Emerging Trends – Notes

Emerging Trends

Emerging trends

Emerging trends are the state-of-the-art technologies, which gain popularity and set a new trend among users.

New technologies and initiatives emerge with each passing day. Some of these new technologies prosper and persist over time, gaining attention from users. Emerging trends are the state-of-the-art technologies, which gain popularity and set a new trend among users.

Artificial Intelligence (AI)

Artificial Intelligence endeavours to simulate the natural intelligence of human beings into machines, thus making them behave intelligently.

An intelligent machine is supposed to imitate some of the cognitive functions of humans like learning, decision making and problem solving.

Knowledge Base – A knowledge base is a store of information consisting of facts, assumptions and rules which an AI system can use for decision making.

For example – Google Maps guiding the fastest route on the basis of real data, uploading photo on social sites and your friends come to know, Siri, Google Now, Cortana, Alexa etc.-

Machine Learning

Machine Learning is a subsystem of Artificial Intelligence, wherein computers have the ability to learn from data using statistical techniques, without being explicitly programmed by a human being and make predictions.

Models are the algorithms that used in Machine Learning.

Firstly models are trained and tested using a training data and testing data, respectively. After successive trainings, once these models are able to give results to an acceptable level of accuracy, they are used to make predictions about new and unknown data.

Natural Language Processing (NLP)

Natural Language Processing (NLP) deals with the interaction between human and computers using human spoken languages, such as Hindi, English, etc.

An NLP system can perform text-to-speech and speech-to-text conversion.

Application of NLP :

  • Search the web or operate or control our devices using our voice.
  • Predictive typing feature of search engine or smartphone, which suggesting the next word while typing.
  • Spell checking features.
  • Automated customers service, computer interact with human to solve their queries or complaints.
  • Translate texts from one language to another with fair amount of correctness.

Immersive Experiences

Immersive experiences allow us to visualise, feel and react by stimulating our senses. It enhances our interaction and involvement, making them more realistic and engaging.

Immersive experiences have been used in the field of training, such as driving simulators , flight simulator and so on.

Immersive experience can be achieved by using

  • Virtual Reality (VR) and
  • Augmented Reality (AR)

(A) Virtual Reality

Virtual Reality (VR) is a three-dimensional, computer-generated situation that simulates the real world. The user can interact with and
explore that environment by getting immersed in it while interacting with the objects and other actions of the user.

At present, it is achieved with the help of VR Headsets.

Applications of VR :- Gaming, military training, medical procedures, entertainment, social science and psychology, engineering and
other areas where simulation is needed for a better understanding and learning.

(B) Augmented Reality

The superimposition of computer generated perceptual information over the existing physical surroundings is called as Augmented Reality (AR).

Users can access information about the nearest places with reference to their current location. They can get information about places and choose on the basis of user reviews.

Location-based AR apps are major forms of AR apps, used by travellers to access real-time information of historical places just by pointing their camera view finder to subjects.

Robotics :-

Robotics is an interdisciplinary branch of technology requiring applications of mechanical engineering, electronics, and computer science, among others. Robotics is primarily concerned with the design, fabrication, operation, and application of robots.

Robots :-

A robot is basically a machine capable of carrying out one or more tasks automatically with accuracy and precision.

Unlike other machines, a robot is programmable by a computer, which means it can follow the instructions given through computer programs.

Robots were initially conceptualised for doing repetitive industrial tasks that are boring or stressful for humans or were labour intensive.

Types of Robots:

  • Wheeled robots –

NASA’s Mars Exploration Rover (MER) mission is a robotic space mission to study about the planet Mars

  • Legged robots,
  • Manipulators,
  • Drone –

A drone is an unmanned aircraft which can be remotely controlled or can fly autonomously through software-controlled flight plans in their embedded systems, working in conjunction with onboard sensors and GPS.

Used in journalism, filming and aerial photography, shipping or delivery at short distances, disaster management, search and rescue
operations, healthcare, geographic mapping and structural safety inspections, agriculture, wildlife monitoring or pooching, besides law-enforcement and border patrolling

  • Humanoids – Robots that resemble humans are known as humanoids.

Sophia is a humanoid that uses artificial intelligence, visual data processing, facial recognition and also imitates human gestures and facial expressions.

Big Data

The generation of data sets of enormous volume and complexity called Big Data.

Big data is generated by a billion Internet users. Around 2.5 quintillion bytes of data are created each day, and the pace is increasing with the continuous evolution of the Internet of Things (IoT).

Processing of Big Data

Big data cannot be processed and analyzed using traditional data processing tools (DBMS) as the data is not only voluminous but also unstructured like our posts, instant messages and chats, photographs that we share through various sites, our tweets, blog articles, news items, opinion polls and their comments, audio/video chats, etc.

Challenges with Big Data

Big Data not only represents voluminous data, it also involves various challenges like integration, storage, analysis, searching, processing, transfer, querying and visualization of such data.

Characteristics of Big Data

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