Last Updated on December 3, 2020 by Sean B
One of the more common questions I get from my readers is, “What is Artificial Intelligence?” As the world moves forward, our areas of interest develop and become more complex over time. Such is also the case with machines; machines are a relatively old human invention and have been around with us for thousands of years.
Machines have helped humans take care of and perform tasks effortlessly that would otherwise require vast amounts of labor. Along with reducing the labor intensiveness of specific tasks, machines help us reduce the time needed for any task.
The capabilities of machines raise a fundamental question, can machines think? This question is known in academia as the study of Artificial Intelligence, and there is a field of research dedicated to exploring this question. In this blog, we will briefly cover the topic of Artificial Intelligence, we’ll also provide some history, examples, and other insights.
What is Artificial Intelligence?
Artificial intelligence refers to the intelligence exhibited by computers instead of natural intelligence displayed by humans and animals. Historically, in academia, artificial intelligence has referred to machines that can mimic living beings’ cognitive functions.
These cognitive functions may involve learning, analyzing, understanding, perceiving the environment, and problem-solving. In other words, Artificial Intelligence can be defined as the effort to reproduce human intelligence in machines through programming.
A Brief History of Artificial Intelligence
Artificial Intelligence has a rich history. Even though the term “Artificial Intelligence” was not coined until 1955, the concept that machines might be able to reason similar to a human has always been around in some form or other.
The precursors towards Artificial Intelligence can be found in Antiquity in myths and legends even though no computers were around that time. The Greek Myth of Talos, a giant Automaton made from bronze that guarded Cretes’ island, is a notable example and dates back to around 300 BCE.
2. Late Modern Period
In the 17th century, ideas and concepts about artificial intelligence can be found in Gottfried Leibniz, Rene Descartes, and Thomas Hobbes. They explored the possibility of rational thinking is converted into a purely mathematical process.
The success and development of mathematics played a massive role in making Artificial Intelligence look plausible. As mathematical formulations and logical operations proved to have a systemic basis, we got closer to the realization of Artificial Intelligence.
3. Modern Times
Artificial intelligence’s key exploration in modern times was done by a brilliant mathematician, logician, computer scientist, and crypto analyst Alan Turing. Alan Turing posed the question of Artificial Intelligence in his 1950 work, “Computing Machinery and Intelligence,” in the following way, “I propose to consider the question, Can machines think?”.
Alan Turing also proposed a Turing machine that was capable of capturing the essence of
Abstract symbol manipulation! This helped to elevate the idea of Artificial Intelligence. Finally, in 1955 Artificial Intelligence came out as its field of study.
In 1955, the term “Artificial Intelligence” was coined by John McCarthy to distinguish Artificial Intelligence from Cybernetics. And soon, Artificial Intelligence in the US began to be funded by the Department Of Defense.
The Categorization of Artificial Intelligence
Artificial Intelligence can be divided into two broad categories.
1. Narrow or Weak Artificial Intelligence
Narrow AI or weak AI refers to a system intended to carry out a specific task, which provides the context in which the AI program is confined and limits itself. These AI programs can be exceptionally efficient at performing tasks, work under numerous constraints, and have limited intelligence.
Narrow Artificial Intelligence is the most commonly occurring type of artificial intelligence and can be found anywhere. Its focus on performing specific tasks has bestowed upon us numerous societal and economic benefits.
The success of weak AI can be attributed to the development of Machine Learning and Deep Learning. Machine learning helps a program learn using statistical methods, while deep understanding is a subset of machine learning and runs input into a biologically inspired neural network.
Examples can include chess or solitaire playing bots in games, Apple’s Siri, IBM’s Watson, Image recognition software, Google search, and Amazon’s Alexa.
2. Artificial General Intelligence or Strong Artificial Intelligence
Artificial General Intelligence or Strong AI is the program that is meant to mimic human intelligence and cognitive abilities. They are capable of performing complex tasks such as solving problems and learning from experience.
Strong AI frequently occurs in science fiction movies, comics, and anime. Strong AI is one of the most intensely debated topics in academia and has always sparked exciting questions about consciousness’s nature.
Due to the challenges of creating a mechanical replica of human cognition, Strong AI is considered one of the most demanding programs to develop. Successful efforts frequently get awarded with praise in academia.
Examples can include modern humanoid robots, chatbots such as Mitsuku, Cleverbot, and PARRY.
Challenges of Artificial Intelligence
As discussed above, the development of a capable machine that can mimic human intelligence raise numerous challenges. Our understanding of human cognition is still limited, and we don’t currently know what our brain is capable of.
Furthermore, current AI architecture only uses a simplified version of human cognition and does not concern itself with the complex nuances associated with human thinking processes. Here is a shortlist of challenges faced by AI.
1. Massive Computing Power
Highly advanced algorithms such as Deep Learning and Machine Learning require many cores and GPU to work efficiently. This adds massive costs to the development of a reliable AI program, which not everyone can afford.
2. Problem Solving
Problem-solving is one of the central tenets of Artificial Intelligence, and researchers have tried their best to develop AI programs that can achieve this. However, the algorithms developed by researchers proved insufficient in solving large problems.
When these algorithms are faced with a large problem, they face a “combinatorial explosion” and become very slow.
3. Data Privacy Concerns
The central aspect on which Deep Learning and Machine learning algorithms are dependants is the set of data from all over the globe that is available to them. While this method is efficient in training AI programs, it raises concerns for privacy among users.
Application of Artificial Intelligence
Artificial Intelligence has many applications in modern society and helps maintain the rubric of today’s civilizations. Following are a few examples of AI’s application in the contemporary world.
1. Artificial Intelligence as Chatbots
Discussion about AI is incomplete without the mention of chatbots, and since that is the focus of this website I couldn’t get away with leaving them out. A chatbot or chatterbox is an excellent application used to conduct an online conversation between the chatbot and a human agent. Chatbots provide numerous services besides entertainment.
1. Messaging Apps
2. Health Care
Chatbots are also widely used in healthcare services, where they give helpful advice to people seeking advice.
3. Customer Services
Due to their appealing nature, chatbots are also used in toys to perform various tasks, such as interacting with the child.
2. Artificial Intelligence in Agriculture
Artificial Intelligence programs are used in the agriculture sector to ensure the excellent quality of crops. AI programs can predict the time it takes for a crop to ripe and when it’s appropriate to reap them.
3. Artificial Intelligence in Cybersecurity
Artificial Intelligence has begun to be used in Cybersecurity with the rise of hacking attacks that Cybersecurity has to face. NLP programs help minimize the risk by sorting data in networks.
4. Artificial Intelligence in the Financial Sector
The use of AI programs in the financial sector is ancient. It can be traced back to 1987 when Security Pacific National Park in the US implemented Artificial Intelligence as a fraud prevention system to prevent debit cards’ unauthorized use.
Today, Artificial Intelligence is used in banks to organize operations, manage properties, invest in stocks, and maintain bookkeeping. Banks use artificial neural networks to detect changes that are unusual and flag them.
5. Artificial Intelligence in Manufacturing
Artificial Intelligence in the form of robotics is frequently used in industries to manufacture a vast array of products. Robots are now given jobs that might be dangerous to a human employee.
6. Artificial Intelligence in Videogames
Artificial Intelligence programs are frequently used in video games as non-playing characters (NPCs).
7. Artificial Intelligence in Utilities
Power electronics converters and other utilities are frequently used in energy storage, renewable energy, and direct high-voltage current. These utilities are prone to failures and, when malfunctioned, can pose severe health and financial risks.
Researchers are now integrating artificial intelligence with these utilities to make them more reliable, productive, safer, efficient, and easily manageable.
8. Artificial Intelligence and Military
The Military has also shown great interest in artificial intelligence; militaries use artificial intelligence for many services such as coordination of sensors, threat detection, target acquisition, and drone development.
9. Artificial Intelligence and Medicine
AI has already shown how useful it can be in Healthcare; companies are using it to assist doctors with diagnosis, to solve complex problems involving Protien Structures, and of course with helping trace infectious diseases like COVID-19.
10. Other Interesting Uses for Artificial Intelligence
Of course the areas mentioned above aren’t alone in using AI technology.
Recently, the Danish Architectural firm BIG and a Chinese tech company Terminus announced plans to build Cloud Valley, an entire city run by AI in the Chongqing region. According to the article by Umberto Bacchi from Reuters, the project “uses sensors and wifi-connected devices to gather data on everything from weather and pollution to people’s eating habits to automatically meet residents’ needs.”
The DeepMind AlphaFold AI recently made a huge leap, solving a problem involving how proteins are folded that has baffled scientists for nearly 50 years. This has the potential to help stop the next Pandemic. The system looked at approximately 170,000 different protein structures and then applied this knowledge to the problem and it’s solutions were accuraute to within 1.6 Angstroms.
In another fascinating use of AI, IBM’s Watson recently created a sculpture called Informed, which is the first thinking sculpturein the style of Gaudi after being fed images of Gaudi’s work. Other AI systems are helping to create their own music. AI systems are also being used to inspire artists, musicians, and even authors.
Essentially, Artificial Intelligence, or AI, is the attempt to make computers think more like human beings do. This effort includes areas like learning, analyzing, understanding, perceiving the environment, and problem-solving. The applications of AI Technology are nearly endless. Anywhere where a computer is used, Artificial Intelligence can be involved. That said, due to the incredible amount of woth that AI often requires, it’s not something you’ll find in simple computer programs.
AI excels in areas where there are repeated tasks, and Artificial Intelligence is showing incredible promise in fields where decision making based on a number of different factors are necessary. The use of AI in chatbots is growing rapidly and can be seen in the use of Virtual Assistants like Apple Siri, Amazon Alexa, and Google Assistant.
As the field of Artificial Intelligence grows, I expect that we’ll see more targeted AI systems being used in areas like Medicine, particularly with Diagnosis and Treatment related tasks. We’ll see similar growth in other areas like the Financial Industry and Utility Management. Architecture and Infrastructure are other areas where I think we’ll see incredible growth. As bridges and roads are rebuilt, the potential to involve AI in the construction and maintenance. Scanning the structures with drones and letting an AI system review the scans would reduce the risk to workers and reduce the number of shutdowns a manual inspection requires.
I’m also hoping that redesigned Power Grids and Transportation Systems using AI will also become more prevalent. Imagine a power grid that rarely has an outage or a transit system where almost every vehicle and train is on time, and they automatically adjust the schedule as needed as the population changes… well, I can dream.
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