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Quality Assurance for AI Software and Machine Learning

The time when artificial intelligence (AI) was limited to labs and research groups is long gone. Its widespread presence in the internet-related industry (search engines, social networks, e-commerce) is now obvious to practically everyone, and we can no longer imagine the IT world without it. Today, the application of AI has spread to all kinds of industries, including those where reliability and safety are critical, and where strict regulations apply. And since quality assurance (QA) is an essential contributor to safety, it has become necessary to develop QA and regulatory frameworks for higher risk AI applications.

When SCADA is the right solution

Throughout Cosylab’s past work of developing supervisory control and data acquisition (SCADA) solutions, we’ve noticed a lack of understanding of the SCADA role in a system when we are asked to provide a SCADA solution. This lack of understanding poses a risk when it comes to whether our customers will find our solution useful for their work in the end or not. Since it is in our best interests to provide useful solutions to our customers and since this is also what we strive for, I’ve decided to share what I see as a role of a SCADA. In the case when a SCADA is really the right solution for the given problem, then I list the questions that need to be asked to design a SCADA solution that will be useful. My ultimate aim is to bring clarity to those thinking about whether they need a SCADA or not.

How the patient safety system contributes to high availability at MedAustron

We explore how a well-constructed patient safety system is able to integrate tightly with a Dose Delivery System and how it contributes to an overall High Availability system. High Availability is an important success factor in the exploitation of capital-intensive medical facilities, such as particle therapy.