AI for Automated Driving – Challenges and Solutions
Automated Driving is generally seen as one (if not the) “next big thing” in automotive. While many assistance functions are already available on modern mid-range and high-end cars and the vision of full automation appears within reach, there are still big steps to be made. The complexity and the unpredictability of road traffic out there pose huge challenges which cannot be met by classical algorithmic solutions. Instead, Artificial Intelligence (AI) — essentially meaning systems which learn from data and are able to abstract from individual sample scenes — will be required to reach true automation. This talk will take you on a tour looking at the different parts of an automation system and shedding some light on the particular challenges and technological approaches and solutions.
Data Engineering and the Cloud: Simplicity Empowers Everyone
Over the past two decades, we have watched as data has become increasingly strategic to nearly every organization. During that time we have lived through the evolution from Big Data (new challenges) to Data Science (new projects) to Data Engineering (new practices). The next step is now in sight: an open and inclusive Data Engineering Cloud that brings together a diversity of stakeholders to transform business, science and government.
Getting this right requires a “big tent” approach that connects data experts and domain experts, hand-coders and no-coders, engineering discipline and analytic agility. In this context, new technologies and tools for data engineering and data science are key to bringing these constituencies together, and empowering all the players—whether they are data experts or subject matter experts—to work effectively and work together. In this talk I will show what an inclusive Data Engineering Cloud looks like, and how a decade of innovation in computer science—from AI to interactive visualization to program synthesis to data operations—can enable the transformational promise of data.