Recent searches

No recent searches

Search options

Not available on lingo.lol.
lingo.lol is one of the many independent Mastodon servers you can use to participate in the fediverse.
A place for linguists, philologists, and other lovers of languages.

Administered by:

Server stats:

55
active users

lingo.lol: AboutProfiles directoryPrivacy policy

Mastodon: AboutGet the appKeyboard shortcutsView source codev4.4.3

#symbolicAi

0 posts0 participants0 posts today
Dr. Anna Latour

One month left to apply!

If you are looking for a PhD position and are interested in working on probabilistic inference, sensitivity analysis, and decision-making, this might be the job for you! We are looking for candidates with a strong background in Computer Science, and ideally also in Mathematics.

Please apply by 31 August. We're looking forward to reading your application!

careers.tudelft.nl/job/Delft-P

#AcademicJobs
#AcademicMastodon
#GetFediHired
#AcademicJob
#SymbolicAI
#Statistics
#AI
#ConstraintProgramming
#CombinatorialOptimisation
#SensitivityAnalysis
#FormalMethods
#CombinatorialOptimization
#Delft
#TUDelft
#AcademicChatter

careers.tudelft.nlPhD Position Symbolic AI and Reasoning Under UncertaintyPhD Position Symbolic AI and Reasoning Under Uncertainty
*
Dr. Anna Latour

Hi everyone,

I feel like a re-introduction is long overdue!

My name is Anna, and I'm an assistant professor of Algorithmics at the Delft University of Technology, specialising in combinatorial optimisation, symbolic AI, constraint programming, propositional model counting, operations research and reasoning under uncertainty.

I'm a nerd, a feminist and a traveller, not always in that order.

In my spare time I like to hike and go geocaching. I try to go swing dancing a few times a week. I am a Trekkie. I want to learn how to draw. I am an Indomie and Obsidian enthusiast. Based in the Netherlands, I miss Belgium, Canada and Singapore.

Since a job in academia somehow always is personal, I have chosen to mix professional interactions with the more personal ones on this platform. At least for now. Obviously, my opinions do not necessarily reflect those of my employer yadiyadiyada.

Hope to keep interacting with you all!

#Introduction#AcademicMastodon#Algorithmics
*
Miguel Afonso Caetano

Gary Marcus is onto something in here. Maybe true AGI is not so impossible to reach after all. Just probably not in the near future but likely within 20 years.

"For all the efforts that OpenAI and other leaders of deep learning, such as Geoffrey Hinton and Yann LeCun, have put into running neurosymbolic AI, and me personally, down over the last decade, the cutting edge is finally, if quietly and without public acknowledgement, tilting towards neurosymbolic AI.

This essay explains what neurosymbolic AI is, why you should believe it, how deep learning advocates long fought against it, and how in 2025, OpenAI and xAI have accidentally vindicated it.

And it is about why, in 2025, neurosymbolic AI has emerged as the team to beat.

It is also an essay about sociology.

The essential premise of neurosymbolic AI is this: the two most common approaches to AI, neural networks and classical symbolic AI, have complementary strengths and weaknesses. Neural networks are good at learning but weak at generalization; symbolic systems are good at generalization, but not at learning."

garymarcus.substack.com/p/how-

Marcus on AI · How o3 and Grok 4 Accidentally Vindicated Neurosymbolic AIBy Gary Marcus
#AI#NeuralNetworks#DeepLearning
FIZ ISE Research Group

Our team member Sven Hertling is presenting "Towards Large Language Models Interacting with Knowledge Graphs Via Function Calling" at the Knowledge Base Construction from Pre-Trained Language Models Workshop at #ISWC2024

paper: lm-kbc.github.io/workshop2024/
KBC-LM2024 website: lm-kbc.github.io/workshop2024/

#llms #KBC #knowledgegraphs #semanticweb #symbolicAI #neurosymbolicAI @fiz_karlsruhe @unimannheim #iswc

FIZ ISE Research Group

Our colleague @sourisnumerique at her presentation of "One Pattern to Express Them All? Towards Generalised Patterns for Ontology Design in the Digital Humanities" at the #WOP2024 workshop on Ontology Design Patterns.

paper: zenodo.org/records/14063917
presentation: zenodo.org/records/14063901

@fiz_karlsruhe @lysander07 #dh #ontologies #ontologydesign #odp #AI #symbolicAI #ISWC2024 #ISWC #semanticweb @NFDI4Memory @nfdi4culture

Harald Sack

Knowledge Representation and Symbolic Reasoning as another AI discipline are much older than machine learning. Already in the 4th century BCE greek philosopher Aristotle suggested ten universal categories under which to place every object of human apprehension.

Studtmann, P.. Aristotle's Categories. In Zalta, E.N. (ed.). Stanford Encyclopedia of Philosophy. plato.stanford.edu/entries/ari

#HistoryOfAI #AI #ISE2024 #knowledgerepresentation #symbolicAI #philosophy @sourisnumerique @enorouzi @fizise

Harald Sack

One benefit of RDF(S) in comparison with traditional data schema lies in its ability to allow logical inference of new knowledge. Admittedly, RDFS doesn't allow for much semantic expressivity, but we have class and property hierarchies as well as domain and range restrictions, which enable us to entail new RDF triples.

#ISE2024 lecture 07, slides: drive.google.com/file/d/1gJ3RD

#RDF #knowledgegraphs #semanticweb #inference #symbolicAI #AI #AIart @sourisnumerique @enorouzi @shufan @fizise

Chris J. Karr

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.

arxiv.org/abs/2308.04445

arXiv.orgGetting from Generative AI to Trustworthy AI: What LLMs might learn from CycGenerative AI, the most popular current approach to AI, consists of large language models (LLMs) that are trained to produce outputs that are plausible, but not necessarily correct. Although their abilities are often uncanny, they are lacking in aspects of reasoning, leading LLMs to be less than completely trustworthy. Furthermore, their results tend to be both unpredictable and uninterpretable. We lay out 16 desiderata for future AI, and discuss an alternative approach to AI which could theoretically address many of the limitations associated with current approaches: AI educated with curated pieces of explicit knowledge and rules of thumb, enabling an inference engine to automatically deduce the logical entailments of all that knowledge. Even long arguments produced this way can be both trustworthy and interpretable, since the full step-by-step line of reasoning is always available, and for each step the provenance of the knowledge used can be documented and audited. There is however a catch: if the logical language is expressive enough to fully represent the meaning of anything we can say in English, then the inference engine runs much too slowly. That's why symbolic AI systems typically settle for some fast but much less expressive logic, such as knowledge graphs. We describe how one AI system, Cyc, has developed ways to overcome that tradeoff and is able to reason in higher order logic in real time. We suggest that any trustworthy general AI will need to hybridize the approaches, the LLM approach and more formal approach, and lay out a path to realizing that dream.
#Cyc#DougLenat#SymbolicAI
*
Gonzalo Polavieja

#Introduction

I study how collectives of agents (animals, neurons, mathematical structures) can solve problems.

We also develop AI approaches based on Model Theory and Universal Algebra. They do not use optimization and are very transparent to mathematical analysis.

#maths #mathematics #logic #algebra #CategoryTheory #types #ComputerScience

#Neuroscience, #CollectiveBehavior #CollectiveIntelligence

#MachineLearning #ComputerVision
#SymbolicAI
#CognitiveSystems
#AI #ArtificialIntelligence

Gonzalo Polavieja

#introduction

I think about how a collective of agents (animals, neurons, mathematical structures) can solve problems. Additionally, I am interested in what it means to produce a good model and understanding of something.

I am excited to be here to learn and discuss.
#Neuroscience, #CollectiveBehavior #CollectiveIntelligence
#ComputerScience
#maths #mathematics #logic #algebra #CategoryTheory #types
#machinelearning #computervision
#symbolicAI
#CognitiveSystems
#AI #ArtificialIntelligence

TrendingLive feeds
About