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News from the world of AI robotics
Mar 2024
Tech News
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“Real” AI: A definition – and how robotics benefits from it

Artificial intelligence (AI) is used in many areas today, whether in chatGPT, voice assistants such as Alexa or in automation with robots. However, there are many different definitions and approaches to Artificial Intelligence and how to train it.

So what is “real”AI?

Artificial Intelligence aims to solve complex problems or issues quickly. Various data processing technologies are used to arrive at this solution or result, including machine learning and deep learning. Watch out: Not everything that calls itself “AI” these days really is AI. When processing and using data, "real" AI must be clearly distinguished from traditional data analysis, which, unlike AI, is static and inflexible in its ability to recognize data and is based on predefined rules and algorithms.

AI, Machine Learning & Deep Learning: The differences

The differentiation between AI, Machine Learning and Deep Learning

Artificial Intelligence (AI)

AI is a broad field in computer science that aims to create machines capable of performing tasks that normally require human intelligence. This includes problem solving, speech recognition, decision making and more. AI is the generic term that includes all technologies that enable machines to act intelligently.

Machine Learning

Machine learning is a subfield of AI that focuses on the development of algorithms and statistical models that enable computers to learn from data and make decisions without being explicitly programmed to perform specific tasks. Machine learning is about enabling machines to learn from experience and adapt to new data.

Deep Learning

Deep learning is a specialized area of machine learning that deals with neural networks that contain many layers of processing units to learn complex patterns in large amounts of data. Deep learning models are particularly powerful for tasks such as image and speech recognition, as they can recognize fine details and patterns in the data without human intervention. Deep learning uses neural networks that work in a similar way to the human brain and learn from data to make decisions. They proceed in a similar way to how humans would: perceive something, think about it, and draw a conclusion. However, compared to machine learning algorithms, neural networks can analyze a much larger amount of data much faster.

In summary,

Artificial Intelligence is the comprehensive field that pursues the goal of creating machines that can act intelligently. Machine learning is a method of AI that enables machines to learn from data. Deep learning is a special method of Machine Learning that uses particularly deep neural networks to recognize and learn very complex patterns in data.

What does this mean for use in robotics?

In robotics, many decisions have to be made quickly, in order-picking or bin-picking e.g. what needs to be picked, where it should be picked and how the robot gets there. The cycle time, i.e. the time it takes to complete a task, is an important factor here. This is where the deep learning approach comes into play, as it enables quick decisions and is therefore necessary in order to use real AI efficiently in robotics. The robobrain® AI is also based on the deep learning approach and is equipped with various neural networks to make quick decisions and give the robot the right"instructions".

To make this complex technology accessible and usable for everyone, robobrain® can be equipped with various AI skills. These skills are based on neural networks that are pre-trained in different ways. This means that different AI skills can be used to give the robot different abilities in order to automate processes easily and efficiently.

Vivien Weiser
Marketing Managerin