AI in Manufacturing – Impacts and Benefits

You’ll come out of this webinar learning: How cyberattacks make their way into environments, The critical role of endpoint protection, Gaps in protection, Tactics to stop attacks in their tracks, If an attack does get through, find out how to respond with proven recovery methods.

The biggest question facing data science and ML teams is how to strike the right mix of MLOps tools, culture, and practices to create enterprise-grade ML platforms suited for their needs.

All security professionals have heard of ransomware, but few truly understand that mobile devices are a key delivery mechanism into the enterprise. Hackers are attacking mobile devices since most have little protection. Data theft is one objective, but finding ways to deliver ransomware is equally important.Ransomware is very real; as is the possibility of enterprises and government agencies being at risk by an employee whose mobile device was hacked. According to a 2018 study, the average cost per ransomware attack to businesses last year was $133,000, with 54 percent of companies having been hit by attacks last year.

In contrast to humans, all decisions made by algorithms are systematic and based on user data, sensors, and algorithms. The question is, who is responsible for errors: the provider, the integrator, or the end-user? In most scenarios, responsibility is distributed amongst all stakeholders. Full autonomic systems (including self-driving technology) are not accepted by lawmakers, and a human supervisor is demanded as a backup. Thanks to behavioral science, research knows that humans can be influenced and manipulated by Artificial Intelligence. This is comparable to the animal kingdom in which an alpha rules the pack, but the beta is able to manipulate the alpha.