ArtsAutosBooksBusinessEducationEntertainmentFamilyFashionFoodGamesGenderHealthHolidaysHomeHubPagesPersonal FinancePetsPoliticsReligionSportsTechnologyTravel

Everything You Need To Know About Artificial Intelligence.

Updated on June 19, 2019
Kavithaarumugam profile image

Kavitha is an Engineer and a data science enthusiast who has done many online MOOC offered by top universities like MIT, UC Sandiego.

What is Artificial Intelligence?

Artificial intelligence
Artificial intelligence
  • Artificial intelligence is a field of computer science that embeds human-like intelligence into computers, and it is developed to extend human capabilities and not to replace humans.
  • AI enables computers to find the common pattern in data without humans having to code them manually.
  • The only innate intelligence that computers have is what we provide to them. computers use that intelligence to learn from the examples and create machine learning models based on the inputs and desired outputs.

Types of Artificial Intelligence:

Applied AI
Generalized AI
Conscious AI
Applied AI is used to do only a specific task. Examples for this type of AI are language translators, self-driving cars, virtual assistants, recommendation engines, AI-powered web searches, and spam filters.
This type of AI can perform a wide variety of independent and irrelevant tasks.
This AI type is self-aware AI that it can completely imitate human-level intelligence.
It cannot learn new things and make decisions from training data.
It can learn new things from experience to solve problems and it does this by teaching itself new approaches.
But still, we can't figure out what kind of consciousness that we able to give to it. So, it is improbable to say that we will create conscious AI in the near future.

Task Domains of AI:

Ordinary task
Formal task
Expert task
Computer vision
Mathematics
Engineering
speech and voice recognition
Games
Financial analysis
Natural language processing
verification
Scientific analysis
Reasoning and motion
Theorem proving
Medical diagnosis

Related Concepts and subsets of AI:

Terminology and Related Concepts of AI
Terminology and Related Concepts of AI

Machine Learning:

  • It is a subset of artificial intelligence that provides computer the ability to learn, without being explicitly programmed.
  • Machine learning models are the algorithms used to find common patterns in the data without the involvement of humans.
  • It does not follow rules-based algorithms instead of that it develops models to classify and make predictions from data.
  • In machine learning, we split datasets into three subsets. They are training, validation, and test sets.
  • Training subsets are the datasets used for training of algorithms.
  • Validation subset is used to validate the result and to tune the algorithm parameters.
  • The testing subset is the dataset that never used before, and it is used to evaluate how good our model is.

Types of Machine Learning Techniques:

Machine learning techniques
Machine learning techniques

Supervised Learning:

  • It relies on datasets with a class label, and we use these datasets to build classification models.
  • Human-labeled data is used to train the algorithms.
  • The accuracy of the model depends on the volume of datasets, which have provided for the training. As the volume of training datasets increases, then the accuracy of the result provided by the model will also increase.
  • The supervised learning subdivides into three categories, and they are regression, classification, and neural networks.

Unsupervised Learning:

  • The datasets used for unsupervised learning does not contain class labels and letting the algorithm to discover class labels from unstructured data.
  • This type of learning is helpful in clustering the data, where the data grouped according to how similar it is to its neighbors and dissimilar to everything else.

Reinforcement Learning:

  • It uses a reward function to penalize bad actions or reward good functions.
  • It has provided with a set of rules and constraints, and letting it learn how to achieve its goal.

Deep Learning:

  • Deep learning layers algorithm to create layers of neural networks that imitate the structure and function of the human brain.
  • It continuously learns from unstructured data to improve the accuracy of results.
  • It enables the natural language understanding of AI systems and allows them to work on context and intent of what is being conveyed by a sentence.
  • It does not directly connect input and output rather than that it contains several layers of processing units, which connects the one layer of output to the input of another layer.
  • It contains many layers between input and output, and that's why it is called deep learning.
  • The Engineers and developers decide the number of layers and the type of functions that connects the layers. Then they train the model with lots of examples.

Artificial Neural Networks:

  • Artificial neural networks are developed to mimic biological neural networks.
  • It is the collection of small units called neurons, which is a computational unit. It takes incoming data and learns to make decisions over time like the human brain.
  • Neural networks learn through a technique called backpropagation. Backpropagation uses a set of training data that match known input to output.
  • A collection of neurons is called a layer. A layer takes input and provides output. Each neural network contains one input layer and one output layer, between these input and output layers it contains many hidden layers.
  • A neural network that contains more than one hidden layer is called a deep neural network.

Types of Neural Networks:

Types of neural networks
Types of neural networks

Perceptrons:

  • This is an uncomplicated and old neural network.
  • This is a single-layered neural network in which the input nodes connected directly to an output node.
  • The input layer transfers the input values to the next layer by multiplying it with a weight and summing the result.

Convolutional Neural Network (CNN):

  • CNN is a multilayer neural network that mimics the animal visual cortex.
  • A convolution is a mathematical operation that applies one function as an input to other function and provides an output, which is the mixture of two functions.
  • Convolution is good at detecting simple structures in an image and mixes those simple structures to form a complex feature.
  • Image processing, video processing, and natural language processing are the main applications of CNN.

Recurrent Neural Networks:

  • It is known as recurrent neural networks because it repeats the same task for every element of a sequence by feeding the prior outputs as an input to the subsequent stages.

Applications of Artificial Intelligence:

Artificial intelligence is a field which has shown discernible growth over the past decades. It has vast application in various fields. Here, I have mentioned some of its application.

Natural Language Processing:

  • Natural language processing is the subset of artificial intelligence that enables computers to understand human's natural language with the help of machine learning and deep learning algorithms.
  • It breaks down sentences grammatically, relationally, and structurally to discern the semantic meanings of words.
  • It might understand the emotional intent of a sentence, which means it might understand whether you are asking a question out of frustration, depression or confusion.
  • Computers convert text-to-speech and speech-to-text with the help of natural language processing, which enables computers to communicate more interactively with humans. Text-to-speech is also known as voice synthesis.
  • In business, AI-powered voice synthesis is used to enhance the customer experience.
  • In medicine, voice synthesis technology is used to help ALS patients to regain their true voice instead of using a computerized voice.

Computer Vision:

  • Computer vision focuses on the replication of the human visual system, and it enables the computer to process the objects in the images and videos in the same way as humans do.
  • This technology helps self-driving cars to make sense of their surroundings.
  • It plays a crucial role in facial recognition applications in which computers match the facial images of the people to their identity.
  • It plays a vital role in augmented and mixed reality in which computing devices are allowed to overlays or embed virtual images on the real world images.
  • It is helping doctors to arrive with a preliminary diagnosis by finding symptoms in X-ray and MRI scans and it can even detect cancerous moles in skin images.

Robotics:

  • Humanoid robots have become possible due to the advancement of artificial intelligence. These robots are designed to do specific tasks.
  • Android robots are kind of humanoid robots that aesthetically resembles human. For instance, Ai-Da is an android robot created to do paintings.
  • Collaborative robots(cobots) are used to lift heavy containers.
  • Robots are used to trigger specific movements in the human body to create new neural pathways in the brain and it is done by detecting patterns in massive movement related datasets of patients with neurological damage.

Infographics :

Infographics about Artificial intelligence
Infographics about Artificial intelligence

© 2019 Kavitha A

Comments

    0 of 8192 characters used
    Post Comment

    No comments yet.

    working

    This website uses cookies

    As a user in the EEA, your approval is needed on a few things. To provide a better website experience, hubpages.com uses cookies (and other similar technologies) and may collect, process, and share personal data. Please choose which areas of our service you consent to our doing so.

    For more information on managing or withdrawing consents and how we handle data, visit our Privacy Policy at: https://hubpages.com/privacy-policy#gdpr

    Show Details
    Necessary
    HubPages Device IDThis is used to identify particular browsers or devices when the access the service, and is used for security reasons.
    LoginThis is necessary to sign in to the HubPages Service.
    Google RecaptchaThis is used to prevent bots and spam. (Privacy Policy)
    AkismetThis is used to detect comment spam. (Privacy Policy)
    HubPages Google AnalyticsThis is used to provide data on traffic to our website, all personally identifyable data is anonymized. (Privacy Policy)
    HubPages Traffic PixelThis is used to collect data on traffic to articles and other pages on our site. Unless you are signed in to a HubPages account, all personally identifiable information is anonymized.
    Amazon Web ServicesThis is a cloud services platform that we used to host our service. (Privacy Policy)
    CloudflareThis is a cloud CDN service that we use to efficiently deliver files required for our service to operate such as javascript, cascading style sheets, images, and videos. (Privacy Policy)
    Google Hosted LibrariesJavascript software libraries such as jQuery are loaded at endpoints on the googleapis.com or gstatic.com domains, for performance and efficiency reasons. (Privacy Policy)
    Features
    Google Custom SearchThis is feature allows you to search the site. (Privacy Policy)
    Google MapsSome articles have Google Maps embedded in them. (Privacy Policy)
    Google ChartsThis is used to display charts and graphs on articles and the author center. (Privacy Policy)
    Google AdSense Host APIThis service allows you to sign up for or associate a Google AdSense account with HubPages, so that you can earn money from ads on your articles. No data is shared unless you engage with this feature. (Privacy Policy)
    Google YouTubeSome articles have YouTube videos embedded in them. (Privacy Policy)
    VimeoSome articles have Vimeo videos embedded in them. (Privacy Policy)
    PaypalThis is used for a registered author who enrolls in the HubPages Earnings program and requests to be paid via PayPal. No data is shared with Paypal unless you engage with this feature. (Privacy Policy)
    Facebook LoginYou can use this to streamline signing up for, or signing in to your Hubpages account. No data is shared with Facebook unless you engage with this feature. (Privacy Policy)
    MavenThis supports the Maven widget and search functionality. (Privacy Policy)
    Marketing
    Google AdSenseThis is an ad network. (Privacy Policy)
    Google DoubleClickGoogle provides ad serving technology and runs an ad network. (Privacy Policy)
    Index ExchangeThis is an ad network. (Privacy Policy)
    SovrnThis is an ad network. (Privacy Policy)
    Facebook AdsThis is an ad network. (Privacy Policy)
    Amazon Unified Ad MarketplaceThis is an ad network. (Privacy Policy)
    AppNexusThis is an ad network. (Privacy Policy)
    OpenxThis is an ad network. (Privacy Policy)
    Rubicon ProjectThis is an ad network. (Privacy Policy)
    TripleLiftThis is an ad network. (Privacy Policy)
    Say MediaWe partner with Say Media to deliver ad campaigns on our sites. (Privacy Policy)
    Remarketing PixelsWe may use remarketing pixels from advertising networks such as Google AdWords, Bing Ads, and Facebook in order to advertise the HubPages Service to people that have visited our sites.
    Conversion Tracking PixelsWe may use conversion tracking pixels from advertising networks such as Google AdWords, Bing Ads, and Facebook in order to identify when an advertisement has successfully resulted in the desired action, such as signing up for the HubPages Service or publishing an article on the HubPages Service.
    Statistics
    Author Google AnalyticsThis is used to provide traffic data and reports to the authors of articles on the HubPages Service. (Privacy Policy)
    ComscoreComScore is a media measurement and analytics company providing marketing data and analytics to enterprises, media and advertising agencies, and publishers. Non-consent will result in ComScore only processing obfuscated personal data. (Privacy Policy)
    Amazon Tracking PixelSome articles display amazon products as part of the Amazon Affiliate program, this pixel provides traffic statistics for those products (Privacy Policy)
    ClickscoThis is a data management platform studying reader behavior (Privacy Policy)