#knowledgerepresentation — Public Fediverse posts

We renamed the Information Service Engineering lecture into "Knowledge-driven AI", simply because what we teach is knowledge-driven AI :) which pertains knowledge representation, natural language processing, machine learning, and reasoning. We adapted the focus emphasizing the machine learning part by going deeper into deep learning, transformer architectures, and large language models.

#KDAI2026 #lecture @fizise @fiz_karlsruhe #AI #knowledgerepresentation #knowledgegraphs #machinelearning #nlp

We renamed the Information Service Engineering lecture into "Knowledge-driven AI", simply because what we teach is knowledge-driven AI :) which pertains knowledge representation, natural language processing, machine learning, and reasoning. We adapted the focus emphasizing the machine learning part by going deeper into deep learning, transformer architectures, and large language models.

#KDAI2026 #lecture @fizise @fiz_karlsruhe #AI #knowledgerepresentation #knowledgegraphs #machinelearning #nlp

We renamed the Information Service Engineering lecture into "Knowledge-driven AI", simply because what we teach is knowledge-driven AI :) which pertains knowledge representation, natural language processing, machine learning, and reasoning. We adapted the focus emphasizing the machine learning part by going deeper into deep learning, transformer architectures, and large language models.

#KDAI2026 #lecture @fizise @fiz_karlsruhe #AI #knowledgerepresentation #knowledgegraphs #machinelearning #nlp

We renamed the Information Service Engineering lecture into "Knowledge-driven AI", simply because what we teach is knowledge-driven AI :) which pertains knowledge representation, natural language processing, machine learning, and reasoning. We adapted the focus emphasizing the machine learning part by going deeper into deep learning, transformer architectures, and large language models.

#KDAI2026 #lecture @fizise @fiz_karlsruhe #AI #knowledgerepresentation #knowledgegraphs #machinelearning #nlp

🔍 Lecture 01 — The Art of Understanding
Before we teach machines to reason, we should ask ourselves: what is knowledge, really?
This opening lecture steps back from the algorithms and starts with first principles.
It's the philosophical foundation the rest of the course is built on. Bring your curiosity. Leave your assumptions at the door.
#KDAI2026 #AI #Epistemology #DataToKnowledge #SemanticWeb #KnowledgeRepresentation #MachineLearning #PhilosophyOfAI @fizise @fiz_karlsruhe

The recording of my @iswc_conf keynote is available online:

Wikipedia and the Semantic Web -- 20 years of co-development, and the future

Drawing on the roots of @wikipedia and the Semantic Web, how they influenced each other during the last two decades, leading to
@wikidata and peeking forward to @wikifunctions and Abstract Wikipedia.

#semanticWeb #abstractWikipedia #knowledge #knowledgeGraphs #knowledgerepresentation #wikipedia #wikidata #wikifunctions

https://videolectures.net/videos/iswc2025_nara_vrandecic_wikipedia_future

What stands out in this call is the focus on explicit models, traceability, and responsibility, from provenance and uncertainty to reproducibility. Computational methods here strengthen interpretation, not replace it. #complexityscience #knowledgerepresentation #researchdata

What stands out is the strong focus on methodological rigor and responsibility: formal models, explicit assumptions, and traceability (e.g. provenance, uncertainty, reproducibility) are treated as central to cultural research—not optional add-ons.
The call also bridges complexity science, Digital Humanities, and Semantic Web approaches, emphasizing interoperability, evaluation, and governance.
#complexityscience #knowledgerepresentation #researchdat

🚀 PMD core ontology (PMDco) v3.0.0 Release

This release marks a major milestone for the #PMD working area Semantic Interoperability and reflects several years of joint conceptual work, implementation, discussion, and validation across projects and disciplines.

GitHub: https://github.com/materialdigital/core-ontology
PMDco 3.0.0: https://materialdigital.github.io/core-ontology/index-en.html#
Docs: https://materialdigital.github.io/core-ontology/docs/

#ontologies #materialsscience #materialdigital #AI #symbolicAI #knowledgerepresentation @fiz_karlsruhe @joerg @enorouzi @lysander07

Interesting approach to lower the burden of using foundational ontologies:
J. P. A. Almeida, G. Guizzardi, T. P. Sales, R. A. Falbo, "gUFO: A Lightweight Implementation of the Unified Foundational Ontology (UFO)", 2019
https://nemo-ufes.github.io/gufo/
GitHub: https://github.com/nemo-ufes/gufo

#ontologies #bfo #ufo #semanticweb #knowledgerepresentation

https://arxiv.org/pdf/2404.18795

When Lawvere meets Peirce: an equational
presentation of boolean hyperdoctrines

by Filippo Bonchi, Alessandro Di Giorgio, Davide Trotta

Pushing algebraization of logic another step forward.

With this approach logical deductions can be made using straightforward equation manipulations.

This kind of bridge will eventually become very useful for knowledge representation!
As knowledge representation is mostly built on description logics, the community so far doesn’t appreciate the potential to enrich its toolset with algebraic methods and other existing mathematical machinery.

#categorytheory #logic #knowledgeRepresentation #cartesianBicategories #relationalAlgebra #Lawvere #Peirce #hyperdoctrines

This was an EXTREMELY interesting paper on what modern LLMs can learn from older older symbolic AI / expert system approaches to improve the validity of what those statistical models generate on their own, using the Cyc system as the contrast to the modern systems.

https://arxiv.org/abs/2308.04445

#Cyc #DougLenat #SymbolicAI #ExpertSystems #LLMs #ChatGPT #Bard #AI #KnowledgeRepresentation

Lieto, Antonio, Lebiere, Christian, & Oltramari, Alessandro (2018). The knowledge level in cognitive architectures: Current limitations and possible developments. Cognitive Systems Research, 48, 39-55.

https://doi.org/10.1016/j.cogsys.2017.05.001

#knowledgerepresentation #knowledgeprocessing #semanticmemory #cognitivearchitectures #cognitivesystems #ArtificialIntelligence #cognitivemodelling #computationalcognitivescience #AI

#Introduction: I'm a ML researcher and entrepreneur based in Taiwan.

My research focuses on virtual #KnowledgeGraphs and automated #KnowledgeRepresentation

Other scientific interests include #explainableai #nlp and #reinforcementlearning.

I'm also a #CFA charterholder and previously served as Head of #optionstrading for a French investment bank and MD of Equity Strategies for a US endowment.

In my spare time, I enjoy #fencing and #cooking.

Glad to join this community!