a human brain does.
Natural Language Processingc: NLP is a science of reading, understanding, interpreting a language by a machine. Once a machine understands what the user intends to communicate, it responds accordingly.
Computer Vision : Computer vision algorithms tries to understand an image by breaking down an image and studying different parts of the objects. This helps the machine classify and learn from a set of images, to make a better output decision based on previous observations.
Cognitive Computing : Cognitive computing algorithms try to mimic a human brain by anaysing text/speech/images/objects in a manner that a human does and tries to give the desired output.
Artificial Intelligence can be built over a diverse set of components and will function as an amalgamation of:

• Philosophy
• Mathematics
• Economics
• Neuroscience
• Psychology
• Computer Engineering
• Control Theory and Cybernetics
• Linguistics

What are the Types of Artificial Intelligence?
Not all types of AI all the above fields simultaneously. Different Artificial Intelligence entities are built for different purposes, and that’s how they vary. AI can be classified based on Type 1 and Type 2 (Based on functionalities). Here’s a brief introduction the first type.

3 Types of Artificial Intelligence

• Artificial Narrow Intelligence (ANI)
• Artificial General Intelligence (AGI)
• Artificial Super Intelligence (ASI)

What are the Advantages of Artificial Intelligence?

There’s no doubt in the fact that technology has made our life better. From music recommendations, map directions, mobile banking to fraud prevention, AI and other technologies have taken over. There’s a fine line between advancement and destruction. There’s always two sides to a coin, and that is the case with AI as well. Let us take a look at some advantages of Artificial Intelligence-

Advantages of Artificial Intelligence (AI)
Reduction in human error
Available 24×7
Helps in repetitive work
Digital assistance
Faster decisions
Rational Decision Maker
Medical applications
Improves Security
Efficient Communication

Applications of Artificial Intelligence in business?

AI truly has the potential to transform many industries, with a wide range of possible use cases. What all these different industries and use cases have in common, is that they are all data-driven. Since Artificial Intelligence is an efficient data processing system at its core, there’s a lot of potential for optimisation everywhere.

Let’s take a look at the industries where AI is currently shining.

Healthcare:

Administration: AI systems are helping with the routine, day-to-day administrative tasks to minimise human errors and maximise efficiency. Transcriptions of medical notes through NLP and helps structure patient information to make it easier for doctors to read it.

Telemedicine: For non-emergency situations, patients can reach out to a hospital’s AI system to analyse their symptoms, input their vital signs and assess if there’s a need for medical attention. This reduces the workload of medical professionals by bringing only crucial cases to them.

Assisted Diagnosis: Through computer vision and convolutional neural networks, AI is now capable of reading MRI scans to check for tumours and other malignant growths, at an exponentially faster pace than radiologists can, with a considerably lower margin of error.

Robot-assisted surgery: Robotic surgeries have a very minuscule margin-of-error and can consistently perform surgeries round-the-clock without getting exhausted. Since they operate with such a high degree of accuracy, they are less invasive than traditional methods, which potentially reduces the time patients spend in the hospital recovering.

Vital Stats Monitoring: A person’s state of health is an ongoing process, depending on the varying levels of their respective vitals stats. With wearable devices achieving mass-market popularity now, this data is not available on tap, just waiting to be analysed to deliver actionable insights. Since vital signs have the potential to predict health fluctuations even before the patient is aware, there are a lot of live-saving applications here.

E-commerce

Better recommendations: This is usually the first example that people give when asked about business applications of AI, and that’s because it’s an area where AI has delivered great results already. Most large e-commerce players have incorporated Artificial Intelligence to make product recommendations that users might be interested in, which has led to considerable increases in their bottom-lines.

Chatbots: Another famous example, based on the proliferation of Artificial Intelligence chatbots across industries, and every other website we seem to visit. These chatbots are now serving customers in odd-hours and peak hours as well, removing the bottleneck of limited human resources.

Filtering spam and fake reviews: Due to the high volume of reviews that sites like Amazon receive, it would be impossible for human eyes to scan through them to filter out malicious content. Through the power of NLP, Artificial Intelligence can scan these reviews for suspicious activities and filter them out, making for a better buyer experience.

Optimising search: All of the e-commerce depends upon users searching for what they want, and being able to find it. Artificial Intelligence has been optimising search results based on thousands of parameters to ensure that users find the exact product that they are looking for.

Supply-chain: AI is being used to predict demand for different products in different timeframes so that they can manage their stocks to meet the demand.

Human Resources

Building work culture: AI is being used to analyse employee data and place them in the right teams, assign projects based on their competencies, collect feedback about the workplace, and even try to predict if they’re on the verge of quitting their company.

Hiring: With NLP, AI can go through thousands of CV in a matter of seconds, and ascertain if there’s a good fit. This is beneficial because it would be devoid of any human errors or biases, and would considerably reduce the length of hiring cycles.

Robots in AI

The field of robotics has been advancing even before AI became a reality. At this stage, artificial intelligence is helping robotics to innovate faster with efficient robots. Robots in AI have found applications across verticals and industries especially in the manufacturing and packaging industries. Here are a few applications of robots in AI:

Assembly

AI along with advanced vision systems can help in real-time course correction
It also helps robots to learn which path is best for a certain process while its in operation .

Customer Service

AI-enabled robots are being used in a customer service capacity in retail and hospitality industries
These robots leverage Natural Language Processing to interact with customers intelligently and like a human
More these systems interact with humans, more they learn with the help of machine learning
Packaging
AI enables quicker, cheaper, and more accurate packaging
It helps in saving certain motions that a robot is making and constantly refines them, making installing and moving robotic systems easily
Open Source Robotics
Robotic systems today are being sold as open-source systems having AI capabilities.
In this way, users can teach robots to perform custom tasks based on a specific application
Eg: small scale agriculture