This technology is based on a artificial neural network – a subtype of artificial intelligence. Thanks to the latest developments in deep learning, digital voice assistants such as Google Assistant, Amazon’s Alexa and the language assistants used in connected cars are now able to understand natural human speech.
The big tech companies like Google, Amazon and Apple aren’t the only ones developing artificial technology. Many German companies, initiatives such as the Munich Mobility Hub which started a cooperation project with Facebook on exchanging knowledge on artificial intelligence last year, and start-ups are also increasingly using AI-based systems. But what do we actually mean when we talk about AI in this context? What specific solutions already exist, and what is their practical relevance?
Machine learning, deep learning, neural networks – what exactly is artificial intelligence?
There are now so many words used to discuss AI that it has become difficult to keep up with the latest developments. In order to be able to assess the true potential of AI, we first of all need to understand the difference between ‘strong’ AI and ‘weak’ AI. Strong AI is used to describe the idea that machines can become generally intelligent and able to think the way humans think. However, we are still a long way from achieving this and it is questionable if we ever will.
The great things that AI is already able to do today are all based on methods such as machine learning, deep learning and artificial neural networks. Machines using these methods are not in themselves intelligent. They need to be taught. A chatbot or an algorithm can be trained to be intelligent at specific tasks – such as image and speech recognition or risk assessment. However, this also means that a smartphone that is able to recognize the face of a user can only be used for this specific task and not others.
How can AI be used in practice? Three start-ups from the IoT & FinTech Hub Berlin and the Digital Health Hub Nuremberg/Erlangen show how the technology can be used:
CLARK – a chatbot that provides insurance
Getting insurance is rather dry, complex and difficult to understand. A Berlin-based InsurTech start-up called CLARK has set out to change this. CLARK is a chatbot that helps people choose the right insurance policy. As it provides advice to customers, it is also called a robo-advisor. Based on data provided by the customers, CLARK analyzes their need for insurance using artificial intelligence.
Artificial intelligence makes it possible to analyse the data from thousands of insurance policies and premiums – which would otherwise be virtually impossible – and therefore provide customers with the offer that is best tailored to their needs. Without artificial intelligence, providing customised offers would take a very long time.
PAIR Finance brings artificial intelligence into debt collection
Start-up PAIR Finance can be best described as a digital collection company, even though the methods used by the company to collect debt are fundamentally different from those used by traditional agencies. The companies informs debtors about outstanding payments not only by mail, but also by text message, email and instant messaging services. The company has created a data-based debt management system that can be used not only to convince debtors to pay the debt, but also to help the companies owed the money to retain the debtors as customers.
This is where artificial intelligence comes in. The intelligent machine learning algorithm places a special focus on how to address customers. Every time a customer is asked to pay, the algorithm identifies the perfect moment for contacting the customer. It also determines how often the customer should be contacted, the wording and tone to be used, and the right channel of communication to contact the customer. All of this is done based on customer data. The collection process – from informing the customer to settling the debt – is not being carried out using a standard protocol, but is adapted to the responses of each individual debtor. By using artificial intelligence, the number of cases where the debtor repays the debt is to be maximised, whilst at the same time helping retain as many customers as possible.
IT labs: transforming the healthcare sector using AI
One of the most pressing challenges in the healthcare sector is how to bring healthcare into the digital age. IT labs – a start-up from Nuremberg – has identified a wide range of areas where this transformation can be achieved by using the right software solutions. Apart from rolling out electronic medical records and expanding the use of digital interfaces by different stakeholders, the start-up also looks at how artificial intelligence – or more precisely machine learning and deep learning – can be used. The number of use cases that exist amply reflects the complexity of the healthcare sector. The start-up recently launched its Alberta platform, where AI is used to remind users of the appointments they have scheduled with patients. It also alerts them to staff shortages, thereby ensuring that healthcare services can be provided around the clock.
Machine learning and deep learning methods are especially good at detecting patterns in huge amounts of data. The detection of big data patterns can provide a better understanding of certain diseases and help provide better healthcare services. Members of staff are alerted to any anomalies in the data that are being detected and are provided with specific recommendations for action. Machine learning also has the potential to improve the quality of medical diagnoses. Doctors and nurses can also use image analysis algorithms as they examine wounds, which makes their work easier and helps them provide better medical care.
Artificial intelligence – an engine for growth
As research is being conducted into AI and artificial intelligence is being used in a wide range of different sectors, it has become an engine for growth. AI methods, particularly machine learning, are increasingly used not only for developing applications and products, but also in manufacturing. Here, AI can help reduce the downtime of production facilities through predictive maintenance, and can streamline processes to improve output. According to a new study by PWC, AI will enable global GDP to grow by 14% by 2030. This means that artificial intelligence will be one of the main engines for growth. And these prospects are not as far away as we may think. As the start-ups presented here in this article show, artificial intelligence can already be used successfully today.
