The term In-Context Learning belongs within the fields of Artificial Intelligence and Digital Transformation. It describes a particular capability of modern AI models, such as those found in chatbots or digital assistants: they learn in real-time from the direct context of a conversation or task.
Instead of relying on a fixed list of questions and answers, the system understands the context in which information is needed. This means that the AI can react flexibly, process new information, and adapt to the flow of conversation – without having been specifically trained beforehand.
A practical example: you first ask a digital assistant for a restaurant's opening hours. In the next step, you ask: „Please book a table for me there.“ The AI understands through in-context learning that „there“ refers to the restaurant without you having to repeat it. This allows it to solve tasks quickly and in a user-friendly way.
In-context learning therefore ensures that artificial intelligence can communicate with us in a more natural and helpful way. This flexibility is a considerable advantage, especially for businesses, in the digitalisation of customer service and internal processes.
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