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14 Applications Of Artificial Intelligence That You’ve Never Even Thought Of

You probably already know that some of the applications you use every day use artificial intelligence, such as Netflix, Spotify, and Siri, among others.

But that’s nothing compared to what you’re about to read… New uses and applications of artificial intelligence (AI) are developed every day, bringing us closer to an unparalleled future.

Then, after they defined the theme, machine learning algorithms programmed to create music found different musical elements, which gave them ideas on how this piece should sound.

If that last point shocked you, now image having a virtual chef by your side next time you cook, guiding you through each step of the recipe to prepare that culinary delight you never thought possible.

This program can find common factors that cause its staff to quit, creating a quality score for each employee based on the projected probability that they will leave the company soon.

An extensive article published in The Guardian exemplified several ways in which AI can help us to prevent future damage and better understand how to address developmental needs while focusing on sustainability.

AI is not only able to save certain areas of the ecosystem, as we already mentioned, but it can also save human lives… Through AI and deep learning, doctors can promptly diagnose cancer, before it’s too late.

The Chinese startup Infervision is using deep learning and image recognition technologies (like Facebook uses to recognize faces) to diagnose possible signs of lung cancer with X-rays.

The devices they’ll send, better known as rovers, will be able to explore Mars’ terrain in more detail and reveal the properties of the planet’s elements to determine the possibility of life with more certainty.

So, if you’re asking yourself what kind of things it can do… this article goes over, in detail, every one of its possible applications in the exclusive fields of digital marketing and sales.

This means that intelligent algorithms are able to learn, detect, and predict which types of users are more likely to become clients at a lower cost per acquisition.

Using machine learning algorithms it manages, optimizes, and automatically updates your digital campaign budget in over 20 different demographic groups per ad and on several platforms.

These kinds of advances are also tangible in e-mail marketing, where AI can personalize e-mails based on preferences and user behaviors to obtain a better interaction that can turn into a sale.

Companies such as Phrasee and Persado even determine what e-mail subject, text for the e-mail body, calls-to-action, and sending times will help prompt the user to make the desired action.

With automatic machine learning, price trends can be correlated with sales trends through an algorithm that aligns other factors, such as category management and inventory levels.

AI is also becoming a retailer’s best friend since there are already AI platforms that monitor the habits of sales representatives, giving them recommendations to improve their performance.

These intelligent CRMs allow them to have a better overview of all the elements involved in the sales process and discover sales opportunities in an unprecedented way.

For example, it’s been proven that cold emails are 20% more effective on Tuesdays, and that making a follow-up call 10 minutes after an online registration leads to more conversions.

Predictive analysis can be used to know which clients will unsubscribe, making it possible to contact them ahead of time to offer them incentives and provide them with specialized care to change their minds.

The most advanced chatbots are already able to answer open questions by using the natural language process and automatic learning to respond in a human-like way.

Sephora, for example, lets its users “try out” their cosmetic products (such as lipstick, eyeshadows, highlighters, etc.) on a photo of themselves that they share with the bot.

On the other hand, H&M helps users who visit its e-commerce platform find exactly what they’re looking for by making suggestions on what they might like or look good on them according to their preferences.

Sometimes it’s better to book the flight ahead of time, while other times it’s better to wait until just before the departure date to find cheaper tickets.

Through predictive analytics driven by artificial intelligence, the app is able to predict price patterns and alert travelers of the cheapest times to buy flights to their destinations.

What are the best examples of artificial intelligence?

AI can be broken down into two distinct fields: Applied AI: Machines designed to complete very specifics tasks like navigating a vehicle, trading stocks, or playing chess – as IBM’s Deep Blue demonstrated in 1996 when it defeated chess grand master Gerry Kasparov.

As per Jessica Goepfert, program director, Customer Insights and Analysis at IDC “Near-term opportunities for cognitive systems are in industries such as banking, securities and investments, and http://manufacturing….In these segments, we find a wealth of unstructured data, a desire to harness insights from this information, and an openness to innovative technologies”.

Machine learning application though, has the ability to learn an individual user’s requirements by examining their account activity and assisting the customer with a better product selection offered by BFSI companies.

Sophisticated language parsing enables today’s AI chatbots and virtual agents to provide more realistic text-to-voice systems (that provide real-value)- making the phone / chat systems customer friendly.

Wells Fargo, the American International American international banking and financial company uses a chatbot for assisting its customers in doing small tasks like taking their account information and helping them reset their passwords.

Other than customer engagement, chatbots are also used by investment service companies as stock market assistants to enable users to stay on top of the market with real-time information on stock prices (and other insights like news) of diverse candidate companies to assist them in investment decisions.

Intelegain powered, a virtual stock simulation platform is test driving a cognitive intelligence bot using Microsoft Bot Framework to provide real-time assistant services to help investors with investment options in the equity markets.

Arria’s CTO Robert Dale states “By emulating human behavior in software, you get technology that can carry out tasks that are more than just straightforward number crunching, with the machine exhibiting real intelligence…But you get all the benefits of this being done by software: it’s incredibly fast, it’s incredibly consistent, and it doesn’t need to sleep or take vacations, so it’s available 24/7.” In a Nutshell Ai is going to have a significant influence on data science use cases in banking- same as it is going to affect finance, healthcare and pharmaceuticals.

One of the best application of AI as of now is to perform the menial work of data analysis (that may be number crunching, finding flaws in investment strategies or a chatbot answering customer’s queries) – it is the economic solution to make everything run smoother, faster and at a lower cost.

Thus, more and more retailers, big and small, are applying AI tools in new ways across the entire product and service cycle- right from the assembling stage to the post-sale customer service interactions.

Personalization “Personalization at scale is the holy http://grail….by adding elements of personality insights or sentiment, touchpoints like email and web personalization can become contextually aware and can build on previous customer interactions” says Corinne Sklar, chief marketing officer at IBM consultancy Bluewolf.

I think the people that can combine technology-powered personalization with a human will be the winners” North Face, the outdoor clothing company adopted IBM Watson cognitive technology in order to help customers determine what jacket may be the best option for them.

offer the right message to the relevant customer at the right time – a key part of building sales, customer relationships all the while minimizing marketing waste.

President of (one of the first retailers to launch an Alexa skill) comments about possibilities AI could bring in retail “With voice as the main interface emerging, I think it will bring us back to the retail experience of our first flower shop where we delivered a true 1-to-1 relationship.

Bean makes use of a Chatbot which asks visitors if they would like to login into their loyalty account- this chatbot which is “loyalty aware” links to the customer’s loyalty points and CRM data to personalize customer’s choices.

Sephora, the French cosmetics brand with retail stores of beauty products adopted video analytics technology that examined the digital video stream from the store cameras and counted the people visiting the store.

For example, visual search for products will grow particularly via mobile and the monetization of eCommerce imagery via automated product tagging will bring new revenue streams in the future.” – Alex Vaidya, CEO &

IKEA uses image recognition technology to enable customers to take photos of images in the company catalog to retrieve useful information about the specific product-swap patterns, colors and even see how the final product would look like in homes.

The healthcare virtual assistant employs voice recognition, EHR integrations and strategic health IT relationships, voice biometrics, text-to-speech and prototype smart speaker customized for a secure platform.

Treatment design AI systems have been designed to analyze data- reports and notes from a patient’s file, clinical expertise and external research, in order to assist in selecting the correct, individually customized treatment path.

The potential AI holds in healthcare is endless- with professionals exploring the application of AI in areas like insurance verification, skin cancer diagnosis, medical record data analysis etc.- we are just beginning to realize the true depth of health-tech innovation that can be unlocked with AI technology.

In fact, Carousel the leading provider of personalized logistics predicts that one of the biggest growth areas where the artificial technology will make noteworthy difference to the bottom line is the intelligent forecast systems and in providing value-added services more easily at a cost-efficient rate.

In this area, anticipatory logistics benefits all parties involved in the supply line – by anticipating demand, permitting businesses to spike up their resources before the demand shoots up.

The retailer will know to order adequate stock – to increase advertising efforts and display space on the store shelves and in general prepare for a boom in online shopping.

Self-Learning Systems “Machine learning uses massive computing power to recognize patterns in data that humans could never see, and then learns from every new piece of data it receives to get smarter and more accurate in real time,” says

In the context of logistics – the system combines all the data in the carrier network with outside data sources like GPS systems, historical pricing performance and Federal Motor Carrier Safety Administration (FMCSA) to assist shippers more accurately estimate demand, examine trends in supply chains, track daily patterns within lanes and monitor seasonal calendars.

The company introduces the intelligent warehouse system (Panasonic iWS) as “a complete solution which includes surveillance cameras, data, network video recording, tracking software and your existing x-ray scanning technology”.

Natural Language Processing (NLP) for time management NLP is a form of machine learning which is dramatically improving the efficiency of supply chains by speeding up the data entry process and auto-populating form fields.

After enough data feed- the system recognizes the behavior of particular users and begins to anticipate the users’ need by auto-populating the bill of lading, shipping orders and other transactions- saving the shipper’s time.

rather than going to the website of the Logistics Service provider to find the details of their consignment and feed the specific code (a complex combo of numbers and alphabets) all the customer will need to do need to do is open a simple chat window for the solution.

Named as Amadeus Passenger Recovery, once the scheduled event is received, it “proposes an optimal passenger recovery plan, rebooks services, re-issues tickets and EMDs, transfers bags and checks passengers onto their new flight.

The system takes account of historical pricing data for a variety of routes, goods and delivery schedules- then it cross-references them with the traffic, weather and then estimates the fairest price.

In a Nutshell AI has aroused interest not only because of its ability to increase efficiency and service customers at a lower cost but also due to its potential to create more agile business models – that are scalable and flexible to the continuously changing market needs.

AI offers great possibilities for efficiencies- while- customers too can enjoy fast delivery, reliable stock information, time-saving and overall a great user experience with AI-powered logistics and supply chain management.

Fraud Detection Machine learning (ML) is especially important now than ever, in fraud detection as there is a significant shift to e-commerce and other remote “cards, not present” transactions where fast approval is needed- yet the customer’s physical card is not available for additional verification.

Legaltech - Legalweek

In this session, we take an in-depth look at the contracts process, including how Legal’s contribution can improve speed to revenue, margins, revenue maximization, and cost savings via comprehensive obligations management, including technologies to enable this.

In this session, we take an in-depth look at the contracts process, including how Legal’s contribution can improve speed to revenue, margins, revenue maximization, and cost savings via comprehensive obligations management, including technologies to enable this.

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“This is going to change every interaction with your customers.”  Matt Zeiler is the CEO of Clarifai, a company that uses artificial intelligence and machine learning to recognize and identify different videos and images.  While there are a lot of uses for image recognition — you’ve probably most recently interacted with facial recognition, for instance, on Facebook — Zeiler said online retail stands to benefit significantly from using AI.  “You have to be thinking about it in your business,” Zeiler said at Recode’s Code Commerce event in New York.

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