12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Industry 4.0 is a concept that describes the digital transformation of industry. It refers to the fourth industrial revolution, in which machines, production facilities and devices are networked to exchange data and automate production. It builds on the previous industrial revolution and uses advanced technologies such as artificial intelligence, machine learning, the Internet of Things and robotics. Industry 4.0 can help increase productivity, optimize processes and accelerate innovation.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
DeepTech is a term used to describe technical innovations that are developed based on sophisticated technologies and algorithms. These technologies are often based on complex analytics and machine learning. They are commonly used in industries such as artificial intelligence, robotics, autonomous systems, biotechnology, and quantum computing.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
A neural network is a model that attempts to solve a complex problem by linking different units called neurons. These networks are built on the principle of neural activity, which was developed according to the way the brain works. Neural networks are a type of artificial intelligence used to solve complex tasks. They are widely used in pattern recognition, image recognition, game development and robotics.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
AI algorithms are algorithms that use machine learning and artificial intelligence to solve problems. They can be used to analyze data, make decisions, and solve problems. For example, AI algorithms can be used to improve the performance of robots, detect spam emails, or automate tasks such as driving a car.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Bayes theorem is a mathematical theorem that allows to calculate the probability of an event based on known information. It is commonly used in statistics, machine learning, and artificial intelligence. It allows predicted probabilities to be updated based on new information. It also helps determine the cause of an event. It was named after the English mathematician Thomas Bayes, who developed it in the 18th century.