Artificial Intelligence

There is a high demand for AI solutions in industrial applications. These solutions need to be efficient, trustworthy and secure in order to be used in series production or quality control.. However, the new possibilities opened up by generative AI also raises questions. Can users rely on what a chatbot says? How can vulnerabilities in an AI model be detected early on during development?

Active learning is a machine learning paradigm that involves the model actively selecting the most informative data points for training, rather than relying solely on randomly chosen samples, with the goal of achieving higher accuracy with fewer labelled examples. In traditional supervised learning, a model is trained on a fixed dataset with pre-labelled examples. However, labelling data can be expensive and time-consuming.

Manufacturing technology company, CloudNC, has announces the release of Cutting Parameters AI, a new solution that automatically generates appropriate physics-based feeds and speeds for virtually any CNC machining scenario, in moments.

Vision systems equipped with artificial intelligence (AI) capabilities have the ability to learn and distinguish between objects, as well as recognize defects or irregularities in products or processes.

With advancements in artificial intelligence (AI) and machine learning (ML), manufacturers are now embracing innovative solutions to enhance quality control processes. AI is revolutionizing quality control in manufacturing, improving efficiency, accuracy, and overall product quality.

The Karlsruhe Institute of Technology (KIT) has developed a process that automatically evaluates the surface conditions of objects using video images, neural networks and machine learning. Intelligent surface inspection can help to improve defect testing.

According to a report released by MIT Sloan Management Review and Boston Consulting Group, an increasing number of companies are using AI to make KPIs more forward-looking and connected, dramatically improving legacy performance metrics.

Siemens is releasing a new generative artificial intelligence (AI) functionality into its predictive maintenance solution – Senseye Predictive Maintenance.

The amount of compute happening at the edge is growing fast because that is where data is generated. In addition, many edge computing deployments are incorporating AI.