Our FAQs

Artificial Intelligence enables rapid, efficient processing of large volumes of data. In complex technical databases like those used in PDM and PLM systems, AI helps identify relevant information without the need to manually sift through dozens of files. AI can find correlations, detect trends, and answer complex questions, saving time, reducing human error, and optimizing decision-making processes.

Machine Learning is a field of AI that allows computers to learn from data without being explicitly programmed. Through algorithms, systems analyze data, detect patterns, and make decisions based on these observations. There are three main types of Machine Learning:

• Supervised learning: the algorithm is trained using labeled data (e.g., with known categories),

• Unsupervised learning: the algorithm learns to detect patterns in unlabeled data (such as customer segmentation),

• Reinforcement learning: the algorithm learns from actions and rewards (e.g., in video games). In short, Machine Learning is one of the core technologies behind many modern AI applications.

In short, Machine Learning is one of the fundamental technologies behind many modern artificial intelligence applications.

Deep Learning is a subcategory of Machine Learning based on artificial neural networks. It is especially effective for processing large volumes of unstructured data, such as images, sounds, or texts. The term “deep” refers to the many layers in these neural networks, which enable the model to learn complex representations of data. By training these networks with millions of data points, the model can automatically extract relevant features and generalize to new data.