There is one thing that you simply will accept as true with me—that the fourth technological revolution is here, because of AI and large Data. In fact, consistent with a report done by CNN there’s no accurate figure on the quantity of knowledge in Big Data. it’s estimated that quite 90% of all data existing immediately was created last year – and it keeps increasing.
Even though this is often tons of knowledge, it’s useless in its raw form. this is often where AI comes in to form a sense of the info. As a result, more companies are now embracing AI. consistent with a survey done by New Vantage Partner quite 95% of Fortune 1000 executives in sixty companies were investing in AI and large Data. AI and large Data have revolutionized every industry and corporations are continually seeking out ways to form AI and large Data work for them.
AI, Big Data and soft drinks
Every day people consume 1.9 billion servings of Coca Cola drinks. thanks to this huge market share within the beverage space, Coca Cola generates tons of knowledge that it uses to form strategic decisions. Coca Cola was the earliest non-IT company to adopt AI and large Data.
Coca Cola is understood for investing heavily in research and development. After having a successful launch of self-service soft drinks and fountains, Coca Cola gathered all this data. It then combined it with AI and using the insights acquired it launched a replacement beverage brand—Cherry Sprite. Cherry Sprite was supported by the info collected by clients mixing their drinks to make the right cocktail beverage.
AI, Big Data and Education
Elsevier is one of the worldwide leaders within the publishing of medical and scientific information. Over the years Elsevier has leveraged AI and large Data to enhance its operations. thanks to the huge amount of knowledge that the corporate has collected in its 140-year existence it’s built advanced analytics systems using AI and large Data.
Traditionally, getting information from any of their publications meant that you simply had to urge a paper-based publication or book. However, as Internet usage spread, Elsevier decided to leverage this and digitize its literature. After digitizing the corporate saw another challenge – information overload. it’s estimated that data within the world doubles every two years.
Not all this data is beneficial, and Elsevier realized that they needed to seek out how to chop through the noise and provides their readers with valuable and actionable data. this is often where AI and large Data came in. AI and large data were wont to study the reading habits of their clients and analyze which type of knowledge was being consumed tons. Using these insights they then deployed machine learning to present relevant information to their readers.
The case for AI, Big Data and faux News
You have probably heard of faux news where people post false information about others on the web. The news might be something as trivial as rumors about one’s dating life to graver news just like the death of an equivalent person. thanks to the various media outlets like social media, blogs, and even traditional media fake news can spread sort of a wild bush fire, and therefore the truth only comes out afterward after the damage has been done.
Fake news may be a significant issue, and one Google-funded company is leveraging AI and large Data to combat fake news. Veri-Flix, a Belgium company, is leveraging AI—with attention on machine learning to fight fake news. lately, citizen-journalism has become a force that even mainstream media institutions cannot ignore. Anyone can upload a video and make fake news about it. By employing machine learning they will scan user-uploaded videos and determining their credibility. this is often done by collecting data like video content, time-stamps, and geolocation. Using this data they tag several videos and compare them against one another. After garnering a gift and funding from Google the company’s technology is being put to the test at the country’s largest media station.
AI, Big Data and food
McDonald’s, one of the most important fast-food chains on the earth, is one company that needs no introduction. For an extended time, the fast-food chain didn’t see the necessity to implement AI and large Data but upon seeing the success that their competitors were having, they revised their strategy. because the largest fast-food chain within the world, serving on the brink of 70 million people daily, it’s clear that it generates tons of knowledge. Moreover, they need leveraged that data in some ways as shown below
Use of digital menus
Digital menus are a standard phenomenon lately, but McDonald’s has taken it a notch higher by introducing digital menus that change supported real-time data analysis. The menus vary also supported parameters like weather and time of day. thanks to this innovation, they recorded the third increase in sales in Canada.
McDonald’s are leveraging the appliance to form a win-win situation for them and their clients. Users of their app get various benefits like:
On the opposite hand, when customers pay through the appliance, McDonald’s not only got money but also vital customer data that has metrics like:
- Where and when the client goes to the restaurant
- The frequency of their visits
- Preference between a drive-thru or a restaurant
By using this data, McDonald’s can make recommendations and promote deals to extend sales. As a result of this data, they need to notice a quite 30% increase in sales in Japan for clients that used the app.
Autonomous ships, Big Data and AI
Most people know that the longer-term lies in autonomous automobiles, but not many of us know that there also are plans to launch autonomous ships. this is often thanks to a collaboration between Google and Rolls-Royce to make autonomous and smart ships. Rolls-Royce is going to be using the Machine Learning Engine on Google Cloud in its applications to form its vision of smarter and autonomous ships come true.
At first, AI algorithms are going to be trained using machine learning to spot objects which will be encountered stumped and classify them supported hazard they’ll pose. The Machine learning algorithms that are currently getting used by Google Voice and image search applications. they’re going to even be augmented by massive data sets produced from various devices like sensors, cameras, and cameras on vessels. By combining the cloud-based AI and large Data application enable data to be shared in real-time to any ship and also to on-shore control centers.
Healthcare, Big Data and AI
One of the problems that a lot of healthcare systems face is matching staffing volumes to patient numbers. On just one occasion you’ll have only a few patients and an enormous staff roster. During other times, you’ve got an overflow of patients and a strained workforce. So how does one solve this problem? Embrace AI and large Data by following the instance set by some hospitals in Paris.
Four hospitals in Paris have managed to leverage AI and large Data to enable nurses, doctors, and hospital administrators to forecast admission and visit rates for 2 weeks. this permits them to draft in extra staff once they expect high patient volumes resulting in reduced wait times and better-quality care.
So how does the system work? Using an open-source AI Analytics platform, the hospitals compiled admission data for the last ten years, and external data sets like flu patterns, weather, and public holidays. The insights were then wont to predict admission rates at different times. aside from just getting used to predict admission rates, such data are often wont to reduce wastage and enhance health care delivery by forecasting the demand for services.
Big Data, AI and Security
When it involves security screening, most folks expect that you simply will find a security person screening you individually employing a face-to-face approach. Although customs and immigration officers are highly trained to detect someone that’s lying about their intentions mistakes do still happen. Also, there’s the very fact that humans get tired and maybe distracted resulting in errors. So how can we avoid such human errors? Apply AI and large Data to screen passengers.
Homeland security has developed a replacement system called AVATAR that screens people’s facial expressions and body gestures and picks up small variations which will raise suspicion. The system features a screen with a virtual face that asks the passenger questions. It monitors the person’s responses for changes in voice tone also as differences in what was said. Data collected is compared to a database and compared against factors that show someone could be lying. If the passenger is flagged as being suspicious then they’re highlighted for further inspection.
AI and large data are indeed the fourth revolutions. The potential for AI and large data is endless. No industry has been disrupted by AI and large data, and therefore the future belongs to people who leverage it to their benefit