A form of logic thatdeals withapproximate ratherthan exact reasoning,allowing for degreesof truth rather thanbinary valuesFuzzyLogicA computationalmodel that consistsof layers ofinterconnectednodes that processand learn from dataNeuralNetwork(NN)A softwareapplicationdesigned tostimulatehumanconversationChatbotIntelligencedemonstratedby machinesor computersystemsArtificialIntelligence(AI)The process ofsorting throughlarge data sets toidentify patternsthat can improvemodels or solveproblemsDataminingA type of machinelearning where anAI system learnsfrom unlabeled datawithout feedbackUnsupervisedlearningAI systemsthat generateoutput inresponse topromptsGenerativeAIAn AI system thatemulates thedecision-makingability of a humanexpert in a specificdomainExpertsystemThe ability of anAI system toidentify andclassify objectsin an imageImagerecognitionThe collectivebehavior ofdecentralized, self-organized systems,such as a flock ofbirds or a colony ofantsSwarmintelligenceAn extension of thecurrent web thataims to make thedata moreunderstandable andaccessible formachinesSemanticwebA neural nettrained on largeamounts of textto imitate humanlanguageLargeLanguageModel(LLM)A test todeterminewhether amachine canexhibit human-like intelligenceTuringTestThe hypotheticalpoint in time whenartificialintelligencesurpasses humanintelligenceSingularityThe branch oftechnology that dealswith the design,construction,operation, andapplication of robotsRoboticsA finite sequence ofinstructionsfollowed by acomputer system toperform a task orsolve a problemAlgorithmA type of machinelearning where anAI system learnsfrom its ownactions andrewardsReinforcementLearning (RL)Very largedatasets thatnormal data-processingsoftware can’thandleBigdataThe study of howto extract insightsand knowledgefrom data usingvarious methodsand toolsDatascienceA form ofmachinelearning basedon neuralnetworksDeepLearning(DL)The branch of AIthat deals with theinteractionbetweencomputers andhuman languagesNaturallanguageprocessing(NLP)The study ofhow AI acquiresknowledge fromtraining dataMachineLearning(MS)The output of anAI system thatestimates thelikelihood of anevent or outcomebased on dataPredictionA type of machinelearning where anAI system learnsfrom labeled dataand feedbackSupervisedlearningAn interdisciplinaryfield of science andtechnology thatfocuses on howcomputers can gainunderstanding fromimages and videosComputervisionA form of logic thatdeals withapproximate ratherthan exact reasoning,allowing for degreesof truth rather thanbinary valuesFuzzyLogicA computationalmodel that consistsof layers ofinterconnectednodes that processand learn from dataNeuralNetwork(NN)A softwareapplicationdesigned tostimulatehumanconversationChatbotIntelligencedemonstratedby machinesor computersystemsArtificialIntelligence(AI)The process ofsorting throughlarge data sets toidentify patternsthat can improvemodels or solveproblemsDataminingA type of machinelearning where anAI system learnsfrom unlabeled datawithout feedbackUnsupervisedlearningAI systemsthat generateoutput inresponse topromptsGenerativeAIAn AI system thatemulates thedecision-makingability of a humanexpert in a specificdomainExpertsystemThe ability of anAI system toidentify andclassify objectsin an imageImagerecognitionThe collectivebehavior ofdecentralized, self-organized systems,such as a flock ofbirds or a colony ofantsSwarmintelligenceAn extension of thecurrent web thataims to make thedata moreunderstandable andaccessible formachinesSemanticwebA neural nettrained on largeamounts of textto imitate humanlanguageLargeLanguageModel(LLM)A test todeterminewhether amachine canexhibit human-like intelligenceTuringTestThe hypotheticalpoint in time whenartificialintelligencesurpasses humanintelligenceSingularityThe branch oftechnology that dealswith the design,construction,operation, andapplication of robotsRoboticsA finite sequence ofinstructionsfollowed by acomputer system toperform a task orsolve a problemAlgorithmA type of machinelearning where anAI system learnsfrom its ownactions andrewardsReinforcementLearning (RL)Very largedatasets thatnormal data-processingsoftware can’thandleBigdataThe study of howto extract insightsand knowledgefrom data usingvarious methodsand toolsDatascienceA form ofmachinelearning basedon neuralnetworksDeepLearning(DL)The branch of AIthat deals with theinteractionbetweencomputers andhuman languagesNaturallanguageprocessing(NLP)The study ofhow AI acquiresknowledge fromtraining dataMachineLearning(MS)The output of anAI system thatestimates thelikelihood of anevent or outcomebased on dataPredictionA type of machinelearning where anAI system learnsfrom labeled dataand feedbackSupervisedlearningAn interdisciplinaryfield of science andtechnology thatfocuses on howcomputers can gainunderstanding fromimages and videosComputervision

AI BASICS - Call List

(Print) Use this randomly generated list as your call list when playing the game. 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.


1
G G
2
O O
3
N N
4
B B
5
B B
6
G G
7
G G
8
O O
9
O O
10
I I
11
G G
12
B B
13
O O
14
B B
15
N N
16
I I
17
I I
18
N N
19
I I
20
N N
21
G G
22
I I
23
B B
24
N N
25
O O
  1. G-Fuzzy Logic
    G-A form of logic that deals with approximate rather than exact reasoning, allowing for degrees of truth rather than binary values
  2. O-Neural Network (NN)
    O-A computational model that consists of layers of interconnected nodes that process and learn from data
  3. N-Chatbot
    N-A software application designed to stimulate human conversation
  4. B-Artificial Intelligence (AI)
    B-Intelligence demonstrated by machines or computer systems
  5. B-Data mining
    B-The process of sorting through large data sets to identify patterns that can improve models or solve problems
  6. G-Unsupervised learning
    G-A type of machine learning where an AI system learns from unlabeled data without feedback
  7. G-Generative AI
    G-AI systems that generate output in response to prompts
  8. O-Expert system
    O-An AI system that emulates the decision-making ability of a human expert in a specific domain
  9. O-Image recognition
    O-The ability of an AI system to identify and classify objects in an image
  10. I-Swarm intelligence
    I-The collective behavior of decentralized, self-organized systems, such as a flock of birds or a colony of ants
  11. G-Semantic web
    G-An extension of the current web that aims to make the data more understandable and accessible for machines
  12. B-Large Language Model (LLM)
    B-A neural net trained on large amounts of text to imitate human language
  13. O-Turing Test
    O-A test to determine whether a machine can exhibit human-like intelligence
  14. B-Singularity
    B-The hypothetical point in time when artificial intelligence surpasses human intelligence
  15. N-Robotics
    N-The branch of technology that deals with the design, construction, operation, and application of robots
  16. I-Algorithm
    I-A finite sequence of instructions followed by a computer system to perform a task or solve a problem
  17. I-Reinforcement Learning (RL)
    I-A type of machine learning where an AI system learns from its own actions and rewards
  18. N-Big data
    N-Very large datasets that normal data-processing software can’t handle
  19. I-Data science
    I-The study of how to extract insights and knowledge from data using various methods and tools
  20. N-Deep Learning (DL)
    N-A form of machine learning based on neural networks
  21. G-Natural language processing (NLP)
    G-The branch of AI that deals with the interaction between computers and human languages
  22. I-Machine Learning (MS)
    I-The study of how AI acquires knowledge from training data
  23. B-Prediction
    B-The output of an AI system that estimates the likelihood of an event or outcome based on data
  24. N-Supervised learning
    N-A type of machine learning where an AI system learns from labeled data and feedback
  25. O-Computer vision
    O-An interdisciplinary field of science and technology that focuses on how computers can gain understanding from images and videos