New technologies disrupt our daily life and the well established structures in our societies. The Disruptive Technologies track at GOTO Copenhagen 2016 includes cool examples of technologies that will disrupt traditional business areas like transportation, education, healthcare, personal banking, insurance, energy etc.
Watch the videos from the Disruptive Technologies – Case Studies track at GOTO Copenhagen 2016 below.
Taking Storage for a Ride
with René Schmidt, Senior Staff Engineer at Uber
In this talk, we dive into how the storage systems have evolved from the early days of Uber until today. In a rapidly growing business, the storage requirements grow exponential year over year. This poses a challenge to the evolution of the storage systems both in terms of performance, capacity, and operational efficiency. We go into the details on the decisions that we made and techniques that we have found useful in design of these systems, and on the importance of tooling and automation around operations, since all changes must be made online with no downtime or service disruption. Most systems starts out small, but when you grow with ~20% a month, small things get big rather quickly.
Automated driving – Are we taking the Human Factors Researcher out of the Loop?
with Sanna Pampel, Research Fellow for Automotive Human Factors at the University of Nottingham
Automation is the replacement of tasks previously conducted by humans with machines or computation. It is anticipated that within a few years it will be possible to replace the human driver by fully automated vehicles. This would mean that the traditional role of human factors in driving would change. However, having cars making decisions on an autonomous basis presents a new set of challenges that cannot be resolved without taking the human factor into account.
The presentation starts with a journey into levels of automation, state-of-the-art technology and hot topics in current research. Then we will look into the future, into a world with fully autonomous vehicles, and consider the role of human factors, exploring issues such as the acceptance by other road users, the predictability of autonomous behaviours, as well as the acceptance by vehicle ‘drivers’ and passengers. Decisions based on artificial intelligence and deep learning provide particular challenges. For example, the Google car accident illustrates how machine learning can pick up bad habits of humans. The presentation will provide an outlook into possible human factors solutions.
Everything Floats: A Look into the Chinese Mirror
with Gert Sylvest, Co-Founder and SVP of Global Network Strategy at Tradeshift
Sometimes when you shift your position of view you get a fresh perspective on what you are doing. Tradeshift went to China first time in 2013 and is now on it’s way to form it’s 2nd joint venture there. Gert talks about how connecting businesses in social technology based networks globally may have the power to fundamentally disrupt the way that supply chains, finance and the relationships between companies works. Our experiences in China help put this into perspective and illustrate the disruptive potential of connecting companies. This is about a technology driven transformation of business relationships that could not have come about without cloud, exponential technologies, and one that bears promises of tearing down old barriers – between the inside and the outside of companies, trade and finance, and digital divides.
How Software Lifecycle Integration and DevOps are transforming car development
with Neelan Choksi, President and COO of Tasktop
Why is it that the industry that created lean manufacturing is having such difficulties applying the concepts of lean to software delivery? Given that software is now the most expensive part of the modern automobile, the companies that solve this problem will be able to innovate far beyond their peers. However, lean software delivery has been very notoriously difficult to achieve at enterprise scale, no matter what the industry, and connecting it to manufacturing adds another level of complexity. In this talk, we examine this problem, and propose a new layer of infrastructure that we believe will yield a 2x improvement in the efficiency of automotive software delivery and pave the path to the goals of Industry 4.0.
Over the past decade, two key trends have been key in improving the efficiency of software delivery for small and mid-sized organizations. Agile development has provided a framework for shortening iterations and adapting to ever changing requirements. DevOps establishes a conceptual foundation for automating every part of the software delivery pipeline. However, scaling these concepts to large organizations with hundreds or thousands of engineers has been challenging and failure prone. It’s time to take a value-stream oriented view on the end-to-end process of how software is built, and how it interacts with physical devices and the Internet of Services, bills of material, and the automotive supply chain.
This talk presents two new concepts. First, the “integration patterns” that define how work flows from a requirement to the road. These include requirements traceability, defect unification, and software supply chain management. Second, we provide a framework for the new integration infrastructure that must be created in order to implement these integration patterns to achieve end-to-end flow across the value stream. We then outline the key lean metrics, such as lead time, velocity, and mean time to resolution, that provide the key measures of the effectiveness of the software value stream. We conclude the presentation with a case study of how this approach to Software Lifecycle Integration has been deployed by visionary organizations in the automotive domain.