In this ever-evolving modern world, we are all surrounded by Artificial Intelligence in one way or another. AI is found everywhere, from assistants such as Alexa and Siri to the internet predicting what we may like to buy next.
However, the idea fascinated many free thinkers but also frightened many others. A few referred to Artificial Intelligence as a great leap toward the modern future, while some bashed the argument based on worries that it might lead to human extinction. So, before wrapping the layers of AI around any new technology, the basic question that comes into your mind is – What exactly is Artificial Intelligence?
The most practical definition explaining AI meaning is any technology attempting to replicate some broader human intelligence aspect. As Artificial Intelligence (AI) is rapidly transforming our world, extraordinary surges in AI capabilities have led to many innovations, including self-driven vehicles and connected Internet of Things (IoT) devices in our homes.
Artificial Intelligence even contributed to developing a brain-controlled robotic arm that can help a paralyzed person feel again through complex direct human-brain interfaces. These new AI-enabled systems are transforming and supporting nearly all parts of our society and economy, everything from healthcare and eCommerce to transportation and cybersecurity.
This amazing technology has brought several extraordinary things into our lives, and it will create an even more significant impact in the next two decades. So let’s find out what AI is and how Artificial Intelligence is shaping our future?
What is Artificial Intelligence?
Back in the 1950s, Minsky and McCarthy defined Artificial Intelligence as any task performed by a machine that would have formerly been considered to involve human Intelligence. That’s apparently a pretty broad definition, because of which you will occasionally see some arguments over whether something is genuinely AI or not.
Francois Chollet, an AI researcher at Google and maker of the machine-learning software library Keras, said, “Artificial Intelligence is tied to a system’s capability to familiarize and improvise in a new environment, generalize its knowledge and apply it in unacquainted scenarios.”
“Intelligence is the efficiency with which you obtain new expertise you didn’t previously prepare for in your tasks,” he said. “Intelligence is not a skill itself; it’s not about what you can do. Instead, it’s how well and proficiently you can learn and understand new things.”
Typically, AI systems exhibit at least some of the subsequent behaviors correlated with human Intelligence: learning, planning, reasoning, knowledge representation, problem-solving, motion, perception, manipulation, creativity, and Social Intelligence.
Artificial Intelligence is virtually impacting nearly every industry and every human being. This amazing technology has brought many remarkable things into our lives, and hopefully, it continues to do so.
According to Ray Kurzweil – a well-known futurist – Computers will have a similar Intelligence level as humans by 2029. Kurzweil stated to Futurism, “2029 is the date I have predicted when an Artificial Intelligence will pass a valid Turing test and thus reach human Intelligence levels. Furthermore, I have set the date 2045 for the ‘Singularity’ when we will grow our effective Intelligence a billion fold by uniting with the Intelligence we have built.”
History of Artificial Intelligence
The history of Artificial Intelligence goes far back to ancient Greece. However, the rise of electronic computing made AI a real possibility. As a result, Artificial Intelligence has also changed from what it was earlier as technology evolved.
For example, a few years ago, machines that could carry out optical character recognition (OCR) or simple arithmetic were considered AI. Today, OCR and basic calculations are not regarded as Artificial Intelligence but rather as fundamental computer system functions.
AI in the 1950s – Alan Turing, a man known for cracking the WWII ENIGMA code used by the Nazis, published the Computing Machinery and Intelligence paper in mind. He tries to answer the question – Whether machines can think. He delineates the Turing Test that defines whether a computer exhibits the same Intelligence as a human.
The test holds that an AI system should be able to embrace interaction with a human without the human knowing they are talking to an AI system. The first AI conference was held at Dartmouth College, where the term Artificial Intelligence was first used.
AI in the 1960s – The US Department of Defense, through DARPA, takes some serious interest in Artificial Intelligence and embarks on building computer programs that simulate human Intelligence. For example, Frank Rosenblatt developed the Mark 1 Perceptron computer based on a neural network that learns through some experience.
AI in the 1970s – DARPA accomplishes several street mapping projects.
AI in the 1980s – A more complex wave of Artificial Intelligence arises. For example, neural networks with backpropagation algorithms find extensive application in AI systems.
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AI in the 1990s –The Deep Blue supercomputer defeats world chess champion, Garry Kasparov, twice. The Genome Sequencing project and other similarly complex undertakings produce huge information. Computing progress makes it possible for this data to be collected, accessed and evaluated.
AI in the 2000s – The Internet Revolution powers Artificial Intelligence to extraordinary heights. Big data joins the corporate lexicon. DARPA rolled out smart personal assistants long before Alexa, Siri, Cortana, and Google Assistant became popular.
This covers the way for the reasoning and automation that’s a part of modern personal computers and smartphones. That involves smart search and decision support systems that enhance and complement human capabilities.
AI in the 2010s – Baidu (China’s search giant) reveals the Minwa supercomputer that depends on a convolutional neural network to recognize, examine, and categorize images with better accuracy than the ordinary human.
DeepMind’s The AlphaGo deep neural network program defeats Go world champion Lee Sodol in a five-game match. Go is an ancient Chinese game that is significantly more complex compared to chess.
AI in the 2020s – During the early stages of the COVID-19 pandemic, Baidu made its LinearFold AI algorithm accessible to scientific and medical teams looking to create a vaccine. The system could forestall the virus’s RNA sequence in just 27 seconds, which was 120 times faster than previous methods.
As the day progresses, Artificial Intelligence is making speedy advancements in almost every industry. AI is no longer the future. It is the present! So now that we have a basic idea of what Artificial Intelligence is, let’s dive into how AI works?
How Does Artificial Intelligence Work?
Creating an AI system is quite a sensitive procedure of reverse-engineering human personalities and capabilities in a machine and using its computational ability to exceed what we are capable of.
To understand How Artificial Intelligence actually works, we need to dive deep into the different sub-domains of Artificial Intelligence and understand how those domains could be employed in the various fields of the industry.
1. Machine Learning:
ML educates a machine to make interpretations and decisions based on experience. It recognizes patterns and evaluates past data to understand the meaning of these data points to reach a reasonable conclusion without the involvement of human experience. This automation to get the findings by considering data that saves human time for businesses and helps them make better decisions.
2. Deep Learning:
Deep Learning is an ML technique. It teaches a machine to process inputs through layers to categorize, comprehend and predict the outcome.
3. Neural Networks:
Neural Networks operate on similar principles to Human Neural cells. They are a series of algorithms that capture the relationship between different fundamental variables and process the data just like a human brain.
4. Natural Language Processing:
NLP is the science of reading, comprehending, and interpreting a language by a machine. Once a machine recognizes what the user proposes to communicate, it responds consequently.
5. Computer Vision:
Computer vision algorithms try to understand an image by breaking down and examining various parts of the object. This helps the machine categorize and study images to make a better output decision based on prior observations.
6. Cognitive Computing:
Cognitive computing algorithms simulate a human brain by evaluating text/speech/images/objects in a way that a human does and provide the anticipated outcome.
Types of Artificial Intelligence?
So, different Artificial Intelligence objects are developed for various purposes, and that’s how they vary. Based on functionalities, AI can be categorized as Type 1 and Type 2. So, let’s understand what these types of Artificial Intelligence are. Here’s a brief introduction to Type 1.
Type 1 is divided into 3 Types of Artificial Intelligence:
- Artificial Narrow Intelligence (ANI)
- Artificial General Intelligence (AGI)
- Artificial Super Intelligence (ASI)
Let’s take a detailed look.
1. Artificial Narrow Intelligence (ANI)?
This is the most general form of Artificial Intelligence found in most places. These AI systems are designed to resolve one single problem and would be able to execute a single task really well. However, they have limited abilities, like recommending a product for an eCommerce user or forecasting the weather.
This is the only kind of Artificial Intelligence that exists today. They can come close to human functioning in particular contexts and even exceed them in many instances, but only excel in very organized environments with limited parameters.
2. Artificial General Intelligence (AGI)?
AGI is still a theoretical concept. It’s described as Artificial Intelligence with a human-level of intellectual function across different domains such as image processing, language processing, intellect and computational functioning.
We are still a long way from creating an AGI system. It would need to involve thousands of Artificial Narrow Intelligence systems working in tandem, interacting with each other to mimic human Intelligence.
Even with the most advanced computing systems and infrastructures, such as Fujitsu’s K or IBM’s Watson, it has taken them 40 minutes to simulate a single second of neuronal activity.
This speaks to both the great complexity and interconnectedness of the human mind and the magnitude of the challenge of developing an AGI with our existing resources.
3. Artificial Super Intelligence (ASI)?
An Artificial Super Intelligence (ASI) system would be able to go beyond all human capabilities. This would involve decision-making, making rational decisions, and even making better art and developing relationships emotionally.
Once we attain Artificial General Intelligence, AI systems will be able to expand their abilities and progress into realms that we might not even dream of. While the gap between AGI and ASI would be relatively narrow, the long journey toward AGI makes this look like a concept that lies far into the future.
- Strong and Weak Artificial Intelligence
Extensive research in Artificial Intelligence also divides it into two more categories: Strong and Weak Artificial Intelligence. John Searle coined the terms to differentiate the performance levels in different AI machines. Here are some of the core differences between them.
|Weak Artificial Intelligence||Strong Artificial Intelligence|
|It is a confined application with a limited range.||It is a comprehensive application with immense possibilities.|
|This application is suitable for some specific tasks.||This application has exceptional human-level Intelligence.|
|It utilizes supervised and unsupervised learning to process the data.||It uses collecting and association to process data.|
|Example: Alexa, Siri.||Example: Advanced Robotics|
Where is Artificial Intelligence Used?
Artificial Intelligence can be really valuable for business innovation and digital transformation. AI can cut costs and initiate speed, scalability, and consistency levels that are otherwise not viable. You probably interact with some form of Artificial Intelligence multiple times each day. The AI applications are too many to cover here thoroughly. So, here we will look at some of the most significant ones.
With cyberattacks growing in scale, complexity in human-dependent cyber defenses is no longer sufficient. Usually, anti-malware apps are developed with some particular threats in mind. Virus signatures were updated as new malware was recognized.
But synchronized with the sheer number and variety of threats, ultimately becomes a near-impossible task. Furthermore, this methodology was responsive and depended on identifying a specific malware for it to be added to the next update.
AI-based anti-spam, intrusion detection/prevention, firewall, and other cybersecurity methods rise above the outdated rule-based strategy. Real-time threat identification, analysis, mitigation, and prevention are included here. In addition, they implement AI systems that detect malware traits and take corrective action even without the proper identification of the threat.
Artificial Intelligence cybersecurity systems depend on the constant data feed to identify patterns and backtrack attacks. These systems learn to identify irregularities, respond to threats, monitor behavior, adapt to attacks, and issue alerts by feeding large data volumes algorithms.
2. Speech Recognition and Natural Language Processing
Speech recognition is a technology that recognizes speech and converts it into digital text. It’s at the core of computer dictation apps, voice-enabled GPS, and voice-driven call responding menus.
Natural language processing (NLP) depends on a software application to decrypt, interpret, and create human-readable text. NLP is the technology behind Siri, Alexa, chatbots, and other text-based assistants. In addition, some NLP systems use sentimentality evaluation to determine the attitude, mood, and specific language qualities.
3. Real-Time Recommendations
Ecommerce and entertainment websites and applications leverage neural networks to recommend products demanded by the customer based on their past activity, the activity of similar customers, season, weather, time of day, and more. These real-time recommendations are modified according to each user. For e-commerce sites, requests grow sales and help enhance inventory, logistics, and store layout.
4. Image Recognition
Image recognition is Artificial Intelligence that allows us to categorize and recognize people, objects, actions, text, and writing occurring within moving or still images. Powered by deep neural networks, image recognition has found application in self-driving cars, fingerprint identification systems, medical image/video analysis, check deposit apps, etc.
5. Automated Stock Trading
The stock market can be exceptionally volatile in times of crisis. Billions of dollars may be wiped out in seconds. An investor who was in a highly lucrative position one minute could find themselves deep in the red shortly after that.
Yet, it’s nearly impossible for a human to react quickly to market-influencing events. High-frequency trading (HFT) systems are AI-driven platforms that make millions of automated trades per day to maintain stock portfolio optimization for big organizations.
6. Ride-Sharing Services and Self-Driving Cars
Ola, Uber, and other ride-share applications use Artificial Intelligence to connect riders to available drivers. AI technology reduces diversions and wait times, provides genuine ETAs, and deploys surge-pricing during spikes in demand.
Self-driving cars are not yet standard everywhere, but there’s already been an intensive push to embed AI-based safety functions to detect risky scenarios and
7. Autopilot Technology
Unlike land-based vehicles, the margin for error in aircraft is very thin. Given the altitude, a small mistake or miscalculation may result in hundreds of fatalities. As a result, aircraft manufacturers had to drive safety systems and become the earliest adopters of Artificial Intelligence.
Autopilot systems have been flying military and commercial aircraft for decades to minimalize human error. They use GPS technology, robotics, sensors, image recognition, and collision prevention to securely navigate planes through the sky while keeping pilots and ground crew informed.
8. Software Test Automation
Artificial intelligence accelerates and simplifies test creation, implementation, and maintenance through AI-powered intelligent test automation. For example, AI-based machine learning and innovative optical character recognition (OCR) provide advanced object recognition.
When combined with AI-based mockup identification, AI-based text matching, image-based automation, and AI-based recording, teams can reduce test creation time and test maintenance efforts and enhance test coverage and resilience of testing assets.
9. Functional Testing
Artificial Intelligence allows you to test faster with efficient testing solutions. By combining extensive technology support with AI-driven capabilities, AI delivers the speed and resiliency that helps quick application changes in a continuous delivery pipeline.
10. Enterprise Service Management
Almost every business faces the challenges of too many manuals, an ever-increasing volume of requests, error-prone workflows, employees unhappy with the level and quality of service, etc. Artificial Intelligence and machine learning technology can take the service management of the business to the next level:
- Smart search competencies allow employees to find answers rapidly.
- Virtual agents or bots can execute tasks using natural language processing (NLP)
- Intelligent analytics allow workflow optimization and automation
- Metrics from unstructured data, for example, user surveys, can be collected and evaluated more effectively.
11. Robotic Process Automation (RPA)
Robotic process automation (RPA) uses software robots that imitate screen-based human activities to carry out repetitive tasks and expand automation to interfaces with challenging or no application programming interfaces (APIs).
Hence, RPA is ideal for automating processes characteristically accomplished by humans or that need human involvement. Furthermore, resilient robots adapt to screen changes and keep operations flowing when change occurs.
When powered by AI-based machine learning, RPA robots recognize screen objects and imitate human intuition to determine their functions. They use OCR to read text and computer vision to read visual elements, for example, shopping cart icons and login buttons.
When a screen object changes, robots adapt, and machine learning drives them to constantly progress how they see and interact with screen objects, just like a human would.
How Artificial Intelligence is Shaping Our Future
Artificial Intelligence has the potential to transform numerous industries, with a wide range of possible use cases. All these different industries and use cases have in common: they are all data-driven. Since Artificial Intelligence is an effective data processing system at its core, there’s a huge potential for optimization everywhere.
Let’s look at the industries where Artificial Intelligence is already shining.
1. AI In The Automotive Industry
One of the prime beneficiaries of Artificial Intelligence is the automotive industry. Robots are being used on several platforms for car manufacturing, from shaping a block of aluminum into an engine. Then, you see them welding the joints, painting the car, assembling the parts, and cutting leather for the interior.
Additionally, Artificial Intelligence assists the automotive industry in many other ways. For example, have you heard of drive assist? Well, that’s an Artificial Intelligence doing its job. Or, while reversing your car, do you hear the car beeping when you’re close to any object? Again that’s AI.
2. AI In Entertainment Sector
This is probably the most exaggerated segment. Artificial Intelligence has totally overturned the way the entertainment industry used to work. Cameras are more subject-oriented and utilize automated modes to identify backgrounds or faces. The best part about it is the number of details and reliability.
3. AI In Healthcare
You might be using Artificial Intelligence in the healthcare industry without even realizing it. For example, the Apple Watch, Fitbit, and other smartwatches examine your activity and monitor your heartbeat. It even notifies you if something is off.
Artificial Intelligence is also being extensively used in the manufacturing and production of medications. In addition, it’s being used in the making of vaccines and medicines, and that’s not enough; robot-assisted surgery is now operative and can get far more precise and faster results.
4. Weather Forecasting
Weather forecasting is not 100% correct because predicting the future has never been an easy task. Earlier, the meteorological department used to take data from different sensors, consider other factors, apply the algorithms, and predict the weather. It used to be a long procedure, but now it has become straightforward, thanks to Artificial Intelligence.
AI collects the sensory and archived data and creates a model that forecasts whether or not you see into the future with better accuracy. A formidably complex data point factors into weather patterns, making Artificial Intelligence essential for this task.
So, when you watch some of your favorite web series on Netflix or Amazon, you usually get a recommendation for the next show or similar show you should watch. So, how did they know what category you like?
The execution of Artificial Intelligence in marketing has given birth to a new industry that we know as Big Data. Numerous brands use the data collected by the Big Data to understand their target audience’s emotions or mood, what people are talking about that brand, etc.
Similarly, social media channels like Facebook, Twitter, Instagram, and others, read your usage data and use Artificial Intelligence to show similar feeds and advertisements. That looks like a huge success of Artificial Intelligence. Right?
FAQs – Artificial Intelligence
Q1. Where Is AI Used?
Artificial Intelligence is used across various industries worldwide. Some of the major sectors that have delved deep into AI are eCommerce, Security, Retail, and Surveillance. Manufacturing & Production, Sports Analytics, Automotive, among others.
Q2. How Is AI Helping In Our Life?
Virtual digital assistants have transformed the way we do our everyday tasks. Alexa and Siri have grown like real humans we interact with each day for our every small to big needs. The natural language abilities and the capability to learn themselves without human intervention are advancing so quickly and becoming just like humans in their interaction.
Q3. Why Is AI Needed?
Artificial Intelligence makes every procedure better, faster, and more precise. It has some crucial functions, such as recognizing and predicting fraudulent transactions, faster and accurate credit scoring, and physically automating intense data management practices. Artificial Intelligence enhances the current procedure across industries and applications and helps create new solutions to problems that are overwhelming to handle manually.
Q4. What Is Artificial Intelligence With Examples?
Artificial Intelligence is a smart object that humans create. It can execute tasks intelligently without being explicitly instructed to do so. We use Artificial Intelligence in our daily lives without even realizing it. Spotify, Google Maps, Siri, and YouTube all of these applications use Artificial Intelligence for their work.
Q5. Is Artificial Intelligence The Future?
We are presently living in the utmost advancements in Artificial Intelligence in history. It has emerged to be the next big thing in technology and has impacted the future of nearly every industry. According to WEF, 133 million new Artificial Intelligence jobs will be available by Artificial Intelligence by 2022. So yes, AI might be the future.
You can better understand what Artificial Intelligence is through some AI-driven electronics that you mostly used in your daily lives, be it your smartphone, computer, television, car or ATM. Artificial Intelligence has made its root deep inside our lives and is transforming it on a massive scale, only to make life way more effortless.
However, it’s better to let the future decide what other benefits it holds for us, but one thing is sure we’re going to taste a really great era of science and technology for now.
Snehil Masih is a professional technical writer. He is passionate about new & emerging technology and he keeps abreast with the latest technology trends. When not writing, Snehil is likely to be found listening to music, painting, traveling, or simply excavating into his favourite cuisines.