Towards Trustworthy AI through Neural-Symbolic Unification
- Date
- Nov 24, 2021
- Time
- 3:15 PM - 4:45 PM
- Speaker
- Tiansi Dong
- Affiliation
- University Bonn and ML2R
- Language
- en
- Main Topic
- Informatik
- Host
- ScaDS.AI Dresden/Leipzig
- Description
- Symbolic reasoning is explainable, rigor, but brittle to noisy inputs. Deep learning overcomes these weaknesses at the cost of the explanability and the rigor of symbolic approach. In this talk, I show the possibility for a precise unification of symbolic structure and vector embedding. The unified representation inherits elegant features from both parent sides, namely, explanability, rigor, robust, and trustworthy. This shapes a new style of AI.
- Links
Last modified: Nov 22, 2021, 7:04:11 PM
Location
Online, please follow the internet link. (https://events.scads.ai/event/4/)
Organizer
Center for Information Services and High Performance ComputingZellescher Weg12-1401069Dresden
- Phone
- +49 351 463-35450
- Fax
- +49 351 463-37773
- TUD ZIH
- Homepage
- http://tu-dresden.de/zih
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