Artificial Intelligence or AI is what simulates human behavior that pertains toits problem-solving capacity. The intelligence process involves analysis, perception, learning, reasoning, correction, linguistics, recognition and other cognitive human functions.
It essentially aims to make human lives easier. Researchers have also been trying to implement various emotion quotients into the AI equation which are going to be implemented in machines. With worldwide spending of $35 billion or more, AI is the future we are looking at. It has projected itself over various sectors starting from health care infrastructure to Engineering.
Philosophy Behind AI:
With the technological advancement, the eventual process of manual integration is getting reduced. With the implementation of computer-based infrastructure, humans are highly dependent on them. So, when everything around humans is surrounded by this technology, a recurrent thought often evoked amongst many i.e. “Can a machine behave like humans?” That curiosity lead to the eventual development of AI. The primary intention upon which the foundation of AI stands is development of machine intelligence similar to humans.
The primary goals of AI are cited below:
Creating an expert system
The creation of AI aims to achieve an automated structure which would provide data-driven advises to humans, exhibiting intelligent behavior.
Implementing human intelligence in computers
It helps to create an identical cognitive pattern in computers, helping them simulate human behavior and take measures to solve a particular problem. This automatically reduces human work and enables a process of automation via the algorithms applied.
AI integration will have its effect in multiple sectors such as:
- Statistics, Psychology
- Space Technology
- Natural Sciences
- Medical Science
- Engineering, Ethics
- Computer Science
- Cognitive Science
Computer science applications
AI also helps in the development of mechanisms which can derive a solution to difficult problems in the sectors such as:
- Search and Optimization
- Logic, Control Theory
- Language Analysis
- Neural Networks
- Statistical Learning Methods
- Probabilistic Methods
Types of Artificial Intelligence:
The varied types of AI are categorized under two primary classification i.e. Type 1 or Basic and Type 2 or Advance. Type 1 AI implemented systems are the machines that work on an input-programmed-output structure based on certain variable parameters. The Type 2, however, makes decisions based on real-time events, entities and scenarios, cumulatively put together into its consideration. There are certain situations that are dynamic and require observational influence on Type 2 AI implemented machines. They are often considered to be sentient since they can react like humans, having the capacity to analyze and recognize.
The types of AI are as follows:
This kind of AI would focus narrowly on one task as opposed to being focused on multiple tasks via generic automated system of a task series. Machines which are relatively less intelligent follow this mechanism within their limited threshold of capacity. For example, in a game like Solitaire, all the rules, instructions and moves are fed when it’s competing against a human opponent.
This system is where the computers assess and reason similar to the human mind via Artificial General Intelligence. It also exhibits intelligence to solve complex problems. The machine would alsobe more sentient given it respond to complex queries using its internal algorithm. Voice AI assistants like Google Assistant or Siri are examples of strong AI that can answer realistically to complex and random questions.
These are also known for being a moment machine which doesn’t rely on past insights to act on future instances. They can produce basic predictions based on the present circumstances under a varied number of parameters devoid of any past memory or data. A game like Chess on computer is a worthy example of such a machine where the moves are based on current circumstances without any prior knowledge.
They can use the information stored in them from past instances to make future decisions. Driving assistants, for instance, can take on-spot decisions based on dynamic and random value of parameter. They can also use the information of any previously visited area to provide the best route for traversal.
Theory of Mind
These machines can react to any responses based on thoughts, scenarios, emotions, beliefs et al. They are ideal for human demeanor observations and social interactions.
These systems can use their super-intelligence based on circumstances, internal traits, conditions, and states. This machine has a lot of scope in terms of future implementation.
The AI Technique:
The properties pertaining to real-time knowledge are
- Disorganized and devoid of any proper format
- The volume of knowledge is huge and is probably beyond unimaginable
- It continually keeps changing
However, the Artificial Intelligence technique involves a process which formats and makes use of the knowledge more effectively
- The knowledge used should be grasped easily
- Must adapt quickly and easily to correct any given errors
- Can be used with efficiency even if it’s yet to be completed
A Brief Overview of Artificial Intelligence History:
It was coined in the year 1956 by John McCarthy which has gained a lot of gravity over the years. The traction is mostly due to advanced algorithms, larger data volumes, programming and advanced computer storage with efficient use of power.
AI can be defined shortly as a subset of computer science. The primary advantage of using AI machines or computers is their ability to emulate human behavior, impersonating human activities which make human life easier.
To get a better angle at AI, let’s have a look at the history of AI which had its inception 100 years ago or in recurrent times.
- 1923: Robot as a term was first used in English on a play called “Rossum’s Universal Robots” by Karel Capek which premiered in London.
- 1943: The fundamental work of neural networks was established.
- 1945: Robotics as a term was invented by Isaac Asimov who was a Columbia University Scholar.
- 1950: Turing Test was introduced by Alan Turing which analyzed intelligence. A seminal paper named “computing machinery and intelligence” was published as well.
- 1956: Artificial Intelligence as a term was coined in this year by John MacCarthy. An AI program demo was attempted at the Carnegie Mellon University.
- 1956: LISP programming language was innovated for AI by John MacCarthy.
- 1964: Danny Brown’s thesis at MIT proved the computer’s ability to apprehend normal language to solve word problems of Algebra with precision.
- 1965: An interactive program called ELIZA came into being which converted message in the English language for the very first time at MIT by Joseph Weizenbaum.
- 1969: Researchers and scientist designed Shakey which was robot equipped with locomotion, problem-solving ability, and locomotion at the Stanford Research Institute.
- 1973: Popular Scottish robot Freddy was invented which could efficiently collect, build and locate model using its vision. It was developed by the Assembly Robotic Group at Edinburgh University.
- 1979: Stanford Cart which is the first computer-controlled auto vehicle originated.
- 1985: Aaron’s drawing program was developed and designed by Harold Cohen.
- 1990: Some of the most important breakthrough related to AI happened.
- 1997: The deep blue chess program defeated world chess champion, Garry Kasparov.
- 2000: Kismet, a robot with a face which could exhibit emotions was showcased at MIT. Robot pets could be availed of in the market. Nomad, the robot which traveled through the remote regions of Antarctica discovered meteorites there.
AI and Its Applications:
AI has a huge role to play in various sectors as of yet. Some of these sectors are mentioned here:
AI plays a huge role in games like chess, solitaire as mentioned already. There is another implementation of AI in modern video games where they can think of multiple steps based on their heuristic knowledge.
Natural Learning Process
It helps computers comprehend the natural languages used by humans.
Applications such as this use machine programming and AI integration to take special moves after data assessment. They also give exhortation and clarification to the end-users.
These systems are designed to comprehend, grasp and interpret visual inputs given. For instance, spy planes or drones taking pictures which can be used as intel or to make spatial data for guiding operations.
Some systems are made to understand and process human language when spoken to them. They can even identify profanities, accent and even background noises.
This specially crafted application can read a text written with stylus or pen on screen and paper respectively. It can also comprehend the various letter shapes and can convert them into editable texts.
Robots are one of the most important creations made by humans. They can do tasks that minimize human effort, saving time. They can’t obviously be an alternative to humans but can efficiently carry out any given tasks they have been programmed for. These machines are often comprised of sensors that can detect physical data like movement, temperature, light, and heat. This is similar to the way’s humans feel all these external stimuli. Robots usually have a big memory with good processing units. These systems can also adapt to the environment around them fairly quickly.
Some Examples of AI application:
- Traffic Management Systems
- Ticket Reservation Systems
- Recommendation software for services and products such as Netflix
- Natural Disaster Warning Systems
- Language translation software
- Image Processing for Diagnosis
- Grading Systems in the educational sector
- Fraud and SPAM detection
- Cloud Computing,
- Open-source technologies
- Climate Change Detection
- Chatbots with personalized learning
- Autonomous Vehicles like buses, cars, submarines, two-wheel drives, drones, and autopilot flights
- AI Robotics in Healthcare Technologies and Surgical Equipment
Difference Between Artificial Intelligence (AI) and Machine Learning (ML):
Machine Learning (ML) is a subset of AI which has a defined goal along with steps to reach that specific goal. All of these are fed as an input into the system along with the parameters with alternative actions if required. The information received is then used by the system automatically where it learns from its experience. The program which generates the algorithm integrates it as an input and for output as well. This increases efficiency in performance.
- The primary aim is to make accurate results as opposed to producing the one that is desired.
- It doesn’t involve any randomization based on variable parameters. It has fixed values which the system is based on.
- The ultimate goal of Machine Learning is to predetermine a specific set of data and give out a mechanical solution for better performance of the system. There is no decision making involved.
- It is purely algorithm based with data format structured for input/output.
- It also involves the building of knowledge without any biases.
- Machine Learning can recognize patterns and act on them.
Artificial Intelligence, on the other hand, is based on the machine’s ability to acquire and apply the knowledge based on real-life instances with real-time data. The goal of AI is to execute an action in a simulated human way. The acts can either be independent or interdependent. AI also incorporates multiple integrations of programming, pattern recognition and even validations to behave in an anticipated way.
- The primary aim of AI is to give results via intelligent data mining, analysis and a deeper understanding of the same.
- AI also involves results that are based on real-time processes and automated processes where the parameters maintain dynamicity.
- The goal of any Artificial Intelligence is to simulate the intelligence that entails human beings to produce realistic solutions to problems via better and organized decision making.
- It also leads to the wisdom of learning where they can do so by using their intelligence or through self-imposed morals.
- It includes smart learning through past iterations and alternative information processing or cognitive analysis applications which also demands distinct capabilities.
Advantages and Disadvantages of Artificial Intelligence:
AI is meant to hold complexity which is its innate nature and also why it is fascinating. It uses an amalgamation of mathematics, computer science, and other branches. The further the complexity, the better is the simulation of human cognitive abilities.
The advantages of AI are as follows:
- It simplifies work by filtering, predicting, sorting, analyzing, determining and scoping large volumes of data to seek the best implementation of a process for optimal solution production.
- It performs mundane tasks which are effective and faster with a reduced number of errors. They can be performed, quiet impeccably so by the AI systems.
- Precise and accurate results acquired by the integration of highly responsive AI to solve any tech-driven task that requires complex solution.
- They can adapt to any given environment without being bound to them physically.
- The simulations are all real-time based for the Artificial Intelligence system to produce better and realistic results during real-life instances.
- It also protects and secures data along with any critical information. Loopholes are also fixed or updated on.
- AI systems can deliver high-quality results and analysis which are well integrated across a wide range of system.
The disadvantages of AI are as follows:
- Costs are high due to the capability of complex programming by these systems.
- Maintenance and repair aren’t just expensive but also requires expertise and high-level understanding of AI.
- All of these systems might emulate the cognitive abilities of humans but it still lacks the judgment a human can only make. For instance, target picking by fighter planes or making investment calls during market value changes.
- AI implementation will slowly reduce the need for humans who formerly carried out those tasks. It would particularly be affecting areas like retail and banking.
- These systems can be misused or even altered during system breaches or internal glitches.
- The Artificial Intelligence systems can’t improve on their functionalities and neither can they propose infrastructures. Unless of course they are developed by humans. This can lead to scenarios which will leave them absolutely obsolete in many situations.
Future it Holds
In the recurrent years and the ones to come, the void of requiring Artificial Intelligence implementation has created the ways for more researches based on AI. It also has issued interest in areas such as control and security of topics that are not technical: law and economics for instance.
While a laptop crash can be handled, an airplane autopilot discrepancy, on the other hand, will put lives in danger. There are various lethal and automated weapons which are using AI implementation, garnering challenges in the future in case of any disputes.
Some of the things that AI can potentially change or affect in the future are as follows:
- Artificial Intelligence can replace humans in Hazardous factory jobs
- Automated transportation
- Artificial Intelligence can predict climate changes using reports and data collected through environment reading.
- AI will effectively handle customer services which will be faster and more efficient.
- Health care management and personalized infrastructure to cater to the specificities of each patient. It can also identify symptoms via medical data processes.
- Patients can make use of artificial prosthetics to make their lives easier.
- Artificial Intelligence sent to space can learn about orbital pathways and suggest traversal route according to the observations recorded.
Artificial Intelligence creation is probably one of the biggest creations in the history of humankind. If they are used constructively, AI can further eradicate poverty and stabilize food crisis all over the world.
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