Explainability Supervised learning Chatbot Unsupervised learning reinforced learning Model Hallucination Neural Network Wizard of Oz Prototyping bias transparent data WatsonX Supervised learning Model Drift Human in the Loop Large Language Models Trustworthy AI AI Human in the Loop Foundation Models Machine Learning Chatbot Wizard of Oz Prototyping Foundation Models Fairness NLP Value Alignment AI data collection sampling Robustness deep learning AI Ethics Model Drift Training Data Large Language Models Machine Learning WatsonX Trustworthy AI Fairness Generative AI reinforced learning Unsupervised learning Neural Network Generative AI Value Alignment Robustness Model Hallucination Training Data data collection sampling Explainability AI Ethics bias transparent data Explainability Supervised learning Chatbot Unsupervised learning reinforced learning Model Hallucination Neural Network Wizard of Oz Prototyping bias transparent data WatsonX Supervised learning Model Drift Human in the Loop Large Language Models Trustworthy AI AI Human in the Loop Foundation Models Machine Learning Chatbot Wizard of Oz Prototyping Foundation Models Fairness NLP Value Alignment AI data collection sampling Robustness deep learning AI Ethics Model Drift Training Data Large Language Models Machine Learning WatsonX Trustworthy AI Fairness Generative AI reinforced learning Unsupervised learning Neural Network Generative AI Value Alignment Robustness Model Hallucination Training Data data collection sampling Explainability AI Ethics bias transparent data
(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.
Explainability
Supervised learning
Chatbot
Unsupervised learning
reinforced learning
Model Hallucination
Neural Network
Wizard of Oz Prototyping
bias transparent data
WatsonX
Supervised learning
Model Drift
Human in the Loop
Large Language Models
Trustworthy AI
AI
Human in the Loop
Foundation Models
Machine Learning
Chatbot
Wizard of Oz Prototyping
Foundation Models
Fairness
NLP
Value Alignment
AI
data collection sampling
Robustness
deep learning
AI Ethics
Model Drift
Training Data
Large Language Models
Machine Learning
WatsonX
Trustworthy AI
Fairness
Generative AI
reinforced learning
Unsupervised learning
Neural Network
Generative AI
Value Alignment
Robustness
Model Hallucination
Training Data
data collection sampling
Explainability
AI Ethics
bias transparent data