How AI is being used in Market Research and Other Industries and its Impact
If you looked up Google's word "artificial intelligence" and ended up in this article somewhere, or commuted to work with Uber, you used AI.
Artificial intelligence has endless examples that influence our lives. Although some people call this the idea of "robots taking over the world in an evil genius way," it is difficult to argue that by saving us tons of time , money and energy, artificial intelligence has made life easy.
Artificial Intelligence refers to the phenomenon where, through being able to understand, interpret, and learn from data through specially built algorithms, a computer functions as a blueprint of the human mind. Machines that are artificially intelligent will remember patterns of human behavior and adapt according to their preferences.
Machine learning, deep learning and natural language processing (NLP) are the main concepts closely linked to AI that you can come across over the course of our discussion. Before we go on, let's make sense of them.
Machine Learning (ML) involves teaching machines to understand essential concepts by examples by means of big data that needs to be organized for the machines to understand (in machine language). Through feeding them the correct algorithms, this is all done.
Deep Learning is a step ahead of ML, meaning it learns by representation, but for it to make sense of it, the data does not need to be organized. This is because of the human neural structure that inspires artificial neural networks.
A linguistic method in computer science is Natural Language Processing (NLP). It allows the reading and comprehension of human language by machines. NLP enables human language data to be automatically interpreted and enables the interaction of two people (computers and humans) that speak different languages.
Practical Uses of AI in different Domains:
Text Editors or Autocorrect
There are inbuilt or downloadable auto-correcting resources for editors when you type out papers, which search for spelling errors, grammar, readability, and plagiarism depending on their level of complexity.
It must have taken you a while before you were fluent in it to understand your language. Similarly, machine learning, deep learning, and natural language processing are now used by artificially intelligent algorithms to recognise incorrect language use and propose corrections.
As you were taught at school, linguists and computer scientists work together to teach grammar to machines. Machines are fed with copious quantities of high-quality language knowledge arranged in such a way that it can be understood by machines. But the editor can mark it red and prompt feedback when you use even a single comma incorrectly.
The next time you have your document reviewed by a language editor, know that one of the many examples of artificial intelligence is being used.
Search and Recommendation Algorithms
Have you found that the things recommended to you are completely matched with your desires when you want to watch your favorite films or listen to songs or maybe shop online? This is AI's grace.
From your online activities, these smart recommendation systems learn your actions and preferences and give you similar content. By continuous training, the customized experience is made possible. At the front end (from the user), the data is processed, stored as big data and analyzed through machine learning and deep learning. Then, through suggestions that keep you entertained without having to look any further, it is able to predict your tastes.
Similarly, another instance of artificial intelligence is the optimized search engine experience. Our top search results usually have the response we're searching for. How is it happening?
To recognize high-quality content over SEO-spammed, bad content, quality controlling algorithms are fed with data. This helps to create an ascending order of search results for the best user experience, based on consistency.
Natural language processing technology allows these applications to understand humans because search engines are composed of codes. In reality, by collecting top-ranked searches and predicting their queries when they start to type, they are also able to predict what a human wants to ask.
New features such as voice search and image search are continuously being programmed into computers as well. You can easily hold your phone up to it if you want to locate a song that is playing in a mall, and a music-identifying app can tell you what it is in seconds. The computer will also tell you all of the information relevant to that song after sifting through the rich database of songs.
As a consumer, it can be time consuming to get queries answered. The use of algorithms to train machines to cater to customers that chatbots is an artificially intelligent solution to this. This helps machines to answer FAQs and take orders and track them.
By natural language processing ( NLP), chatbots are trained to impersonate the conversational styles of customer representatives. Advanced chatbots do not need complex input formats (e.g., yes / no questions) anymore. They will answer difficult questions that require thorough answers. When, in reality, they are just another example of artificial intelligence, they can give the appearance of a customer representative.
The bot will recognise the error it made and fix it the next time, ensuring full customer satisfaction, if you offer a bad rating for the response you receive.
We frequently resort to ordering robotic assistants to execute tasks on our behalf when we have our hands full. You could ask the assistant to call your mom while you're driving with a cup of coffee in one hand. For example, the assistant, Siri, can access your contacts, recognize the word 'Mom,' and call the number.
Interestingly, Siri is old news, as it is an instance of a lower-tier model that can only respond to and not provide complex answers when spoken to. In human language, the new digital assistants are well-versed and implement advanced NLP and ML. They understand complicated inputs of commands and have satisfactory outputs. They have adaptive capabilities that can determine your needs, timetables, and behaviors. This helps them, in the form of reminders, prompts and schedules, to systemize, arrange and prepare things for you.
With excessive freedom of expression, the rise of social media brought the world a new narrative. This brought some social evils, however, including cybercrime, cyberbullying, and hate speech. Various social media apps use AI support to handle these issues and include other entertaining functionality for users.
AI algorithms can spot and easily take down posts that include hate speech much faster than people can. This is made possible by their ability to recognise keywords, phrases, and symbols of hostility in various languages. These have been fed into the framework, which has the extra capacity to add to its dictionary neologisms. A significant component of this method is the neural network architecture of deep learning.
Emojis have been the perfect way for different feelings to be portrayed. AI technology also understands this digital language because, as part of predictive text, it can understand the connotation of a certain piece of text and prompt the right emoji.
A perfect example of artificial intelligence , social media also has the potential to understand the kind of content with which a person resonates and offers similar content to them. In social media accounts, the facial recognition feature is also used, helping individuals tag their friends with automated recommendations. Smart filters can detect spam or unwanted messages and automatically weed them out. Another feature that users can enjoy is Smart Answers.
Many of the social media industry's future plans include using artificial intelligence to recognise mental health concerns such as suicidal thoughts by analyzing the shared and consumed content. This can be forwarded to clinicians in mental health.
When they go beyond human capabilities, artificially intelligent algorithms act when time-savers, enabling scientists to spend their resources in other more meaningful discoveries.
In addition to serving as a source of entertainment, the examples of artificial intelligence that we have mentioned also include countless services on which we have become so reliant. The area of artificial intelligence is still young and many more developments are yet to come that can mimic human capabilities even more accurately.