KI Park Special
Virtual Chat "Chances & Challenges wih Open Innovation to drive AI adoption"
Marcel 'Otto' Yon & Fabian Westerheide
Virtual Event | September 24, 2020 | 11.00 AM–12.00 PM CEST
About the event
Open Innovation aims to motivate companies to open their innovation processes to the outside world. Nowadays Open Innovation takes on new meaning as Artificial Intelligence significantly shakes the business world and the rapidly growing AI startup landscape demands the attention of corporates. While AI startups have been setting technological standards ever since, their adoption in corporates still lags behind.
Please register here for this Virtual ChatRegistration
In this virtual chat Marcel ‘Otto’ Yon and Fabian Westerheide discuss Chances & Challenges with Open Innovation to drive AI adoption. Marcel ‘Otto’ Yon is an AI pioneer and serial entrepreneur. Otto served as CEO of the German Armed Forces digital innovation unit under two defense ministers with a mission to accelerate disruptive innovations to the soldier and develop a lean start-up as a military capability. In a discussion with Fabian, he will share his experiences and insights on how Open Innovation can be successfully deployed in large corporations and the public sector.
Fabian Westerheide is a well-known international expert on Artificial Intelligence and the host of Rise of AI, Europe’s most influential platform for the growing Artificial Intelligence industry. The Rise of AI Virtual Chats are a series of live conversations with leading minds with the aim to share new ways not the future.
About KI Park
This special episode of the Virtual Chat Series is co-hosted by KI Park, which operates an Open Innovation platform for AI projects that provides companies with access to applied AI challenges. The KI Park initiative was founded by Deloitte and Investa with the aim to promote the application of AI and connect startups all over Europe to corporates to bring their solution into production.
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Commentary by Deloitte partner Olly Salzmann on the establishment of a reference model.