Artificial Intelligence

In the ever-evolving landscape of manufacturing, Artificial Intelligence (AI) presents both significant opportunities and substantial risks. While AI can drive efficiency, innovation, and enhanced cybersecurity, it also introduces challenges that must be carefully managed to ensure safety and trust. This

Generative AI can make AI insights more accessible to shop floor operators, allowing them to make better decisions without having to understand complex data or algorithms. For example, generative AI could help operators understand what the next best action is to

Generative AI is transforming the manufacturing industry by offering innovative solutions to enhance efficiency, improve product design, and optimize processes. Let's explore three specific ways generative AI can be applied to jobs in manufacturing, providing concrete examples for each. 1. Enhancing

Birth of AI. Winter The terms "artificial intelligence" and "machine learning" began shaping the technological landscape in the mid-20th century, with the official birth of AI at the Dartmouth Conference in 1956. John McCarthy and his colleagues coined "artificial intelligence" there.

In the evolving landscape of industrial IoT, the ability to identify anomalies is not just a luxury but a necessity. This blog post shows how AI-driven anomaly detection is transforming how industries operate and setting new standards in efficiency and

While most of the attention around AI in recent years has gone to consumer-focused applications like text generation and image creation tools, businesses are also adopting AI for more practical uses in the physical world. In this article, you will

The world is surrounded of problems to solve at the same time companies need to use innovation to offer new products and new services for their customers. There are several technologies already available to be combined by smart teams to

The oil and gas industry is undergoing a profound transformation, driven by a realization among plant managers and engineers of the imperative to reassess business processes related to fugitive emissions. There's a compelling need to modernize emissions detection, moving from

The proliferation of artificial intelligence (AI) in business-to-consumer markets is driven by great minds and significant investments, harnessing simulated human reasoning for autonomous problem-solving. As AI gains momentum, it is crucial to separate technical milestones from promotional hype and focus