Artificial Intelligence vs. Real Intelligence: Challenges, Opportunities and Geopolitical Tensions

However unlike us, they cannot cope with different environments and circumstances that were not anticipated such that we, humans, need to step in to redesign the system whenever the conditions change. This manual approach for engineering machine learning systems is not sustainable and is reaching its limits and will eventually lead to severe impact on society are businesses, like process industries, who require more and more predictive and autonomous operations.

Wouldn’t it be a lot more effective if we could just tell a machine learning system what we wanted it to do, after which it would compose its own code to solve the problem. What makes this situation even more frustrating is that many biological systems find it easy to adapt to different environments and evolve with changing circumstances. Why can’t we have computing systems that adapt and evolve to find their own solution?

Evolutionary learning and computation are based on concepts for computing systems that could evolve to solve problems they are tasked with and do so quickly and efficiently, as opposed to humans maintaining the software for them, which is time consuming and prone to problems.

The first part of this talk will present NORCE effort on building real intelligence, taking inspiration from biological systems, with the aim to develop computing systems that can adapt, learn and evolve to their changing environments and requirements in an autonomous and manageable manner.

The second part of the talk will present the current developments in artificial / real intelligence, the op-portunities, the challenges and the trending geopolitical tensions that are impacting and shaping our soci-etal developments and business constellations.

Presented by Nabil Belbachir, Director at BoD of euRobotics Aisbl, Research Director Smart Instrumentation and Industrial Testing, NORCE