Meta-learning belongs to the category of artificial intelligence and also plays an important role in the areas of big data, smart data and automation.
Meta-learning means "learning to learn". In the world of artificial intelligence, meta-learning describes methods in which machines not only learn individual tasks, but also how they can learn new tasks faster and better. Instead of starting from scratch for every new situation, meta-learning algorithms utilise their previous experience and transfer this knowledge to new challenges.
An everyday example: Imagine a robot learns to grasp different cups. Using meta-learning, it recognises certain basic patterns when gripping - such as how round a cup is or how heavy it weighs. If a completely new cup then comes into play, the robot can use its "knowledge of learning" to find out much more quickly how best to grip this new cup.
Meta-learning saves time and resources because machines can adapt to new tasks independently. Especially in the rapidly changing world of big data and automation, this is an important step forward for companies.
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