You may not have known it, but the first form of artificial intelligence helped the British and their allies win World War II.
It was called "British Bombe" and was the machine developed and "trained" by the British genius of logic and mathematics Alan Turing and his team of scientists that made it possible to decipher the language of the code that encrypted the military communications of the Germans.
German submarines relentlessly sank ships loaded with weapons and supplies traveling from the United States to Britain across the North Sea; To encrypt their messages they resorted to a machine called "Enigma", but Bombe – Turing's machine – managed in a race against time to crack the code, thus allowing the British and the Allies to anticipate the movements of the opposing forces.
Turing's higher goal of creating a machine capable of learning from experience practically paved the way for machine learning and consequently AI.
Although it sounds absurd, advanced technologies were largely invented more than half a century ago: artificial intelligence, natural language processing, and programmable robotics, for example, have been around since the 1950s; The first research on facial recognition began in the 1960s.
But then you may wonder why they have only established themselves in recent years?
Simple: at the time, the technologies were not as powerful as they are today, and data storage was still quite demanding and expensive. It was the maturity of six enablers that made the rise of these technologies possible: 1.Computing power
2. Software open source
3. High-Speed Internet
4. Cloud computing
5. Mobile devices
6. Big data
Today “advanced technologies” are in a “sleep” situation, but trends say they will finally take off in the next decade.
Advanced technologies imitate humans
What are called “advanced technologies” essentially try to emulate and reproduce the so-called contextualized learning of human beings: as humans we learn from experience, that is, we are able to communicate, perceive and move based on environmental stimuli. In other words, we acquire knowledge, select relevant elements based on our life experience and thus develop an overall vision of the world.
Likewise, artificial intelligence engines are not designed to learn on their own, they must be trained using algorithms to figure out what to learn. They extract relevant elements from big data that serve as contextualized examples and can ultimately “understand” the algorithms and understand the deep meaning of the data.
So environmental sensors mimic the five human senses (think of facial and image recognition that can help machines distinguish objects based on the visual learning model used by humans); NLP – or natural language processing – becomes the “cognitive ability” of computers; robotics allows machines to perform physical movements; the augmented reality and the virtual reality try to imitate man's imaginative capacity by superimposing two different realities, physical and digital; IoT and blockchain finally reproduce the way machines should “socialize” and realize the connection.
Bionics, or the science that studies the structure and functions of living organisms with the aim of extracting useful elements to create technological equipment, shows us that these are the six ways in which technologies imitate human beings.
Examples of advanced technologies at the service of businesses
ARTIFICIAL INTELLIGENCE
AI is more popular than you might imagine.
It is not yet that technology that we see in science fiction films and which frankly scares everyone a little because it has a level of awareness equal to the human level. This form of artificial intelligence called AGI – Artificial General Intelligence – is not yet available and its development phase will take at least another 20 years. The most common artificial intelligence, however, the “less sophisticated” or restricted one (this is the correct adjective) is the form of AI widely used to automate routine activities in various sectors. Financial services companies use it to automate tax fraud detection; Google does this to recommend searches as we type individual letters into the search bar; Amazon uses it to provide helpful book recommendations, Uber to set dynamic pricing, and airlines to manage customer service via Chatbot.
This is to say that any type of recurring and standardized process can use automation systems and that artificial intelligence, in practice, replaces and automates the most boring and repetitive activities, those that generally cause human errors.
Another important thing is that AI transforms unstructured data into structured information. What does it mean?
Let's look at a couple of applications. In the field of marketing, for example, based on social media posts, transaction history and other behavioral data, AI can group customers into clusters, allowing companies to segment and target the market from the data. So from the interpretation of big data what are called insights are obtained. And what is this if not the basis for companies to offer customization and personalization in product recommendation campaigns, pricing and content marketing? As customers respond to the offers made in this way, the computer continues to learn and modify its algorithm.
Another example of integrating AI solutions into business processes other than marketing could be that of Ant Financial, which reinvented car insurance using image recognition and machine learning: customers can submit a claim for compensation of an accident based on a photo taken with your smartphone; the AI engine analyzes the image and determines whether the request is legitimate.
Ultimately, we could say that AI is the brain of automation and to offer a latest generation customer experience it must be associated with other technologies such as robotics, facial recognition, voice technology, sensors. It is no longer confined to computer research laboratories and creates value, but it certainly must be managed carefully.
NATURAL LANGUAGE PROCESSING NLP
Machines are able to reproduce the way of human communication, written and spoken and it is extraordinary if we think that in its natural form human language is often imprecise, convoluted, ambiguous.
Chatbots are certainly the most widespread application of natural language processing and with voice technology, machines have also become much better at responding to verbal commands. But I am not referring to simple chatbots, those that can only answer closed questions, but to the “powerful” ones based precisely on NLP. They are chatbots capable of interpreting non-standardized questions and giving an answer, capable of understanding a message in a chat even if it contains communication noise such as typing errors, slang or abbreviations; those who can even understand feelings and detect, for example, sarcastic statements.
Regarding verbal commands, we know that many voice assistants are now available: Amazon's Alexa, Apple's Siri, Google's Assistant and Microsoft's Cortana. These applications are already fully capable of answering simple questions and executing commands in multiple languages, but the demo of Google Duplex showcased at I/O 2018 demonstrated something extraordinary: how a virtual assistant can seamlessly carry out multilingual conversations “super” natural, I would say. When you call a hair salon or a restaurant to book an appointment, the voice assistant abandons the robotic tone and even adds the use of pauses and intercuts making the interaction more realistic than ever.
Technology solutions that use NLP in sales, for example, often reduce the need to resort to higher-cost channels such as inbound call centers and outbound telemarketing. Companies like Lyft, Sephosa and Starbucks use chatbots for order capture and customer interactions, while in B2B HubSpot and RapidMiner use them to qualify leads and direct potential customers to the most appropriate follow-up channels.
SENSORS
In addition to recognizing written and spoken language, computers also learn from the recognition of faces and images. What is the operating mechanism?
An image is scanned and basically the web or database is searched for similarities. The simplest example is that of Google's image search or Google lens – which allows you to "search for what you see" using a camera or a photo, but if we think about business processes, what can brands do? Companies can scan social media posts for people who buy and consume their products and send short thank-you messages; or on the contrary, they can identify people who use competing brands and invite them to change; they can make a highly targeted promotional communication and thus increase their market share. Or again, companies can do like Tesco which in the United Kingdom plans to install a facial recognition camera at the checkouts in order to identify the age of buyers of alcohol and cigarettes and to allow automated payment without the presence of a cashier human. They can exploit the principle behind telematics systems installed in cars that serve to improve safety and provide assistance in vehicle management.
Businesses can use sensors to feed AI with understanding everything they care to learn about.
ROBOTICS
Since the 1960s, large enterprises in industrialized countries have used robots mainly for back-end automation, primarily in manufacturing – given its labor-intensive nature. In recent years, however, robots have even replaced humans in interfaces aimed at consumers, so much so that one of the most extreme experiments in robotics perhaps takes place in the hospitality sector, where the human role is fundamental: in Virginia the hotel chain Hilton has experimentally adopted Connie, a robot concierge that recommends nearby attractions and restaurants to guests; the Aloft Hotel in Cupertino has introduced a robot butler called Botlr that offers services and provides room service and the Studio M Hotel in Singapore even uses a robot chef to prepare omlettes.
Robotics applied to hospitality and assistance go hand in hand: Toyota and Honda are investing in carebots for elderly care, Softbank's Pepper robot becomes a companion in nursing homes and a sales assistant in stores retail and Nestlé in Japan uses robots to produce, sell and serve coffee.
Although we often think of it in humanoid form, robotics is not just about physical robots. A growing trend is Robotic Process Automation (RPA – Robotic Process Automation) which involves software for robotics. These are virtual robots that perform computer work based on specific guides as a human being would do. Companies use it for example to automate invoicing and payments, for human resources management including payroll processing, in sales for CRM management and in marketing for programmatic advertising – which involves automatic offers to purchase advertising space digital to optimize results.
RPA can be used in different ways and its use is becoming very popular also due to the increase in budgets allocated to online advertising.
MIXED REALITY
In the field of innovation of three-dimensional user interfaces, the augmented reality (AR) and the virtual reality (VR), together with the mixed reality (MR), stand out among the most promising solutions and blur the boundaries between the physical and digital worlds. We could simplify by saying that AR is similar to bringing digital objects into the real world, while VR is similar to bringing people into the digital world; both are typically associated with the world of entertainment and gaming because current solutions are mainly concentrated in these two areas, but the ability to operate in the phygital world through MR is also a turning point in marketing, above all because it offers infinite possibilities of decidedly more engaging content marketing.
The tourism sector is one that uses MR to offer virtual tours and encourage people to visit a destination in the physical world. The Louvre, for example, offers a virtual experience to users wearing HTC Vive VR headsets not only to see the Mona Lisa up close, but also to access narratives about the painting.
“
"The VR
will help visitors
to understand what is behind the curtain"
will help visitors
to understand what is behind the curtain
Retailers use it to allow customers to virtually “try” or “consume” products before deciding to purchase or to provide tutorials. Ikea, for example, produces 3D images of its products and uses AR to help potential buyers visualize how a piece of furniture fits into their homes.
Furthermore, in the automotive sector, companies such as Ferrari provide Car Configurators which allow users to choose colours, designs, setups, wheels and customize their Ferrari in every detail through interactive 3D configuration experiences.
INTERNET OF THINGS (IoT) E BLOCKCHAIN
IoT refers to the interconnectivity of machines and devices that communicate with each other. If individuals can use the IoT to have what are called “smart homes,” businesses can use it for remote control, monitoring of assets such as buildings and company fleet vehicles, and to deliver a seamless customer experience.
The most obvious example of a fluid customer experience is the MagicBand of the Disney parks: the bracelet continuously communicates with thousands of sensors placed in the various attractions, restaurants, shops and hotels via radio frequency technology, stores visitor information and It therefore functions as a) Disneyland ticket, b) hotel room key, and c) payment instrument. In this way the Internet of Things eliminates all points of friction in the experience and at the same time improves it: for example, it allows staff to monitor customer movements, anticipate the arrival of guests within a radius of 12 meters and serve them in proactive way.
The blockchain, on the other hand, is mainly known as the technology that underlies bitcoin, but has a practically infinite degree of applicability. It is an open and distributed, i.e. decentralized, ledger system that contains encrypted data via a peer-to-peer network. Simply put, a blockchain “block” is like a ledger page that contains all previously made transactions. Once a block is completed, it can no longer be modified and gives way to the next block in the blockchain. The turning point of blockchain lies fundamentally in the secure and transparent nature of data management and storage, therefore the technology becomes a guarantor of truth.
For example, it allows you to record and trace entire supply chains – think of the offer of products declared 100% organic guaranteed by the recording of transactions along the supply chain – and to share and manage distributed customer data between multiple companies and brands. All in the name of transparency.
POINTS FOR REFLECTION
Do you adopt advanced technologies in your company? Have you thought about your organization's technology roadmap for the next five years?
If you feel like reinventing your business by taking advantage of the opportunities offered by advanced technologies, don't hesitate to get in touch with the TDE team!
We are at your disposal!
01/12/21
Oriana Torregrossa | Digital & Communication Manager TDE
Source: Marketing 5.0 – Philip Kotler