In the cybersecurity sector, artificial intelligence testing is crucial. This is because AI has the potential to help cybersecurity overcome some of its major obstacles. And there are many obstacles, including the incapacity of many organizations to stay on top of the numerous new risks and attacks that emerge as the internet and technological usage increase. AI-powered cybersecurity is expected to change how we respond to cyber attacks. Because of its capacity to study and learn from enormous volumes of data, artificial intelligence will be crucial in identifying sophisticated threats.

AIMLSystems is a brand new conference targeting research in the intersection of AI/ML techniques and systems engineering. Through this conference we plan to bring out and highlight the natural connections with these two fields. Specifically we explore how immense strides in AI/ML techniques are made possible through computational systems research (e.g., improvements in CPU/GPU architectures, data-intensive infrastructure, communications etc.), how the use of AI/ML can help in the continuous and workload-driven design space exploration of computational systems (e.g., self-tuning databases, learning compiler optimizers, learnable network systems etc.) and, the use of AI/ML in the design of socio-economic systems such as public healthcare, and security.

The development of artificial general intelligence is considered by many to be inevitable. What such intelligence does after becoming aware is not so certain. To that end, research suggests that the likelihood of artificial general intelligence becoming hostile to humans is significant enough to warrant inquiry into methods to limit such potential. Thus, containment of artificial general intelligence is a timely and meaningful research topic. While there is limited research exploring possible containment strategies, such work is bounded by the underlying field the strategies draw upon. Accordingly, we set out to construct an ontology to describe necessary elements in any future containment technology. Using existing academic literature, we developed a single domain ontology containing five levels, 32 codes, and 32 associated descriptors. Further, we constructed ontology diagrams to demonstrate intended relationships. We then identified humans, AGI, and the cyber world as novel agent objects necessary for future containment activities.

We know that Cities need to increase the efficiency in which they operate and use their resources. Major efficiency improvements can be achieved by horizontally interconnecting individual systems such as electricity, water, sanitation and waste management, transportation, security, environmental monitoring, or weather intelligence. Researchers predict that by 2050, 66% of the world's population is expected to live in urban areas. The challenge, here, will be to supply these populations with all these basic resources while ensuring overall economic, social, and environmental sustainability. Digital Transformation with its intent of making the citizen's lives better, is accelerating the process of transformation of urban centers to the smart cities.