People from across the AI world came together in London for the Artificial Intelligence Conference. Below you'll find links to highlights from the event. Raffaello D'Andrea presents his vision of how autonomous indoor drones will drive the next wave of robotics development. Get a free trial today and find answers on the fly, or master something new and useful. Marta Kwiatkowska provides an overview of techniques being developed to help improve the robustness, safety, and trust in AI systems.

Academic machine learning involves almost exclusively offline evaluation of machine learning models. In the real world this is, somewhat surprisingly, often only good enough for a rough cut that eliminates the real dogs. For production work, online evaluation is often the only option to determine which of several final-round candidates might be chosen for further use. As Einstein is rumored to have said, theory and practice are the same, in theory. So it is with models.

Francesca Lazzeri is a senior machine learning scientist at Microsoft on the cloud advocacy team and an expert in big data technology innovations and the applications of machine learning-based solutions to real-world problems. Her research has spanned the areas of machine learning, statistical modeling, time series econometrics and forecasting, and a range of industries--energy, oil and gas, retail, aerospace, healthcare, and professional services. Previously, she was a research fellow in business economics at Harvard Business School, where she performed statistical and econometric analysis within the technology and operations management unit. At Harvard, she worked on multiple patent, publication and social network data-driven projects to investigate and measure the impact of external knowledge networks on companies' competitiveness and innovation. Francesca periodically teaches applied analytics and machine learning classes at universities and research institutions around the world.