Talk & Panel: Responsible AI: Trust, Fairness, and Transparency in Machine Learning at the appliedAI Ecosystem Meetup in Munich, 14. January 2019
Around 150 attendees participated in the appliedAI Ecosystem Meetup on Artificial Intelligence in Munich and Partners. Challenging talk on #ResponsibleAI: Trust, Fairness, and Transparency in Machine Learning – and interesting panel with Leon Szeli and Fabian Mader. AI and ML…
MOOC: Industrial Artificial Intelligence at Siemens – from the impact of Deep Learning, the creation of Conversational AI, to AI-centric API ecosystem
Awesome – finishing the MOOC on Artificial Intelligence at Siemens – from the impact of Deep Learning, the creation of Conversational AIs, to the acceleration via an AI-centric API ecosystem. Proud to push the Siemens AI Lab further – accelerating…
End-to-End Trainable Attentive Decoder for Hierarchical Entity Classification
Abstract: We address fine-grained entity classification and propose a novel attention-based recurrent neural network (RNN) encoderdecoder that generates paths in the type hierarchy and can be trained end-to-end. We show that our model performs better on fine-grained entity classification than…
AI & Machine Learning Research with Meaningful Impact
I am curious about the foundations of computational intelligence, specifically methodologies that bridge the areas of connectionist and symbolic learning applied to real-world AI and NLP applications. I am passioned about enabling an open, interdisciplinary research & innovation culture with…
Natural Language Access to Enterprise Data
Abstract:This paper describes USI Answers — a natural language question answering system for enterprise data. We report on the progress towards the goal of offering easy access to enterprise data to a large number of business users, most of whom…
