Where content, #knowledgeManagement, and #AI converge, you'll find Michael Iantosca.
As many in the AI world choose probabilistic models like LLMs, Michael takes a deterministic approach to #contentManagement and #knowledgeEngineering, using #ontologies and #knowledgeGraphs to ground content in facts.
This approach embodies his insight that content and the models that describe it are valuable enterprise IP assets.
Introducing #EKAW24 2nd keynote speaker 
𝐒𝐮𝐳𝐚𝐧 𝐕𝐞𝐫𝐛𝐞𝐫𝐧𝐞
We are looking forward to the keynote
"Is the Search Engine of the Future a Chatbot?" 
Find more information about the keynote talks at https://event.cwi.nl/ekaw2024/keynotes.html
Find more about #EKAW24 𝙏𝙪𝙩𝙤𝙧𝙞𝙖𝙡 on
Semantic Knowledge Modeling -
Ontologies & Vocabularies
at https://metaphacts.com/ekaw24-semantic-modeling-tutorial
A few days left for 𝗣𝗼𝘀𝘁𝗲𝗿𝘀 & 𝗗𝗲𝗺𝗼𝘀!
Submit your
late-breaking results 
on-going projects 
innovative prototypes
P&Ds in #EKAW24 are great opportunity for
invaluable input 
effective feedback 
starting collaborations
Check the call at https://event.cwi.nl/ekaw2024/cfpd.html
𝐖𝐨𝐫𝐤𝐬𝐡𝐨𝐩 ELMKE
Evaluation of Language Models in
Knowledge Engineering
Submissions:
Long 10-15 pages
Short 5-9 pages
Deadline September 17
Find more at: https://sites.google.com/view/elmke
#LanguageModels #KnowledgeEngineering #OntologyEngineering #Evaluation #Workshop #EKAW24
One essential conclusion of Giorgia Lodi's keynote at #ISWS2024: #GIGO - the (in)famous Garbage-In-Garbage-Out is a universal computing principle, which also cannot be changed via #AI and #LLMs. Couplig with data, information, and knowledge that is curated by domain experts is essential for constructing dependable (#LLM-based) solutions!
...quoting @kidehen OpenLink Software
When using knowledge engineering methodologies,...
- data quality increases
- domain experts start to understand the importance of semantics
- more participation - but understanding is the key challenge
- costs will be rising
- even technicians consider it as too complex for aplications development
Lessons learnt from knowledge engineering presented by Giorgia Lodi in her #ISWS2024 keynote
In the next #ISWS2024 tutorial Aldo Gangemi is addressing the principles of extensional vs. intentional modeling in #knowledgegraphs.
Interesting, how knowledge engineering requirements have evolved over time ;-)
from the slides of Paul Groth's tutorial on #knowledgegraph creation at #ISWS2024
referencing Bradley P. Allen, Filip Ilievski, Saurav Joshi, Identifying and Consolidating Knowledge Engineering Requirements, https://arxiv.org/abs/2306.15124
#ESWC2024 closing ceremony led by general chair @albertmeronyo with lots of thanks, acknowledgements, and of course....awards ;-)
Reflections on the Special Track on LLMs for Knowledge Engineering at #ESWC2024.
From my point of view a very valuable contribution to the conference, exchanging our experiences and research efforts as long as there are no established methodologies and evaluations in this field.
#llms #knowledgeengineering #knowledgegraphs #ontologydesign #ontologicalengineering ontologies
Knowledge Engineering is transforming. This is what we're going to need.
...Conclusion of Elena Simperl's keynote at #ESWC2024
FIrst #ESWC2024 Keynote by Elena Simperl on "Knowledge Engineering from people to machines and back" dives into the history of knowledge engineering and reminds us about the many different approaches ranging from people, over more people, gamification, crowdsourcing, automation, etc.
Tolle Neuigkeiten: Für seine herausragenden Beiträge im Bereich #KnowledgeEngineering wurde #TIB-Direktor und @L3S_Research_Center@wisskomm.social-Mitglied @soeren_auer auf Platz 33 als „#AI 2000 Most Influential Scholar Honorable Mention“ zwischen 2014 und 2023 ausgezeichnet und zählt damit zu den einflussreichsten #KI-Forscher:innen. Herzlichen Glückwunsch! 
Information Service Engineering is the denomination of our research group at @fiz_karlsruhe as well as of my chair at @KIT_Karlsruhe
...and this is how #Midjourney imagines how "Information Service Engineering" might look like ;-)
Our research focus lies on on #knowledgegraphs
#informationextraction
#knowledgeengineering
#ontologies #researchdatamanagement
#exploratorysearch #semanticsearch
#nlp #aiart #generativeai @sourisnumerique @tabea @sashabruns @MahsaVafaie @enorouzi
Check out the call for papers for the special issue of the new Neurosymbolic AI Journal on "Knowledge Graphs and Neurosymbolic AI".
Deadline May 31, 2024.
Contributions may include full papers, dataset descriptions, survey papers, application reports and reports on tools and systems.
Editors: Marta Sabou, Raghava Mutharaju, Frank van Harmelen
#neurosymbolicAI #AI #knowledgeengineering #knowledgegraphs #semanticweb #machinelearning #humancentric
via #linkedIn
#ExplainableAI for #LLM systems whether chatbots or backend components is very important for trustworthiness and debugging.
One of the most effective ways to do it is to make the chatbot refer to sources of facts. Tag every RAG document partial with an anchor, and tell the chatbot refer to them. Then you can show in a final presentation a link to the document part used.
In a document index you similarly want to include metadata for partials, so that a user can click "show the whole document" and navigate the information if they want to see where the content came from.
It's all very well explainable but requires a bit of work in #KnowledgeEngineering and #LinkedData.
With the release of my restored versions of #FMCS and #Babylon I plan on posting more about #SymbolicAI programming techniques and algorithms, the #KnowledgeEngineering approach to #MachineLearning, and why #DemonicMetaprogramming (as in, #Metaprogramming under the semantics of demonic nondeterminism) is so important for them
Whenever applicable, I will include side-by-side comparisons of #Babylon and #KnowledgeWorks as well
I’ve restored Jürgen Walther’s #Babylon #AIWorkbench system for #CommonLisp from the CMU AI Repository, released under the #MITLicense and available from #Ultralisp or directly from the #GitHub repo linked below
Babylon provides a comprehensive set of tools for #SymbolicAI programming and metaprogramming, such as frames, productions, propositional and predicate logic, constraint satisfaction, expert systems, demonic metaprogramming via #FMCS, to build #KnowledgeEngineering based systems
It’s basically an #OpenSource version of #KnowledgeWorks from #LispWorksEnterprise (although I’ve made no attempt to optimize or benchmark performance of Babylon against KW at this stage)
Naturally I plan to extend Babylon with all the tools necessary for #ConnectionistAI programming as well
