SEO glossary: Artificial intelligence (AI)

 

What is artificial intelligence (AI)?

Artificial intelligence - AI for short - is a technology that enables computers and machines to simulate human abilities. Specifically, the aim is to replicate human intelligence and problem-solving skills. The purpose of this is for AI to take on tasks that can normally only be performed by humans.

 

You come across artificial intelligence in many areas of everyday life, for example:

 

• GPS navigation
• autonomous vehicles
• digital assistants
• Generative AI tools
• Weather forecast

 

AI sometimes works alone and sometimes in combination with other technologies such as sensors, robotics or geolocation. In general, all our smartphones and computers integrate certain programs that are based on AI.

 

Artificial intelligence is a branch of computer science. It therefore encompasses other disciplines that are already familiar from this field: machine learning, deep learning and others.

 

These methods help AI to continue to "learn", i.e. to better and better imitate the decision-making processes of the human brain. Large amounts of data are used to make artificial intelligence ever more meaningful and effective.

 

How long has artificial intelligence been around?

Artificial intelligence (AI ) is currently on everyone's lips, but it is by no means a new invention. The first algorithms that could 'learn' and evolve were developed as early as the middle of the 20th century. This enabled the technology to solve problems even back then.

 

In the course of advancing digitalization, however, AI has continued to develop, resulting in a veritable hype. Not only companies and scientists, but also private individuals are making use of AI technologies. Corresponding systems have managed to improve considerably in natural language processing (NLP).

 

AI can now not only learn and imitate human language, but also create images, videos, software code and molecular structures.

 

However, the idea of artificial intelligence does not actually originate from our time. Even in ancient Greece , people had the vision of a "machine that thinks". Of course, it could not be realized at that time, as there was no electronic data processing.

 

How important is AI for everyday life?

Today, it is almost impossible not to come into contact with AI. There are many areas in which artificial intelligence plays a major role. The number of applications for artificial intelligence is increasing every day.

 

Tools such as ChatGPT from Open AI in particular are leading to more and more people using artificial intelligence. This in turn is sparking new debates. It is now about AI ethics, trust in AI, safe use of AI and responsible AI. All of this shows that artificial intelligence is playing a major role in society.

 

Types of AI: strong vs. weak AI

When it comes to AI, a distinction can be made between two types:

 

• weak AI - also known as narrow AI: trained and focused on performing specific tasks, e.g. Siri from Apple, autonomous vehicles, Alexa from Amazon
• strong AI - consisting of artificial general intelligence (AGI): theoretical form of AI in which humans and machines are equally intelligent, also known as superintelligence

 

Weak AI is therefore what we encounter every day today. There are no practical examples of strong AI, as it is completely theoretical in this day and age despite digital progress.

 

Sub-disciplines of artificial intelligence

The computer science disciplines already mentioned, deep learning and machine learning , are what make AI what it is. These are important sub-disciplines that are necessary for the functions of artificial intelligence.

 

They have one thing in common: they are based on neural networks that enable them to learn from large amounts of data. The model for these networks is the human brain, which has numerous connections and layers that enable intelligent thinking and learning.

 

When it comes to solving a task, the neural network is trained with data. For this purpose, the programmatic structures consist of layers of interconnected nodes - similar to the human brain.

 

The main difference between machine learning and deep learning is that they use different types of neural networks. Machine learning algorithms have an input layer and an output layer. In between, there are one or two hidden layers.

 

These algorithms are therefore limited to supervised learning . There still has to be a human expert who structures the data. This is the only way the data can be extracted by AI.

 

Deep learning, on the other hand, uses - as the name suggests - deep neural networks. They consist of an input layer and three or more hidden layers as well as an output structure. Unsupervised learning becomes possible. It is no longer necessary for humans to structure the data.

 

Deep learning therefore enables machine learning on a large scale. This is how the two sub-areas differ and yet interlock.

 

Generative AI as a leading technology

Today, we mainly talk about generative AI. It refers to deep learning models that are able to learn from raw data. They encode a simplified representation of the training data and create new works from it. These are not identical to the original data, but are very similar to it.

 

Generative AI models have been in use for many years. They are used to analyze numerical data for statistics. Their scope of application is now expanding to include images, language and many other complex data types.

 

As a lot is happening in AI research, corresponding technologies are increasingly being introduced in companies. Various processes can be improved and in some cases entire workflows benefit from this.

 

 

Areas of application for AI

As diverse as AI itself is, the areas of application of artificial intelligence are just as extensive.

 

• Speech recognition: Artificial intelligence can recognize and interpret verbal speech. Such algorithms are used in voice assistants, for example. In addition, AI also has semantic speech recognition. This extends the scope of application to written texts.
• Computer vision: AI can recognize images, graphics, videos and other visual inputs and derive important information from them. Large data sets are processed at lightning speed, which is used in medical diagnostics, for example, but also in the translation of handwriting into print.
• Pattern recognition: Machine learning helps AI to identify patterns in sequences of events. For humans, such patterns are only visible - if at all - through in-depth analysis. For example, AI can recognize error patterns in vehicle electronics so that parts can be replaced before they even cause problems.

 

AI opportunities for companies

The application areas of artificial intelligence offer attractive opportunities for companies. Processes can be optimized and many other benefits can be achieved. AI is used in a targeted manner to improve certain areas of the company.

 

Customer service

Artificial intelligence is becoming increasingly common in customer service. In many companies, support is no longer provided by human employees, but by chatbots and virtual online agents. These are trained to answer frequently asked questions and offer personal advice.

 

Artificial intelligence can already sell products, suggest clothing sizes, help with shipping and returns and perform many other tasks that were previously carried out by humans. This means that many customers can be helped in a much more targeted and faster way. This increases customer satisfaction and customer loyalty.

 

Process optimization

AI's ability to recognize patterns also makes it easy to identify errors in processes. You can use machine learning to optimize processes in order to use your resources more effectively.

 

Anomaly detection

Similar mechanisms that are used in process optimization using AI also play a key role in anomaly detection. Artificial intelligence can quickly and reliably detect anomalies in data sets.

 

These can be faulty components, defective equipment, human error or cyber security breaches. This can improve your products and manufacturing processes and make them safer.

 

Supply chains

You can optimize your supply chains with AI. The technology used here is called adaptive robotics, which is based on device information from the Internet of Things (IoT). Search and pattern recognition algorithms analyze data in real time and can identify and eliminate errors in supply chains.

 

Online marketing

Also in online marketing AI technologies can also be used in online marketing. ChatGPT and its alternatives help you to research and create suitable content. You can also realize a lot of other creative projects with AI.

 

Safe AI - safety first

When humans rely on machines, it is important to take safety precautions. AI systems are specifically secured with Safe AI. This is particularly relevant for technologies such as autonomous driving.

 

This requires precise data analysis and process control. To stay with the example of autonomous driving: Vehicles must be able to recognize and reliably interpret their surroundings. This forms the basis for a reaction.

 

However, there is a problem here: the decision-making process of AI is opaque for humans. In addition, it is not possible for humans to adapt the decisions. Humans can only control the input and the result - everything in between is beyond their control.

 

As a result, it is still difficult to classify and evaluate the safety and reliability of AI . For this reason, artificial intelligence is only gradually being used in safety-critical applications.

 

Industry 4.0 - Machine learning for companies

However, industry is already making extensive use of AI. The digitalization of industry is therefore not referred to as "Industry 4.0" without good reason. Machine learning ensures improved planning and reliable predictions.

 

The machines are networked with each other and act automatically. As they also have access to their environment, they can adapt their actions to it independently.

 

However, the safety aspect also plays a role here: AI must be appropriately safeguarded so that humans and robots can work hand in hand and no injuries occur.