What really is Artificial Intelligence?

If you have been wondering what Artificial Intelligence is and it’s application, in this article, I attempt to break down what AI is and it’s uses.

Artificial intelligence (AI) is the ability of a digital computer or computer controlled robot to perform tasks commonly associated with intelligent beings. Sometimes called machine intelligence; AI is intelligence demonstrated by machines.

Artificial intelligence is really just a program or machine’s ability to learn and think for itself in such a way that it is capable of developing skills at it practices and gains experience. Its purpose is none other than supporting and enhancing human activities.

There are a number of different forms of learning as applied to artificial intelligence. The simplest is by trial and error. For example, a simple computer program for solving mate-in-one chess problems might try moves at random until mate is found. The program might then store the solution with the position so that the next time the computer encountered the same position it would recall the solution.

This simple memorizing of individual items and procedures — known as rote learning — is relatively easy to implement on a computer. More challenging is the problem of implementing what is called generalization. Generalization involves applying past experience to analogous new situations. For example, a program that learns the past tense of regular English verbs by rote will not be able to produce the past tense of a word such as jump unless it previously had been presented with jumped, whereas a program that is able to generalize can learn the “add ed” rule and so form the past tense of jump based on experience with similar verbs.

Capabilities generally classified as AI as of 2017 includes:

· Successfully understanding human speech

· Competing at the highest level in strategic game systems such as Chess and Go

· Autonomous Cars

· Intelligent routing in content delivery network

· Military simulations

Artificial intelligence was founded as an academic discipline in 1956. The AI field draws upon Computer science, Mathematics, Psychology, Linguistic, Philosophy and many others.

The traditional problems or goals of AI research include:

· Reasoning

· Knowledge representation

· Planning

· Learning

· Natural Language Processing (NLP)

· Perception

· The ability to move and manipulate objects

Knowledge engineering is a core part of AI research. Machines can often act and react like humans only if they have abundant information relating to the world. Artificial intelligence must have access to objects, categories, properties and relations between all of them to implement knowledge engineering. Initiating common sense, reasoning and problem-solving power in machines is a difficult and tedious task.

Types of AI — Weak and Strong AI

Weak AI also known as narrow AI is an AI system that is designed and trained for a particular task. Virtual personal assistants, such as Apple’s Siri, are a form of weak AI.

Strong AI, also known as artificial general intelligence, is an AI system with generalized human cognitive abilities so that when presented with an unfamiliar task, it has enough intelligence to find a solution. The Turing Test, developed by mathematician Alan Turing in 1950, is a method used to determine if a computer can actually think like a human, although the method is controversial.

Another example is from Arend Hintze, as assistant professor of integrative biology and computer science and engineering at Michigan State University. He categorizes AI into four:

· Reactive Machines: An example is Deep Blue, the IBM chess program that beat Garry Kasparov in the 1990s. Deep Blue can identify pieces on the chess board and make predictions, but it has no memory and cannot use past experiences to inform future ones. It analyzes possible moves — its own and its opponent — and chooses the most strategic move. Deep Blue and Google’s AlphaGO were designed for narrow purposes and cannot easily be applied to another situation.

· Limited memory: These AI systems can use past experiences to inform future decisions. Some of the decision-making functions in autonomous vehicles have been designed this way. Observations used to inform actions happening in the not-so-distant future, such as a car that has changed lanes. These observations are not stored permanently.

· Theory of mind: This is a psychology term. It refers to the understanding that others have their own beliefs, desires and intentions that impact the decisions they make. This kind of AI does not yet exist.

· Self-awareness: In this category, AI systems have a sense of self, have consciousness. Machines with self-awareness understand their current state and can use the information to infer what others are feeling. This type of AI does not yet exist.

Examples of AI technology:

· Automation is the process of making a system or process function automatically. Robotic process automation, for example, can be programmed to perform high-volume, repeatable tasks normally performed by humans. RPA is different from IT automation in that it can adapt to changing circumstances.

· Machine learning is the science of getting a computer to act without programming. Deep learning is a subset of machine learning that, in very simple terms, can be thought of as the automation of predictive analytics. There are three types of machine learning algorithms: supervised learning, in which data sets are labeled so that patterns can be detected and used to label new data sets; unsupervised learning, in which data sets aren’t labeled and are sorted according to similarities or differences; and reinforcement learning, in which data sets aren’t labeled but, after performing an action or several actions, the AI system is given feedback.

· Machine vision is the science of making computers see. Machine vision captures and analyzes visual information using a camera, analog-to-digital conversion and digital signal processing.

· Natural language processing (NLP) is the processing of human — and not computer — language by a computer program. One of the older and best known examples of NLP is spam detection, which looks at the subject line and the text of an email and decides if it’s junk. Current approaches to NLP are based on machine learning. NLP tasks include text translation, sentiment analysis and speech recognition.

· Robotics is a field of engineering focused on the design and manufacturing of robots. Robots are often used to perform tasks that are difficult for humans to perform or perform consistently. They are used in assembly lines for car production or by NASA to move large objects in space. More recently, researchers are using machine learning to build robots that can interact in social settings.

AI and its applications

Finance: Banks use A.I systems to organize operations, invest in stocks, and manage properties.

Medicine: A medical clinic can use AI systems to organize bed schedules, make a staff rotation, and provide medical information. AI has also application in fields of cardiology (CRG), neurology (MRI), embryology (synography), complex operations of internal organs etc.

Social Sites: Facebook wants to analyze the way people communicate with one another so that it can add new features to its service or even automatically remove offensive posts.

Education: AI researchers have created many tools to solve the most difficult problems in computer science.

Robotics: Robots are manufactured as hardware. The control of robot is AI (in the form of software agent) that reads data from the sensors decides what to do next and then directs the effectors to act in the physical world.

These are some of the most popular examples of artificial intelligence that’s being used today.

1. Siri

2. Alexa

3. Tesla

4. Cogito

5. Boxever

6. Netflix

7. Pandora

8. Nest

9. Amazon.com

9 Things AI can do for you today:

1. Schedule your meetings

2. Buy things for you (sorry, you still have to pay)

3. Answer your door

4. Customize your home’s lighting

5. Drive you around town

6. Help your salespeople prospect and track potential new accounts

7. Help you avoid traffic collisions

8. Help doctors find treatments for cancer

9. Translate your conversations in real time

Want more information about the impressive things AI can do today? Click here.

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