Did you know the fascinating ways various popular companies these days are employing technology to make the whole user process more convenient for their customers?
One such technology that is taking the world by storm and is being effortlessly adopted by many corporations is of course, Artificial Intelligence (AI). This intriguing technology offers a massive range of applications across various industries. From reaching out to customers to helping enhance their operations, businesses across sectors have exposed themselves to AI.
In our previous blog on Artificial Intelligence, we’ve already talked about how this technology has seeped its path into our daily lives in ways that we may not even realize. Every time we perform everyday actions such as doing a Google search or booking a trip on an online portal, getting a product recommendation from Amazon, or opening our Facebook newsfeed, AI is always shrouded in the background, its powerful presence subtle yet absolute.
While I’m definitely not referring to the level of power that AI seems to hold in movies or television series like Blade Runner or Westworld, the reference here is primarily to the AI technologies which have been propelling much of our voice and non-voice based interaction with machines, in other words, you could call it the machine learning phase of the Digital Age.
As popular tech giants and acclaimed firms like Apple, Google and Tesla introduce path breaking updates and transformations in how the society operates and converses with machine learning technology, plenty of us still remain perplexed on how AI is being adopted by big and small companies in our present world.
Since 2017, Twitter has been employing artificial intelligence and natural language processing to assess a sea of tweets per second and gauge what tweets each of its users would find most relevant and interesting.
Upon being condemned over not taking action to put a stop to the hate tweets on its platform, Twitter has employed AI to cope with the issue. The technology is also being employed for adopting algorithms to flag any racist or extremist content on its platform by sifting through the massive quantity of tweets posted every day. Yet another subtle way that twitter is employing AI is by using this technology to allow its users to crop photos. The platform adopts neural networks for detecting the most compelling portion of a photo for displaying on the thumbnail.
Netflix is one tech giant that has put Artificial Intelligence and data at the heart of its operations. The company employs carefully developed AI algorithms to recommend new content to its users. The personalized content feed that we see every time we open the platform is created by filtering through a massive volume of data and adopting AI. Artificial intelligence is also used by Netflix to auto generate personalized thumbnails for its users.
Yet another area where Netflix employs AI is in its optimized streaming. Netflix is even employing Artificial Intelligence during the pre-production of its original shows and movies, for instance by scanning the availability of prospective actors and their locations to scout out the perfect area for the shoot. You can learn further about this topic with one of our previous blogs.
Google’s employment of AI is related to its interest in Deep Learning, where artificial neural networks simulate the way the human brain processes data. It all began with the Google Brain project in 2011, which was a neural network developed for image recognition. Google also makes excellent use of AI through its Google Assistant which enables both voice as well as text entry, making use of natural language processing. It facilitates various services, from voice commands, voice searching, voice-activated device control to translating in real-time, etc.
Across Google services, deep learning has been employed in everything from natural language processing to offering user recommendations in the case of YouTube. Its open-source TensorFlow machine learning programming platform allows users to create their own neural network solutions. AI is also driving Google’s self-driving car endeavors, adding deep learning algorithms into its autonomous vehicles.
Uber employs AI for detecting frauds, evaluating risks, during safety processes, for marketing spend and allocation, for pairing drivers and riders, optimizing the route as well as in various remaining parts of its application.
Having over a million customers, Uber is highly devoted to its customer service. The customers seeking help or support are required to be connected to the most relevant agents in the department, a task which is carried out flawlessly by AI.
AI also assists its agents with appropriate responses for customer inquiries, making this an aspect where Uber has shown over 10% enhancement in efficiency as well as simultaneous leaps in customer satisfaction.
AI is at the heart of some of Amazon’s most popular efforts. The most important aspect where AI has been incorporated by Amazon is Alexa, Amazon’s voice-controlled virtual assistant which employs natural language processing as well as machine learning for handling user queries and executing actions such as ordering products or managing smart home devices.
When it comes to Amazon Go convenience stores, machine vision as well as algorithms helps in tracking when customers select items for making purchases in the absence of human cashiers. Amazon’s product recommendation technology which makes the platform distinguished for all its users interprets user purchases for suggesting items which customers might prefer to buy in the future.
Apple has always remained devoted to AI in its operations, making it convenient for developers to design apps which could tackle machine learning in case of Apple devices. By using Core ML, developers gain access to machine learning tools to perform common tasks which include image recognition. In 2018, Apple introduced Create ML, a toolkit that makes it possible for developers to learn the basics of how to build machine learning models.
As the iPhone X was introduced, Apple added a neural engine to its A11 processor to accelerate AI-specific tasks. Combined with developer tools, new and experienced developers alike can conveniently build applications that take full benefit of machine learning capabilities as well as AI-focused hardware.
Yet another area where Apple makes excellent employment of Artificial Intelligence is in case of its virtual assistant Siri that uses voice queries as well as a natural language user interface (UI) for functioning and which can make calls, send text messages, respond to questions, and offer recommendations. It entrusts requests to several Internet services. Siri can adapt to the users’ language, searches, as well as preferences.
In the case of Artificial Intelligence, Tesla has leveraged it to focus on mainly 2 areas: All electric propulsion and autonomous driving. Through its self generated AI chips the firm aims to ensure that the cars are able to navigate through not only the freeways but also through local streets as well as traffic signals.
The Tesla system consists of two AI chips in order to support it for better road performance. Each of the AI chips makes a separate assessment of the traffic situation for guiding the car accordingly. The assessment of both chips is then matched by the system and followed if the input from both is the same. You can further knowledge on this topic via our previous blog.
Pandora's A.I. is one of the most remarkable techs which exists in the present world. It is often christened by the firm as their musical DNA. Stationed on over 400 musical attributes, every song is initially manually interpreted via a professional musician team on the basis of this criteria, and so far the system holds a remarkable track record for suggesting underrated songs which would normally get overlooked but that people innately adore.
Facebook employs machine learning for interpreting and making predictions about the interest of the users. By assessing the likes of the user, their friend’s likes as well as location data, Facebook uses the information for deciding the content which it feels its user will enjoy through features like Facebook Watch. These prediction capabilities can also be employed for predicting other future behavior such as the products which a user could purchase, which in turn gets bestowed upon advertisers.
Facebook also uses AI technology to enable image recognition to help identify the faces in a photo, so it can prompt the user to tag it. The company is highly devoted to this technology since photos have extreme prominence for the platform.
Cogito employs AI for enhancing the emotional relationship with customers in sales and customer service calls. The firm adopts AI for making interaction more empathetic than humans could do alone.
The Cogito software interprets a conversation in real-time, facilitating clues and prompts over the ongoings, which could be either a speaker holding for too long or cutting too much or not making delays in response. The application also facilitates color-based warnings as well as updates. The software assesses hundreds of indications to gauge the emotional quality of the interaction.
These are just a handful of examples. Apart from these companies, there’s plenty of others like these that have employed Artificial Intelligence in intriguing and appealing ways. With AI having placed its influence powerfully and dominantly in the present world it's an undeniable fact that this technology has been impacting human lives as well as the society in a plethora of ways.
While this threatens the role of humans in various traditional occupations, it also opens up a whole new avenue of opportunities that has the scope of rising in the near future. However as the technology grows in prominence, factors like convenience, speed, accuracy, assurance as well as experience are always required to be considered. You can also follow us on Facebook, Twitter, and LinkedIn.
6 Major Branches of Artificial Intelligence (AI)READ MORE
Reliance Jio and JioMart: Marketing Strategy, SWOT Analysis, and Working EcosystemREAD MORE
Top 10 Big Data TechnologiesREAD MORE
8 Most Popular Business Analysis Techniques used by Business AnalystREAD MORE
Deep Learning - Overview, Practical Examples, Popular AlgorithmsREAD MORE
7 types of regression techniques you should know in Machine LearningREAD MORE
7 Types of Activation Functions in Neural NetworkREAD MORE
What Are Recommendation Systems in Machine Learning?READ MORE
Introduction to Time Series Analysis in Machine learningREAD MORE
How Does Linear And Logistic Regression Work In Machine Learning?READ MORE