The Real World Potential and Future Development

  • TYPE: Combined Session DATE: Wednesday, November 27, 2019 TIME: 12:00-13:00 LOCATION: Session Room 1


The talk will explore the evolution of complexity in data sets and the evolution of complexity in the algorithms that deal with them. References will be made to simple datasets demonstrating simple machine learning models up to more complex datasets such as images, text and now non-euclidean datasets - such as point clouds, graphs, manifolds, geospatial datasets and network like data structures that represent highly complex interactions in systems-of-systems. The talk will also make references to a new family of powerful deep learning methods such as Graph neural networks and their applications to non-euclidean data domains. 


Pooja is an engineer in Electronics and Communication with a post graduate degree in Systems and Signal processing from the University Of Southampton, UK. After her masters she worked in the biomedical industry in the UK for about 4 years. She worked at Equivital in Cambridge, UK as a Biomedical...

Imagine someone enters the room. What is the first thing we do?
In milliseconds we have an assessment: Good or bad. Friend or foe.  
Most of the time we are not even aware of this mental process. It’s part of our survival instinct, deeply rooted in our DNA. This judgement is based on experience which results in patterns we try to match so we can make immediate decisions.  
This speech is about how to apply this survival strategy into a digital model - call it AI, Machine Learning, or something else -  that allows us to protect our digital life from evil.


Matthias Canisius has been Regional Director CE & EE of SentinelOne since May 2018 and is responsible for the strategic and operational business development of the company in Central and Eastern Europe.  Matthias Canisius brings more than 20 years of business development experience...


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AImpact Summit 2019

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€1200.00 $1500.00 S$1920.00 13200.00 kr
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Ms. Lauren Zuber
+49 211 23707725
  • Nov 27 - 28, 2019 Munich
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