Most of us already know that adopting new cloud applications can boost a business's productivity by enabling organizations to be more agile and ready to change course in our fast-moving and connected digital world. But the rapid adoption of cloud apps and services also brings with it profound security threats, including visibility and control challenges that aren't present in traditional on-premises environments. At the same time, the cloud - because of its interconnected, flexible and adaptable nature - can also provide new possibilities for addressing cloud security problems. By leveraging the power of the cloud with a data science and machine learning cloud-based solution, security and risk professionals can solve many of the traditional security challenges found in popular apps like Office 365, Google Drive, Salesforce and Box. In her session at 19th Cloud Expo, Deena Thomchick, Senior Director of Cloud Security at Symantec, detailed how cloud-based data science, machine learning, computational analysis and intelligent algorithms can work together to help to deliver truly intelligent and responsive security and compliance for the cloud.

Summary: Whether you are a startup person or data science-minded executive in a larger organization what logic can you apply to spot the most compelling opportunities for AI in your organization. In 2014 Kevin Kelly, founder of Wired magazine and prolific futurist famously said, "The business plans of the next 10,000 startups are easy to forecast: Take X and add AI." Kevin you were clearly right. The Silicon Valley and every other tech startup haven are awash in companies trying to fulfill his vision. However, whether you are a startup person or data science-minded executive in a larger organization that's not enough information to spot compelling opportunities. What are the rules or guidelines you can apply to identify these transformative applications?

While the application areas addressed typically - Social Interaction operate at a macroscopic scale and could not be considered quantum in a quantum mechanical sense, they may - Finance, economics, and social structures (e.g., organizations, share many key properties with quantum systems. Each paper was thoroughly reviewed by at problems with AI in non-quantum domains more efficiently least three members of the international programme committee. Kanerva (Stanford University), and an invited talk on day - Logic, planning, agents and multi-agent systems 2 by Terry Bollinger (ONR/MITRE). Finally, welcome and we look forward to a stimulating symposium!