Home» Online Test » Technology » Artificial Intelligence (AI) Online Test 0% Sorry, time's up. To complete the online test, please restart it. Created by Vikash chaudhary This 'Artificial Intelligence (AI) Online Test' covers questions across all the topics related to Artificial Intelligence like Robotics, LLM, GPT, NLP, IoT, etc Get fresh, new questions in each attempt. Total Questions: 30 Time Allotted: 30 minutes Passing Score: 50% Randomization: Yes Certificate: Yes Do not refresh the page! 👍 All the best! 1 / 30 1. Which Artificial Intelligence application in algorithmic trading focuses on executing trades at high speeds and frequencies to capitalize on small price discrepancies? a) Scalping b) Arbitrage c) Market making d) Momentum trading 2 / 30 2. Which AI application involves using algorithms to analyze financial markets, data, and trends to make trading decisions and optimize investment strategies? a) Algorithmic Trading b) High-Frequency Trading (HFT) c) Financial Forecasting d) Quantitative Analysis 3 / 30 3. What challenge arises from the potential for Artificial Intelligence systems to generate outputs or recommendations that are difficult for humans to understand or trust? a) Lack of interpretability b) Lack of scalability c) Lack of robustness d) Ethical dilemmas 4 / 30 4. Which Python library provides an intuitive and flexible interface for deep learning research and development? a) TensorFlow b) PyTorch c) Keras d) Scikit-learn 5 / 30 5. What is the primary advantage of using Graphics Processing Units (GPUs) for deep learning tasks? a) Lower power consumption b) Lower cost c) Higher parallel processing capabilities d) Higher clock speeds 6 / 30 6. Which Artificial Intelligence technique is commonly used in self-driving cars to estimate the vehicle's position and orientation relative to its surroundings? a) Global Positioning System (GPS) b) Simultaneous Localization and Mapping (SLAM) c) Kalman Filters d) Markov Localization 7 / 30 7. Which component is responsible for rendering graphics and accelerating parallel processing tasks in a computer system? a) Central Processing Unit (CPU) b) Graphics Processing Unit (GPU) c) Random Access Memory (RAM) d) Solid-State Drive (SSD) 8 / 30 8. In personalized medicine, which Artificial Intelligence application focuses on identifying patient subgroups with similar characteristics to optimize treatment strategies? a) Disease classification b) Treatment planning c) Risk prediction d) Clustering analysis 9 / 30 9. How does AI assistance contribute to workforce productivity? a) By replacing human workers with autonomous AI systems b) By augmenting human skills and abilities with AI assistance c) By limiting access to AI technologies to a select group of individuals d) By prioritizing AI autonomy and decision-making over human input 10 / 30 10. Which Artificial Intelligence technique is commonly used in fraud detection to group similar transactions together based on their characteristics and detect outliers? a) K-nearest neighbors (KNN) b) Hierarchical clustering c) DBSCAN d) Local Outlier Factor (LOF) 11 / 30 11. What is one of the benefits of using GANs in generating synthetic data? a) Increased reliance on labeled training data b) Limited diversity in the generated data samples c) Ability to capture complex data distributions d) Reduced computational complexity in training 12 / 30 12. Which object detection algorithm combines region proposal generation with object classification in a single end-to-end network? a) YOLO (You Only Look Once) b) SSD (Single Shot MultiBox Detector) c) R-CNN (Region-based Convolutional Neural Network) d) Faster R-CNN (Faster Region-based Convolutional Neural Network) 13 / 30 13. Which Artificial Intelligence application in fraud detection focuses on verifying the identity of individuals through biometric data or authentication mechanisms? a) Identity verification b) User profiling c) Behavioral analytics d) Access control 14 / 30 14. Which Artificial Intelligence technique is commonly used in medical imaging diagnosis to assist radiologists in interpreting images and detecting abnormalities? a) Convolutional Neural Networks (CNNs) b) Recurrent Neural Networks (RNNs) c) Support Vector Machines (SVMs) d) Decision Trees 15 / 30 15. Which type of processing unit is more suitable for general-purpose computing tasks, including data preprocessing and postprocessing? a) Central Processing Unit (CPU) b) Graphics Processing Unit (GPU) c) Field-Programmable Gate Array (FPGA) d) Application-Specific Integrated Circuit (ASIC) 16 / 30 16. Which AI-based medical imaging application focuses on predicting the likelihood of certain diseases or conditions based on imaging findings and patient data? a) Computer-aided detection (CAD) b) Disease classification c) Prognostication modeling d) Radiomics analysis 17 / 30 17. Which programming language is often used for developing deep learning models with the PyTorch framework? a) Python b) Java c) C++ d) JavaScript 18 / 30 18. What does GAN stand for in the context of Generative AI? a) Global Adversarial Network b) Generative Adversarial Network c) Gradient Activation Network d) Genetic Algorithm Network 19 / 30 19. Which programming language is commonly used for numerical computing and data analysis in scientific research? a) Python b) Java c) C++ d) MATLAB 20 / 30 20. Which programming language is commonly associated with the Keras library? a) Python b) Java c) C++ d) R 21 / 30 21. What is the objective of the discriminator in a GAN? a) To generate synthetic data samples b) To learn the feature representations of the data c) To distinguish between real and fake data d) To optimize the generator's performance 22 / 30 22. What is the primary purpose of using R alongside Python in GAN development? a) Data preprocessing b) Model training c) Visualization d) Performance optimization 23 / 30 23. Which evaluation metric is commonly used to measure the accuracy of semantic segmentation models? a) Precision and Recall b) Mean Absolute Error (MAE) c) Intersection over Union (IoU) d) F1 Score 24 / 30 24. In fraud detection, which AI-based approach focuses on creating models to distinguish between genuine and fraudulent transactions? a) Anomaly detection b) Supervised learning c) Unsupervised learning d) Reinforcement learning 25 / 30 25. Which programming language is commonly used for developing GANs with the TensorFlow framework? a) Python b) Java c) C++ d) JavaScript 26 / 30 26. What challenge arises from the potential for AI systems to reinforce or perpetuate existing social inequalities or biases present in the training data? a) Lack of interpretability b) Lack of scalability c) Lack of robustness d) Bias amplification 27 / 30 27. What is one advantage of using MXNet for deep learning development? a) Limited support for distributed computing b) Compatibility with JavaScript c) Static computation graphs d) High-performance execution and scalability 28 / 30 28. How can organizations leverage AI to enhance human capabilities effectively? a) By limiting human involvement and control in AI-driven processes b) By fostering a culture of openness, trust, and collaboration between humans and AI c) By prioritizing AI autonomy and decision-making over human input d) By replacing human workers with autonomous AI systems 29 / 30 29. Which evaluation metric is commonly used to measure the accuracy of instance segmentation models? a) Precision and Recall b) Intersection over Union (IoU) c) Mean Average Precision (mAP) d) F1 Score 30 / 30 30. Which type of processing unit is commonly used for inference tasks in deep learning applications? a) Central Processing Unit (CPU) b) Graphics Processing Unit (GPU) c) Field-Programmable Gate Array (FPGA) d) Application-Specific Integrated Circuit (ASIC) Please provide accurate information so we can send your Achievement Certificate by mail. NameEmailPhone Number Your score is Share your achievement! 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