Artificial Intelligence in a Nutshell
Artificial Intelligence in a Nutshell
Everything you need to know about Artificial Intelligence
No matter if you are a tech-enthusiast or a total novice, it is a fact that we all are surrounded with technology. With the current pace in the artificial intelligence field, we will be able to scale new heights of infinite proportions in the coming future. If you don’t seem to grasp the concept of AI, this blog is a must read for you.
Let’s get into everything you need to know about Artificial Intelligence in a nutshell!
I will be covering important facts about Artificial Intelligence in this blog that will help you to understand its concept.
Topics that will be included in this blog briefly are as follows:
What is Artificial Intelligence?
Learning stages of AI
Types of AI
Branches of AI
Impact of AI in our lives
How to get started with AI?
So without further ado, let’s delve right into it!
What is AI?
The term Artificial Intelligence was coined in 1956 by John McCarthy, an American Computer and cognitive scientist. Artificial intelligence refers to an umbrella term comprising of various techniques that enable machines to acquire human-like intelligence. John McCarthy himself defined it as the science and engineering of making intelligent machines.
These computer techniques that are created in the image of human cognitive skills are capable of solving complex problems same as humans. AI is perfectly capable of performing certain tasks such as making calculations, formulations and decisions. The decision making skills of AI devices have been gradually improving over the years to the point that now they can easily sense changes in their surroundings, make out the meaning of all that and decide on their actions based on those calculations.
Learning stages of AI
Artificial Intelligence has come a long way since it was first introduced. The technological evolution that AI has undergone can be described in three stages based upon the learning mechanism.
These are the stages through which AI can reach its maximum potential and gradually earn supreme intelligence:
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Artificial Intelligence Stages
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Artificial Narrow Intelligence (ANI) |
Artificial General Intelligence (AGI) |
Artificial Super Intelligence (ASI) |
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It is also called Weak Artificial Intelligence (WAI).
This stage of AI as the name suggests is able to perform a narrow range of tasks which are pre-defined and do not exhibit any thinking process.
This stage involves every AI-based system available out there in the commercial market.
Examples are autonomous automobiles, Sofia (the humanoid), Alexa, Siri, Alpha-Go, etc.
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It is also called strong Artificial Intelligence (SAI). T his stage of AI is a bit more evolved than ANI as the machines that fall under this stage will have the thinking and decision making abilities same as humans. Their actions won’t be pre-defined and they will be able to act on their own. This stage is yet to be achieved and soon smart machines will be amongst us.
This stage is up for complicated debate among scientists where there are mainly two schools of opinions. One supports this idea of a machine that can perfectly act like humans whereas the other describes AGI to be a threat to our existence in many ways.
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This stage of super intelligence is highly speculated to be the ultimate goal of Artificial intelligence. Although it is a hypothetical concept that has been frequently the core subject of science fiction movies and books. But with the pace our existing AI technologies keep evolving, fiction can be turned into reality.
This capability of acquiring super intelligence is a far-fetched theme for now, but there are strong chances that future will be dominated by machines, hopefully we will still be able to have an upper hand on our creations.
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Types of AI
According to the different levels of functionality of AI-based systems, AI can be classified into following types:
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Artificial Intelligence Category
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Description
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Reactive Machine AI |
Machines that are only responsive to present situation and can accomplish a narrow range of tasks, comes under this category.
These AI machines function only on the availability of current statistics and data. They are incapable of formulating their future actions based on the given data.
Example of Reactive Machine AI is the AI chess program from IBM that was able to defeat Garry Kasparov, world chess champion.
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Limited Memory AI |
Limited Memory AI is capable of making well-informed and improvised decisions by examining its past data memory.
The machines based on this type of AI have a temporary memory that is short-lived. Such memories from its data can be used to record past experiences and further make predictions about future actions.
Example of Limited Memory AI are Self-driving cars. The sensors installed in self-driving or autonomous cars can use the data collected from past memories such as pedestrians across the road, traffic lights, etc and help the car to make immediate decisions while driving. This helps in preventing accidents and ensures better driving experience.
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Theory of mind AI |
It is an advanced Artificial Intelligence type that as the name suggests deals with psychological areas. It’s main goal will be to analyse and interpret human emotions and enhance its emotional intelligence. This AI type is in developmental phase for now but chances of its debut are very bright in the near future.
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Self-aware AI |
Self aware AI will comprise of self aware machines that will have their own cognitive abilities with heightened consciousness.
Highly theoretical, we are quite far from achieving this AI type any time soon which could be a good sign. Imagine a machine that can act like humans with almost no possible weaknesses roaming the earth.
There could be some advantages in this tech for example having a powerhouse of a device that never dries-off its juice but we cannot negate the disadvantages associated with the idea as well. Take an exponential rise of unemployment for example. Humans getting replaced by machines has always been a matter of condemn. Whenever we achieve a super intelligent AI system, there should be a proper system to take everything under consideration and make the tech beneficial for everybody.
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Branches of Artificial Intelligence
AI comprises of different ranges of techniques that have been branched out of it and are extremely useful in solving real-world problems. These are as follows:
Machine learning
Machine Learning refers to the science of making machines capable to observe, analyze and process the given data for the purpose of solving real-world problems and issues.
There are three categories of Machine learning:
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
Deep learning
Deep Learning denotes to the process of using neural networks on high dimensional data in order to gain insights and come up with plausible solutions.
It is an advanced field of Machine Learning that can be utilised to solve more advanced problems.
Examples of this technique are self driving cars, social media security measures, Siri, etc.
Natural language processing
Natural Language Processing is the science of taking information from the naturally occuring human language for communicating with machines and thrive business agendas.
Example: Twitter uses Natural language processing to filter out offensive and immoral language usage.
Robotics
The most impressive and highly ambitious branch of AI is Robotics that is characterized by the implementation and application of robots in technology. AI Robots act as agents of AI technology that perform in a real-world environment and aim at producing results. They are accounted for their own actions that are authorised on legal basis.
Expert systems
Expert systems are important computer systems that are AI-based and exhibit decision-making abilities of a human expert after thorough observation.
Expert systems make use of some pre assumptive logical theories in order to solve complex problems. They do not use the conventional programming procedure.
Expert systems are primarily used in healthcare systems, information management, financial analysis, etc.
AI Impacting our lives
Artificial Intelligence is everywhere around us. It has impacted our lives in great manner and helped it to become comfortable and easy to deal with.
Following are the examples of the AI technology from our daily lives that you can easily comprehend with:
- E-commerce: to create a customer centric experience.
- Healthcare: for detection of diseases, screening and formulating diagnosis methods.
- Smartphones features: auto correct features on smart keyboards, smart assistance such as virtual assistance from Alexa, Siri and Google assistant.
- Smart devices for home: affiliating various features such as weather checking, temperature regulation, sending text messages, news via smart speakers and so on.
- Security: facial recognition, anti-theft, surveillance applications.
- Finance sector: automated financial investing, securing customer services, automated e-mails, etc.
- Travelling: for navigation, location spotting, GPS, Google maps, cab booking, flight ticket registration via virtual travel agent, etc.
- Online businesses: online networking, advertising.
- Robotics: overcoming human limitations.
- Hybrid automobiles: self driving cars.
- Music streaming
- Social media Apps
- Videogames with life-like virtual set-up.
- Social media activities and monitoring.
How to get started with AI?
If you are interested in learning AI and start a career in it, I would suggest you to go through following steps:
Taking up a free online course is the best decision for a great career in AI and data science. But before you begin, you need to prepare yourself first in order to have a smooth learning experience. How you ask? Read on:
- Familiarize yourself with some fundamental programming tools such as, Python, R, Panda, Hadoop, Numpy, Seaborn, spark, Matplotlib, bot frameworks (Amazon Lex Microsoft Bot). These are the most popular ones and might be helpful during your training.
- Basic knowledge of programming languages such as C++, Java.
- Machine learning models and applications.
- Brush up on your maths skills, especially algebra, probability, calculus, matrices, as most of the AI courses requires some knowledge of linear algebra.
- Understand how AI algorithm and data analytics work.
You can check my other blog on A Beginner’s Guide for Free Online Artificial Intelligence Courses.
To summarize it all
We are all important members of the modern digital world which is enriched with infinite technological inventions. Artificial intelligence is a revelation among technologies which has immense potential for more growth. Aspirants for this field should take proper training before starting their career in this wonderful field as it equally requires utmost dedication and determination.
