Synopsis: Automotive functionality is becoming increasingly defined by software, enabling new features as well as feature growth during the service life of the product​.

There is a strong demand for unsupervised automation, where the vehicle system is responsible for the dynamic driving task. It is important to understand the challenge of making sure that the system is sufficiently safe, and also how to make use of fleet data in that process. Concept and architecture of the development machine will be presented, along with needs and opportunities for third party interaction to enable future competitiveness, supported by new knowledge, tools, and system SW/HW components.

Synopsis: Founded in Sweden in 1919, Electrolux is a global leader in appliances for households. We shape living for the better by reinventing taste, care and wellbeing experiences, making life more enjoyable and sustainable for millions of people. With connected and more intelligence appliances we want to deliver improved performance and better results with customized experience based on user-specific inputs and needs. Our challenge is the combination of new sensors, IoT data and machine learning algorithms deployed in the cloud or optimized for the machines, to make our applications smarter.

Synopsis: Reducing unplanned breakdowns is key success factor for long term sustainable production. Utilizing Artificial Intelligence in predictive maintenance is a major step to understand asset health, and to maximize technical availability through eliminated unplanned breakdowns.

Synopsis: AI research at GE covers a wide range of industrial and medical applications. An overview of the types of AI technologies being developed and their applications across multiple domains will be presented. Topics include machine perception and computer vision for inspection, automation, and performance enhancements, as well as Digital twins for predictive maintenance and schedule optimization. We will also discuss how the Science of AI may help ensure robustness, trust and security in AI systems and algorithms.

Synopsis: We want to look at what can add new value to our grocery stores – store operations, business model and concepts such as sustainability (sustainable business models, food waste, energy solutions, subscription models etc.) and store efficiency (scan & pay, amazon go, micro fulfillment, AI coach, etc.) are prioritized.

Computer Vision (CV) as a technology is very interesting and we want to broaden our knowledge related to streamlining and developing better store concept solutions. We already see today retail players who use CV technology for various purposes such as unmanned stores, robots for identification of signals and in-store deviations, automated staff-assistance and reduces queues and check-out problems as well as security.

Synopsis: Nvidia is a global technology company headquartered in the USA but with substantial research and development activities in Israel. The company offers advanced system chip and SW frameworks to integrated with strong AI capabilities solutions for professional industries around the world. Nvidia is focusing heavily on cyber security and in enabling their customers to achieve new levels of improved cyber security through its product offerings. Of particular interest is to collaborate on cyber security issues related to Nvidia’s embedded processing units within the industries of automotive, healthcare, video/retail analytics and Smart City.

Synopsis: MobilityXlab is a collaboration innovation hub founded by six global companies to create and develop new innovations within future mobility. The company offers young companies with pioneering ideas within mobility and connectivity the opportunity to accelerate via their network and strategic partnerships. MobilityXlab is focusing heavily on Smart Transport Systems, to meet increased transportation demands while also working towards reaching the United Nations Sustainable Development Goals. The future brings with it challenges of having to move more people and goods with less energy consumption and decreased pollution.

Of particular interest to MobilityXlab is collaboration on issues related to demand-responsiveness, flexible and convenient transit solutions enough to outcompete the private car as well as route optimization as well as issues of combining transport of goods and people and solutions for multi-modal transport systems. Hence, MobilityXlab is looking for innovative system solutions that go beyond simple ride-sharing apps.