Generative or non – generative AI?
Both are forms of machine learning, but the key difference lies in the outcome. Generative AI creates new content based on existing data, such as texts, images, or videos. Non – generative AI, often referred as discriminative AI, is primarily used for organizing, processing and interpreting existing data – for example data archiving or intelligent document analysis.
According to a Forbes study, business representatives agree that AI enhances customer experience, making companies more successful. In particular, the use of AI – powered chatbots, email optimization and the delivery of personalized services are seen by many respondents as key opportunities for their own success.
Topics such as data protection and ethics play a crucial role in AI and require significant attention. The rapid pace of change also demands a proactive approach. It is therefore essential to support employees throughout the digital transformation, ensuring both acceptance and the correct, secure use of AI in daily operations. To facilitate this, Bechtle offers a wide range of training sessions and workshops.
AI, or Artificial Intelligence, broadly refers to attempting to replicate or simulate intelligent behavior. Machine Learning and Deep Learning are subfields of AI. Machine Learning uses algorithms to analyze and predict human actions, such as detecting fraudulent credit card transactions. Deep Learning takes this a step further by utilizing hierarchical layers to enhance the machine learning process. This involves creating artificial neural networks that mimic the structure of the human brain. Deep Learning technology is commonly used in autonomous vehicles, enabling them to distinguish between traffic signs, cars and pedestrians.
