Table of contents
- What is artificial intelligence?
- How does artificial intelligence function?
- What is learning in AI programming?
- What is reasoning in AI programming?
- What is self-correction in AI programming?
- What are the types of artificial intelligence?
- What is automation?
- What is machine learning?
- What is machine vision?
- What is natural language processing?
- Why is AI the future?
Always hearing the AI or artificial intelligence but cannot understand what it is all about? Well, AI or artificial intelligence can be defined in simple words as the intelligence of machines. On the other side, the intelligence displayed by human beings and animals is called natural intelligence.
What is artificial intelligence?
Artificial intelligence is the human intelligence process simulation by machines. The intelligence is coded and artificially produced hence the term ‘artificial’. With the use of artificial intelligence, the systems could perceive their surrounding environment and act according to the situation to achieve their goals. The term AI also refers to the machines or systems that mimic the cognitive actions of the human body like logical reasoning, problem-solving and so on.
Artificial intelligence began as an academic discipline in 1956. In the beginning, there was steady growth in AI but then it declined with not enough funding. This period is called AI Winter. The revival of artificial intelligence gave way to new approaches and research. AI has been researched in simulating a human brain and mimicking animal behaviour.
How does artificial intelligence function?
Artificial intelligence-based systems take in a large volume of training data that are labelled and analyse this data for correlations and patterns, and then these patterns are used to make predictions on future conditions.
For this functioning, a foundation of specialised hardware and software is required. These hardware and software write and train the machine learning algorithms. With these algorithms, the machine is fed with examples of text chats or image recognition tools. So, when a chatbot comes to a situation where it has to chat like a person it does so and with the image recognition tool, it is able to identify and understand elements in an image by comparing it with other millions of examples.
AI programming mainly focuses on three basic cognitive skills, which are, learning, reasoning, and self-correction.
What is learning in AI programming?
The learning process in AI programming is about acquiring data and creating algorithms that could turn these data into actions. These algorithms give the computing devices instructions on how to perform a specific task.
What is the reasoning for AI programming?
The reasoning process in AI programming is about choosing the apt algorithms for respective situations to get the desired outcome. It is the process of deriving logical conclusions from existing data. This is very important in AI for machines to think and behave like human brains.
What is self-correction in AI programming?
Self-correction process in AI programming is the machine’s ability to correct itself. Machines do not make any major errors or mistakes but in case it does it can rectify themselves with the self-correction and self-enhancement feature. This is designed in AI so that it could give the most accurate results at all times.
What are the types of artificial intelligence?
AI can be categorised into four types. They are reactive machines, with limited memory, theory of mind, and self-awareness.
Type 1- Reactive machines
The basic types of AI machines are reactive and do not perform any other functions like using memories or past experiences to make new decisions.
An example of this type of machine is the chess-playing super-computer by IBM, Deep Blue. This super-computer can identify the pieces of the chess board and can predict the moves but cannot think about what has happened in the past.
This type of AI machine reacts on the basis of what they see in front of them at that particular moment. It perceives the world as it is and does not have an internal concept of the world. Systems of this type are made to fulfil a particular task. They could perform better at a specific game but once they are put in a different situation, they cannot cope with it. Since they cannot perform beyond a function that they have been assigned, these machines can be easily fooled. Their imaginations are not for the broader aspect of the world.
They are not interactive and would not feel bored, sad, or interested ever. These are the simplest task-specific models of artificial intelligence.
Type 2- Limited memory
This type of AI machine has memory and therefore can use to inform decisions for the future. They can look into the past.
Self-driving cars use this technology to drive across and record the speed and direction of neighbouring vehicles. The observation is not made in a moment but after monitoring them over some time. The self-driving cars are preprogrammed with the lane markings on the road, traffic lights and curves of the road. This helps for the smooth functionality of the self-driving cars on the road without hitting or crashing with other vehicles on the road.
But the observations made by the car of other vehicles’ speed and directions are only for some time. It does not save in the car’s memory forever like the drivers accumulate experience in their brains with each driving.
Type 3- Theory of mind
This aspect of AI helps machines understand human behaviour, feelings, and emotions. This would make it easier for the machines to become a part of human teams and work better with human beings.
This gives machines the social intelligence which is necessary for interactions with human beings. With this ability, machines will be able to infer human intentions and predict human behaviour and act accordingly. The systems will be able to differentiate between the emotions and change their course of action to suit them better.
Type 4- Self-awareness
This is an extension of Type 3 artificial intelligence, the theory of mind. The AI systems have consciousness and a sense of self. This type of machine can understand their state.
The consciousness possessed by these machines can also be called self-awareness as they can understand their internal state and also understand the internal state of others. For example, if someone moves faster, the system is able to infer that the person is impatient because it does so when it is impatient or feels the same.
This type of artificial intelligence is not yet invented. Scientists are working to create this type.
AI and Technology
When technology and artificial intelligence came together it paved way for AI Technology which can be used in various other fields. Some examples of AI technologies are automation, machine learning, machine vision, NLP, and robotics.
What is automation?
Automation is the term normally used for tech applications which minimise human input. Artificial intelligence automation is the most complex type of automation among the other types of automation which are basic automation, process automation, and integration automation.
When automation tools include artificial intelligence in their core, the types and volumes of tasks performed are expanded. Robotic process automation (RPA) is an example of AI automation. The software used by this automates tasks which are repetitive and rule-based and normally done by humans.
What is machine learning?
Machine learning is the technology which enables machines to perform without programming. Machine learning works on the basis of two steps; one is to access and learn from data and the other is to use and enhance data (Big Data, Data Analytics).
In the first step, it collects data from different sources of data and then learns from the data. The next step is to use these data and enhance that data for a better work experience. There are three types of machine learning. They have supervised learning, unsupervised learning, and reinforcement learning.
In supervised learning, data sets are labelled, therefore, when new data arrives it can detect the pattern and label it accordingly. In unsupervised learning, data sets are not labelled but are grouped on the basis of similarities and differences. In reinforcement learning, data sets are not labelled but once an action is performed AI system receives feedback.
Some of examples of machine learning are personal assistants like Siri and Alexa. They first access your data and then use the data to perform functions for you. Another example of machine learning is in getting targeted ads for you. These ads are personalised for you using machine learning.
What is machine vision?
Machine vision is a technology which enables the machine to see. Using this technology, it can capture visual information and analyse it with the help of a camera. It also does analogue-to-digital conversion and digital signal processing.
Machine vision can see through the walls, unlike human eyes. It is used in signature identification, and medical image analysis and has got various range of applications.
What is NLP or natural language processing?
NLP or natural language processing is the process by which machine understands and processes human languages. It can read and write human language the same way human beings do.
This ability of computers combines computational linguistics with statistical, machine learning, and deep learning models. All these technologies combine will give the system the ability to process the human language in text or voice data. The computer can understand its full meaning with the sentiment and intentions passed along by the source.
Some examples of natural language processing are voice-generated GPS systems, speech-to-text dictation software, customer service chatbots, and digital assistants.
Why is AI the future?
Artificial intelligence is a game changer and has already made life easier for people. AI systems have replaced many manual labourers by automating manual and repetitive tasks. Research is being done on developing the systems to a level where it could augment human decisions. It is set to change the course of current employment situations.
Let us look into some of the fields where AI is set to rule in the coming years.
Artificial intelligence is transforming the media and entertainment industry by giving the audience the kind of content they wish to see. With AI, the entertainment industry is giving a personalised user experience which is otherwise not an easy option.
The film recommendations based on personal taste enlisting on online platforms is an example of using AI technology in the entertainment industry. Netflix has adopted AI in 2016 to give its users the utmost personalised experience.
Some other examples where AI has changed the course of the media and entertainment business is through the extensive usage of virtual reality and augmented reality, the smart AI algorithms which help in marketing and advertising fields.
With OTT platforms ruling the release industry, film directors have already adopted new ways of telling narratives. Sophisticated predictive programs will be introduced which can analyse a film’s storyline and predict its box office potential. This will end the flops in the cinema.
The medical field has also been transformed by artificial intelligence. Every human body is different from each other, and the same medicine affects each body differently. With AI this can be changed. Personalised medical treatments are available.
Expert doctors are always short in supply and AI has changed that. With machine learning and deep learning models, systems could now diagnose diseases and there is no need to book for a very busy doctor. This makes the medical field cheaper and more accessible. Machine learning is reliable in areas where diagnostic information is digitised like cancer cells can be detected through CT scans, skin lesions can be identified with skin images and so on.
Scientists are on their way to developing AI algorithms that can analyse data and customize treatment according to a patient’s genes, lifestyle, and environment. AI is set to start a personalised medical revolution.
The potential artificial intelligence has in cyber security is beyond words. AI technology develops with time and is able to improve network security time. Machine learning and deep learning, it studies the behaviour of a network and when there is a change in behaviour it can detect easily.
AI can identify unknown threats which cannot be identified with human intelligence. Websites with huge traffic and large chunks of transfer data are a vulnerability and can be safeguarded with AI technology. The data needs protection from malicious software which can be given by AI technology. It serves better vulnerability management, better overall security, accelerate detection and reaction times and so on.
What do you think is the biggest achievement of AI so far? Let us know in the comments below.
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