Properties (50)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:physicist
|
| gptkbp:addresses |
Data scarcity issues
Generalization problems |
| gptkbp:aimsTo |
Data analysis
Knowledge Representation Decision making AI interpretability AI reasoning capabilities |
| gptkbp:associated_with |
Explainable AI
|
| gptkbp:develops |
Attention from industry
Popularity in research |
| gptkbp:facilitates |
Human-AI collaboration
|
| gptkbp:fieldOfStudy |
Machine Learning
|
| gptkbp:has |
Bridge between different AI paradigms
|
| gptkbp:has_a_focus_on |
AI ethics discussions
AI policy making |
| gptkbp:hasPrograms |
Education
Finance Healthcare |
| https://www.w3.org/2000/01/rdf-schema#label |
Neurosymbolic AI
|
| gptkbp:influenced |
Cognitive Science
Neuroscience Philosophy of Mind |
| gptkbp:is_a_subject_of |
Conferences
Research papers Workshops |
| gptkbp:is_characterized_by |
Hybrid approaches
|
| gptkbp:is_expected_to |
Shape_the_future_of_AI
|
| gptkbp:is_part_of |
AI research community
AI development trends |
| gptkbp:is_studied_in |
AI researchers
|
| gptkbp:is_supported_by |
Government funding
Private investment |
| gptkbp:is_used_in |
Natural Language Processing
Robotics Ontologies Knowledge graphs Computer_Vision |
| gptkbp:isUsedFor |
Neural Networks
Symbolic Reasoning |
| gptkbp:leads |
More robust AI systems
|
| gptkbp:produces |
Academic institutions
Tech companies |
| gptkbp:related_to |
Deep Learning
Logic_Programming |
| gptkbp:relatedTo |
Pure Symbolic AI
Pure_Neural_Networks |
| gptkbp:resultedIn |
Better performance on complex tasks
|
| gptkbp:suitableFor |
Promising research direction
|
| gptkbp:was_a_response_to |
Limitations_of_traditional_AI
|