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Calculemus!
The only way to rectify our
reasonings is to make them as
tangible as those of the
Mathematicians, so that ...
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Semantic &
Exploratory
Search
Recommender
Systems
Question
Answering
Data
Integration
Visualizations
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dbr:Neil_Armstrong rdfs:label Neil Alden Armstrong"@en ;
dbo:birthDate “1930-08-05”^^xsd:date ;
dbo:birthPlace dbr:Wapa...
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2019
The Power of AI and Knowledge Graphs
Karlsruhe, Germany, 9-12 Sep 2019
https://2019.semantics.cc/
The Sorcerer’s Apprentice  or  Why Semantics still matters and why we should not only trust in ML
The Sorcerer’s Apprentice  or  Why Semantics still matters and why we should not only trust in ML
The Sorcerer’s Apprentice  or  Why Semantics still matters and why we should not only trust in ML
The Sorcerer’s Apprentice  or  Why Semantics still matters and why we should not only trust in ML
The Sorcerer’s Apprentice  or  Why Semantics still matters and why we should not only trust in ML
The Sorcerer’s Apprentice  or  Why Semantics still matters and why we should not only trust in ML
The Sorcerer’s Apprentice  or  Why Semantics still matters and why we should not only trust in ML
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The Sorcerer’s Apprentice or Why Semantics still matters and why we should not only trust in ML

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Artificial intelligence (AI) is penetrating our daily life and has become an important factor for research and economic growth. But with every new success story, false expectations are awakened again and again, and this follows a long tradition. Today, AI is mostly understood as machine learning, especially deep learning, whose recent successes are responsible for the current popularity of this term. However, due to some unique ability of an AI system, limited to a narrowly focused field of application, often unjustified generalizations about its actual "intelligence" are made. In this talk, we show that AI can not only be reduced to deep learning, but must also consider symbolic knowledge representation, as well as planning and optimization.


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The Sorcerer’s Apprentice or Why Semantics still matters and why we should not only trust in ML

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  28. 28. 32 Calculemus! The only way to rectify our reasonings is to make them as tangible as those of the Mathematicians, so that we can find our error at a glance, and when there are disputes among persons, we can simply say: Let us calculate [calculemus], without further ado, to see who is right.
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  32. 32. 36 Semantic & Exploratory Search Recommender Systems Question Answering Data Integration Visualizations
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  45. 45. 52 dbr:Neil_Armstrong rdfs:label Neil Alden Armstrong"@en ; dbo:birthDate “1930-08-05”^^xsd:date ; dbo:birthPlace dbr:Wapakoneta,_Ohio ; dbo:deathDate “2012-08-25”^^xsd:date ; dbo:deathPlace dbr:Cincinnati,_Ohio ; dbo:occupation dbo:Astronaut ; dbo:almaMater dbr:Purdue_University , dbr:University_of_Southern_California . ... dbr:Neil_Armstrong rdfs:label Neil Alden Armstrong"@en ; dbo:birthDate “1930-08-05”^^xsd:date ; dbo:deathDate “2012-08-25”^^xsd:date ; dbo:occupation dbo:Astronaut . ...
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  52. 52. 2019 The Power of AI and Knowledge Graphs Karlsruhe, Germany, 9-12 Sep 2019 https://2019.semantics.cc/

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