Artificial Intelligence

Artificial Intelligence: A Simple Guide to Understand the Complexities of AI

Artificial Intelligence (AI) is not science fiction anymore. It is a common sight in today’s complex world. AI is the most disruptive technology of all time and has sparked a new industrial revolution. From Apple’s Siri, Google search engine, Tesla’s autonomous vehicle to online stores you use every day, AI is now everywhere.

But what exactly is artificial intelligence? How does it work? How AI is used? This guide will answer all your queries related to AI.

In this guide, you will learn the following concepts about AI:

  • What is AI?
  • A little bit of history
  • What are the AI Components?
  • How does AI work?
  • Stages of Learning in Artificial Intelligence
  • Types of Artificial Intelligence
  • AI Application Categories
  • Use Cases of AI
  • AI Applications in Different Industries
  • Top AI Apps
  • What’s the AI future?

What is AI?

John McCarthy, who is called the father of AI, has given a simple explanation for AI. He says Artificial Intelligence is a science of developing intelligent machines that can do any task that humans can do but intelligently and in less time.

AI is about making machines that can think humanly, think rationally, act humanely and act rationally.

Now, what does that mean? AI makes it possible for machines to learn from experiences (a vast amount of data generated daily) and perform human-like tasks in a short time.

AI-powered systems learn from the mountains of data, perform intelligent searches, interpret texts, videos, and images to identify patterns and then act according to those patterns.

A little bit of history…

We may have heard this term in the recent past but it isn’t actually a new concept.

The history of AI dates back to the 1950s when Alan Turing, a famous mathematician, broke the Nazi encryption machine Enigma. This helped the allied forces to win World War II.

After this breakthrough work, Turing wrote a paper “Computing Machinery and Intelligence”, and created a Turing test to establish the fundamental goal of artificial intelligence.   

Then came the first AI application – translation. In 1954, the Georgetown-IBM machine translated Russian sentences into English automatically. In 1959, three researchers – Allen Newell, Herbert Simon and J.C. Shaw – developed the General Problem Solver (GPS) which imitated human problem-solving.  

The first AI Lab at Stanford was established by John McCarthy.  In the 1980s, corporations and labs started to invest in AI development such as supercomputer, advanced computing, AI programming language, logistics planning and scheduling tool, and more.

At the beginning of the 2000s, more development and breakthroughs were seen in the AI field. DARPA produced intelligent personal assistants in 2003.

STANLEY, a self-driving car, was developed in 2005. Google creates speech recognition in iPhone apps in 2008. Then came IBM’s Watson, neural network, self-driving car, and Google DeepMind.

  1. 1950s–1970s – Neural Networks
  2. 1980s–2010s – Machine Learning
  • Present Day – Deep Learning

Now as you can see AI is not a new thing but has been discovered many years ago. It has been refined in these years and now it can be seen in almost every field.

What are the AI Components?

Machine Learning (ML) – In simple terms, it means learning from experience. ML is a method of data analysis that automates the process of learning from data, identifying patterns and making predictions with minimal human intervention.

Neural Networks – They are computer systems that have been modeled after neural connections in the human brain. Neural networks can label raw input, create patterns, and perform tasks by considering examples.

Deep Learning – Deep learning uses machine learning algorithms and multiple layers of artificial neural networks to extract higher-level information from the raw input.

Cognitive Computing – It is a computerized model that improves the interaction between humans and machines. The model uses a combination of artificial intelligence algorithms, neural networks, machine learning, natural language processing, sentiment analysis and contextual awareness to solve day-to-day problems.

Natural Language Processing (NLP) – It is a technology that helps computers to understand the human’s natural language. Syntactic analysis and semantic analysis are used to complete Natural Language Processing tasks.

Computer Vision – Computer vision focuses on replicating the human vision system to enable computers to identify and process objects in the same way that humans do.

How does AI work?

AI is not a computer system. A normal desktop or PC simply executes our given commands but the Artificial Intelligence-powered system does a task through a consent learning process just like a human being would do.

It has been found in different studies that AI will be 20 times much intelligent than a human being in the coming years. But what makes it intelligent? How does the entire AI system work?

AI combines large amounts of data and applies iterative processing and intelligent algorithms to allow the software to learn automatically from patterns derived from the data. 

AI technology takes the help of machine learning, deep learning, neural networks, NLP, cognitive learning, and computer vision for data analysis and model creation. It then detects patterns in the environment and learns from those patterns.

Additionally, several technologies support AI to perform tasks intelligently, including graphical processing units (GPUs), application programming interface, Internet of Things, and advanced algorithms.

Learning Stages in Artificial Intelligence Learning Stages in Artificial Intelligence

There are three stages of learning in Artificial Intelligence. Let’s understand each stage in depth.

1. Artificial Narrow Intelligence-This type of AI can perform only a narrowly defined set of tasks. A machine at this stage can perform pre-defined tasks without any thinking ability. These examples might help you understand this AI better – Siri, Alexa, and self-driving cars. Uber has already launched self-driving trucks for beer delivery.

2. Artificial General Intelligence-An AI-powered machine at this stage possesses the ability to think and make decisions just like humans. Unlike ANI, it can improve itself to perform various tasks. Example – AlphaGo – it is the first computer program to defeat a professional human Go player.

3. Artificial Super Intelligence– Artificial Super Intelligence is the stage wherein computers or systems will surpass human beings. With technological advancement, this stage is not so far when machines can do better than humans.

Types of Artificial Intelligence

Artificial Intelligence systems can be categorized based on their functionalities. Here are the following types of AI: Image reference-McKinsey&Company

1. Reactive Machines :Deep Blue, a chess-playing supercomputer developed by IBM, which defeated international chess player Garry Kasparov in the1990s, is the best example of a reactive AI machine. These types of AI machines perceive the world directly and act on what they see.

2. Limited Memory AI: This class of AI machines can look into the past and act based on that past behavior. Self-driving cars are an example of limited AI machines. For instance, they observe other cars’ speed and direction and take help of pre-programmed representations of the world to slower or move a car.

3. Theory of Mind AI: In simple terms, the theory of mind refers to the ability of understanding that mental states such as beliefs, desires, goals, and intentions are different in every human being.

A machine with a theory of mind is useless if it does not make a human being feel that it is interacting with another being. They will adjust their course of action accordingly. This kind of AI is a work-in-progress.

4. Self-aware AI: Computers equipped with this type of AI will be able to understand themselves. We have attained self-awareness, but this type of artificial intelligence is still a probability.

Applications of AI

AI is important for solving immensely difficult issues in various industries. AI applications can be grouped into five categories:

Reasoning: Generation of new knowledge by inference and logical deduction. AI collects structured and unstructured data, organize them, and use statistical inferencing to predict or deduce unknown factors hidden in the data. Examples of AI reasoning include financial asset management, games, financial applications, and legal systems.

Automated Planning: It is about teaching a machine to plan ahead. This helps to set goals and achieve them on time. Examples of AI planning are inventory management, forecasting demands, predictive maintenance, scheduling, logistics, among others.

Real-time Communication: AI algorithms have the ability to make machines understand spoken and written languages and reply to them accurately. Translation apps, voice control devices, chatbots are examples of real-time communication powered by AI algorithms.

Knowledge: AI simplifies knowledge discovery. AI enhances the ability of systems to collect, store, and share knowledge rather than information. Some examples of AI use in knowledge management include fraud prevention, music creation, medical diagnosis, and video or product recommendation.

Perception: AI allows you to perceive reality and surroundings in new ways. With the help of AI technology, systems can infer things from sounds, images, videos, and other things. Image and voice recognition tools, surveillance systems, and autonomous vehicles are examples of how AI can help the machine improve their perception.

Use Cases of AI

Whether you agree or not, AI has a massive impact on our daily lives. From helping us do our jobs efficiently to enabling businesses to increase productivity, AI applications are limitless and endless.

AI Autopilots in Airplanes

Surprised? AI autopilots in commercial airlines are the early use of AI technology and it date backs to 1914. A commercial flight includes only 7-min of human-steered flying and the rest is controlled through AI autopilot.

 Ridesharing Apps

Do you use Uber for the daily commute? Do you know about Lyft? Have you ever thought about how these ridesharing apps decide the price of your ride or minimize your wait time? Uber uses machine learning to determine ETAs for rides and optimal pickup locations.

Social Media

Artificial intelligence has improved how we communicate and locate friends or target customers. For instance, Instagram and Facebook use AI to target advertising and fight cyber bullying and delete offensive comments.

 Email Communications

Yes, AI is used in email communications too! Gmail uses AI to ensure that all the emails that are landing in your inbox are authentic. For this, it uses filters like Primary,Social,Promotions,Updates, Forums and Spam. Smart replies and nudging reminders in Gmail are other applications of AI.

 eCommerce Stores

Amazon, Flipkart, Walmart, and other online stores use AI to gather information about your preferences and buying habits. Product recommendations and exclusive offers are based on this information collected by their AI tools. The same is the case with music recommendation by Spotify and Google Play.

Video Streaming Apps

Netflix, Amazon Prime, and other video streaming platforms use AI to personalize their services. They collect behavioral data from millions of subscribers and use them to recommend the best movies, shows, and series for you. They also use machine learning to identify possible server problems and service interruptions.

Google, Smart Assistants, and Chatbots

Google search engine has evolved over time by studying the natural language used in search queries. Its AI tool learns from questions asked by users and results and then adapt over time to satisfy the needs of users.

Smart personal assistants like Google Home, Alexa, Siri, etc uses voice-to-text technology to help set reminders, play music, book an Uber, switch off lights, and more. Similarly, chatbots help you complete your shopping, errands, and day-to-day tasks just with a conversation.

AI Applications in Different Industries

AI has become an integral part of every business. It can solve immensely difficult issues in various industries, such as finance, education, health, commerce, transport, and more. AI applications in different industries are mentioned here:

  1. AI and Retail

The retail sector is the leading investor in AI. It is expected to invest more than $4 billion in AI in the next year. Retail is currently using AI for product recommendation. The retail sector will use AI for customer services, product purchases, and automation of operations on different channels. 

  1. AI and Healthcare

The healthcare sector is using AI apps and software for telediagnosis, robotic surgery, virtual nurses, physician scheduling, automated follow-up of patients, and intelligent emergency triage. Computerized X-ray vision can detect diseases, natural language processing is now being used for drug discovery and safety, and ML helps to find patterns within a population.

It has been found that clinical health AI applications can potentially create $150 billion in annual savings for the U.S. healthcare economy alone by 2026.

  1. AI and Energy and Mining

A study conducted by Infosys found that 29% of energy companies have applied AI and ML in their operations and are satisfied with the results. For instance, cognitive AI is now used to track tankers to determine when they leave port or when they reach the destination, refinery destination and arrival times, and reactive recovery.

AI algorithms and tools are used for asset management, diagnostics, mine area identification, and prognostics to enable seamless autonomous operation.

  1. AI and Insurance

Only 5% of insurance companies are using AI technologies, which will increase significantly in the next 10 years. Presently, machine learning is used to calculate the price of insurance policies and recommend useful products to customers.

AI is used to recognize fraud patterns and fraudulent claims. Auto insurance companies are also making intelligent use of AI-powered apps to detect the chance of road accidents and provide insurance accordingly. Liberty Mutual is a US-based insurance company which has developed an app.

The app allows drivers to determine damage to their cars in real-time after an accident through their smartphone camera.  

  1. AI and Supply Chain

According to the report, State of Artificial Intelligence for Enterprises, the supply chain is the top industry that is earning high revenue from AI investment. IBM’s Watson is used to gain insights and productivity in supply chain management. AI can analyze supplier-related data to make better supplier decisions and improve its customer service.

Alibaba and Amazon have transformed their warehouses into a smart warehouse using mini robots and AI-based machines. Supply chain companies are using C3’s AI-powered Inventory Optimization to manage inventory levels in real-time across purchase parts, components and finished goods. 

  1. AI and Tourism

A report by Travelzoo reveals that 80% of travel assistants will be robots by 2020.

The use of chatbots in tourism-related websites has increased in recent years to provide assistance to travelers. Not just chatbots, but companies have developed face-to-face robots too for customer assistance. A

I robot ‘Connie’, deployed by Hilton, uses AI and speech recognition to provide tourist information to customers who ask questions to it. The Dorchester Collection hotel uses AI programs to analyze customer feedback in order to get a clear picture of current opinion in real-time.

  1. AI and Customer Service

78% of brands say they are planning to implement artificial intelligence and virtual reality by 2020 to better serve customers. A recent Zendesk study showed that 42% of B2C customers showed more interest in purchasing after experiencing good customer service.

52% of customers stopped purchasing due to a single disappointing customer support interaction.

AI integrated systems used by customer service providers capture infinite online data to identify customer issues, define customer behavior patterns, determine their frequent decisions and preferences, respond with suitable products, suggest personalized offers and discounts, resolve issues before they arrive, and minimize customer complaints.

Not just these industries, AI is redefining other industries like manufacturing, fashion, education, agriculture, IT service, and many more by automating processes, innovative solutions, and personalized services.

Top AI Applications

  1. DataBot
  • Creates customized multimedia presentations using voice, text and images
  • Allows you to share answers using SMS, email, etc.

Cost: Free

  1. FaceApp
  • It allows you to age yourself
  • Change gender
  • Improve images with various filters, etc.

Cost: Free 

  1. Google Assistant
  • Make quick phone calls on-the-go
  • Set reminders as well as text messages
  • Navigate places and receive updates
  • Get weather information

Cost: Free 

  1. Hound
  • Search, discover and play music
  • Get the latest news very quickly
  • Book cabs, know weather, plan travel and more

Cost: Free 

  1. Robin
  • Create personalized playlist
  • Send the text by voice, set reminders and alarms
  • Get directions

Cost: Free 

  1. Socratic
  • It supports subjects like Maths, Science, Chemistry, History, English, Economics, etc.
  • Explains topics instantly
  • Curated the best online education videos, etc.

Cost: Free

  1. Magisto

An effective tool for video editing

Edits and asks what your preferred style

Make marketing videos

Cost: Free 

  1. Microsoft Seeing AI
  • Helpful for people with limited senses and mobility
  • Talking camera application
  • It analyzes whatever the camera is seeing

Cost: Free

  1. Youper
  • Emotional health assistant application
  • Guides users through personalized meditations
  • Tracks users’ mood

Cost: Free

 

What’s the future of Artificial Intelligence  

Instead of asking what is the future of AI, we should question how will it affect our future. 10-20 years from now, we will see robots that work and think like humans, cars will drive you to your office, smart homes will become better, robots will help old people at home, the fridge will give you health tips, a country will have only smart cities, and automated transportation will become common.

To date, Only 23% of businesses have incorporated AI into processes and product or service offerings. 61% of business professionals point to machine learning and AI as their company’s most significant data initiative for next year. IDC forecasts 75% of commercial enterprise apps will use AI by 2021. That’s why the AI market is expected to grow to a $190 billion industry by 2025.

Top business decision-makers and tech leaders believe that AI adoption can boost productivity, create jobs, enhance product features, improve service, optimize internal business processes, automate repetitive tasks, and enable employees to concentrate on meaningful works.

So are you ready to integrate AI tools and apps into your existing processes and systems? Do you want to innovate the way people work, perform, and do other tasks through AI? Contact Fuel4Media to discuss your innovative idea. We specialize in building intelligent products, backed by the power of AI, that companies love and users enjoy.

We make products “great” through simplified coding, engaging designs, and AI capabilities. Contact our AI expert to get assistance for your next AI idea – be it a robotic process automation system, AI app, chatbot or AI software.

 

Naveen Gupta

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Naveen Gupta

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