Nowadays artificial intelligence (AI) and machine learning are impacting our daily lives in many different ways. They help businesses make decisions and optimize operations for some of the world's leading companies. As a result, there will be a huge change in jobs and employment in the future.
These are practical examples of artificial intelligence (AI) and machine learning.
Based on the operation of natural language, machine learning and advanced analytics, Hello Barbie can listen and answer a child. A microphone on the Barbie's necklace records and transmits what the child was saying to the servers at ToyTalk. The record is analyzed to determine appropriate responses from 8,000 lines of dialogue. The server transmits correct responses to the Barbie after a second so she can respond to the child. Answers to the questions, such as 'what is your favourite food?' are stored for later conversations.
Despite having been a leading global brewer for the past 150 years, Heineken, the Dutch company, is continuing their success, especially in the United States. They make use of the vast amount of data collected. From marketing based on IoT (Internet of Things) to operational efficiency improvement through data analysis, AI and data are always developed by Heineken for the purpose of improving operations, marketing, advertising and customer service.
Does culinary art always need humans? Yes and no. Watson, the head of AI at IBM, has an idea of how AI can become a chef in the kitchen to help develop recipes and advise human's partners on food combinations to create completely unique flavours. When AI and humans work together in the kitchen, they can create more than just working alone.
Music production algorithms are now inspiring new songs. Through input data - millions of conversations, newspaper titles and speeches - insights are collected to help create a theme for the lyrics. Machines like Watson BEAT can find different musical elements to inspire composers. AI helps musicians understand what their audience wants and helps determine more precisely which songs can be the most suitable.
Dominating the global energy industry, BP is taking the lead in the application of big data and artificial intelligence in the energy industry. They use this technology to create new levels of efficiency, improve the use of resources, the safety and reliability of producing and refining oil and gas. With the use of AI technology to improve operations, BP has brought data to engineers, scientists and decision-makers to help increase performance.
With an effort to provide energy in the 21st century, GE Power uses big data technology, machine learning and IoT to build the "internet of energy." Advanced analytics and machine learning help create predictable maintenance, energy, operations, and business optimization to help GE Power move towards its vision of the "digital power plant".
With around 3.6 petabytes of data (currently under development) for individuals around the world, Experian receives a special amount of data from its marketing database, transaction records and public information records. They are applying machine learning to their products to enable faster and more effective decision making. Over time, machines can learn to recognise important data. Detailed information extracted from the machines will allow Experian to optimize their processes.
American Express processes $ 1 trillion in transactions and has 110 million AmEx cards in operation. They rely on data analysis and machine learning algorithms to help detect fraud in real-time nearby, thus saving a lot of money. In addition, AmEx is making use of data stream to develop applications that can connect cardholders to special products or services and offers. They also provide analysis of online business trends and finance industry's benchmark.
AI and Deep learning are used to save lives through Infervision. There are not enough radiologists in China to detect early signs of lung cancer. Radiologists need to do hundreds of scans per day. Not only this tedious but also exhausting work can lead to negligence. Infervision trains and teaches algorithms to enhance the work of radiologists, helping them to diagnose cancer more accurately and effectively.
Neuroscience is the inspiration and foundation for DeepMind which creates a machine that can mimic the thought process in our brains - Google's. Deepmind has succeeded in defeating humans at games. The really intriguing thing at DeepMind, however, is health care applications such as reducing treatment planning time and using machines to help diagnose diseases.
Cars are increasingly connected and generate data that can be used in a variety of ways. Volvo uses data to help predict when car parts are broken or when the car needs maintenance, monitor the vehicle's performance in dangerous situations and increase convenience for the and passengers. Volvo is also conducting research and development separately on autonomous vehicles.
The AI technology revolution has also affected agriculture, and John Deere is bringing data analysis and automation tools to farmers. They acquired Blue River Technology for a solution that uses advanced machine learning algorithm. This is an algorithm that allows a robot to make decisions based on visual data about whether a tree is suffering from diseases. The company has provided automated agricultural vehicles that can precisely plough and seed with GPS and the Farmsight system designed for agricultural decision-making.
"Talking with Machines", The BBC project, is an audio film that allows listeners to participate and have two-way conversations through their smart speakers. Listeners can become part of the story because they can answer the questions and insert the lines they speak into the story. In addition to the newly created Smart Speaker for Amazon Echo and Google Home, BBC is expected to develop other voice-activated devices in the future.
Big data analytics is helping Netflix predict what customers enjoy watching. They are also becoming a content creator rather than just a distributor and using data to determine what content they will invest in.
When you think of Burberry for the first time, you may think of a high-end fashion brand rather than a digital business. However, they have made a lot of effort to use big data and AI to combat counterfeit products, improve their business and customer relations. The company's strategy to increase sales is to cultivate closer, more personal relationships with customers. As part of this strategy, they have rewards and loyalty programs that collect data to help them personalize the shopping experience for each customer. In fact, they are making the shopping experience at their traditional stores as innovative as an online shopping experience.
Walmart is looking for ways to transform retail and provide better services to its customers. They use big data, Machine Learning, AI and IoT to ensure a unified experience between online shopping and at traditional stores. They use the Scan and Go feature on the app, the Pick-up Towers, and are testing facial recognition to determine if customers are happy or sad.
Everything that Microsoft does focuses primarily on leveraging smart machines. Microsoft has Cortana, a virtual assistant; chatbots to run Skype and answer customer service queries or provide information like weather or travel information updates. The company has implemented smart features in its Office. Other companies can use Microsoft's AI Platform to create their own intelligent tools. In the future, Microsoft wants to see smart machines combined with artificial intelligence that allow them to complete any task.
As a leader in delivery services, Disney is getting much better signals thanks to big data application. Each customer has their own MagicBand wristband for ID, hotel room key, ticket, Fastpasses and payment system. When it comes to customer convenience, Disney receives a lot of data to help them anticipate customer needs, providing great customer experience. They can deal with traffic jams, providing additional services to customers who may have experienced inconvenience. Data even allows the company to plan for their employees more effectively.
In order to prevent inappropriate content or racist content, and at the same time enhance users' experience, Twitter uses artificial intelligence to improve their products. They process a lot of data through artificial neural networks to find out what users like over time.
Deep learning is bringing values to Facebook mainly thanks to unstructured datasets created by 2 billion people updating their status 293,000 times per minute. Most of Facebook's deep learning technologies are built on the Torch platform which focuses on artificial deep learning and neural networks.
Instagram also uses big data and artificial intelligence for advertising and the fight against online threats as well as remove offensive comments. As content grows in the platform, artificial intelligence plays an important role in showing users the information they may like, preventing spam and improving user experience.