Statements (58)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Artificial_Intelligence
|
| gptkbp:bfsLayer |
6
|
| gptkbp:bfsParent |
gptkb:Creative_Destruction_Lab
|
| gptkbp:aims_to |
decision making
customer experience efficiency |
| gptkbp:applies_to |
healthcare
finance automotive retail |
| gptkbp:collaborates_with |
research institutions
technology companies |
| gptkbp:developed_by |
gptkb:High_School
CDL consumer applications |
| gptkbp:dividend_yield |
business intelligence
operational efficiency cost savings |
| gptkbp:focuses_on |
gptkb:software_framework
computer vision natural language processing |
| gptkbp:has_programs |
gptkb:education
gptkb:robot agriculture smart cities |
| https://www.w3.org/2000/01/rdf-schema#label |
CDL Artificial Intelligence
|
| gptkbp:is_part_of |
CDL's technology suite
|
| gptkbp:is_recognized_for |
gptkb:benchmark
innovation scalability |
| gptkbp:is_supported_by |
gptkb:Cloud_Computing_Service
gptkb:Io_T big data |
| gptkbp:is_used_in |
personalization
predictive analytics fraud detection automated customer service |
| gptkbp:provides |
gptkb:municipality
insights automation |
| gptkbp:requires |
expertise
computational resources data privacy measures |
| gptkbp:supports |
data visualization
real-time monitoring decision support systems |
| gptkbp:training |
large datasets
historical data real-time data |
| gptkbp:uses |
gptkb:microprocessor
data analytics deep learning |
| gptkbp:utilizes |
algorithms
simulation techniques statistical models |
| gptkbp:works_with |
gptkb:software
business analysts data scientists |