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CAIC試験問題はすべて、99％〜100％の高い合格率を持ち、有効です。 CAIC学習ガイドの非周期性を修正します。購入したものが最新かつ高品質のCAIC準備資料であることをご安心ください。 CAIC実践準備はお金に見合う価値があることを保証します。すべてのユーザーはCAIC試験ガイドの恩恵を受けます。試験に不合格になった場合、すぐに全額のダンプを返金します。余分なペニーはすべてその価値に値します。 CAICテストの質問が最良の選択です。
質問 # 37
Which of the CORRECT cognitive modeling is used in AI applications?
正解：E
解説：
The correct answer is E. All of the above because deep learning, expert systems, natural language processing, and robotics are all connected with AI applications that support or model intelligent behavior. Cognitive modeling in AI is concerned with building systems that can represent, simulate, or support human-like capabilities such as learning, reasoning, decision-making, perception, language understanding, and action.
Deep learning is used to recognize patterns from large amounts of data and is common in speech recognition, image analysis, recommendation systems, and generative AI. Expert systems use knowledge bases and rules to support decision-making in specialized domains. Natural language processing helps AI systems understand, interpret, generate, and respond to human language. Robotics applies AI to physical systems so machines can sense, plan, move, and perform tasks in real-world environments.
Since all the listed options are valid AI application areas related to intelligent and cognitive capabilities, the correct answer is E. All of the above .
質問 # 38
What is a prompt?
正解：D
解説：
The correct answer is D. a and b only because a prompt is the input provided by a user to a generative AI model. In natural language systems such as ChatGPT and other language models, the prompt is usually written as text in natural language. It may be a question, instruction, command, description, context, example, or task requirement that guides the model toward producing a response.
Statement A is correct because prompts are the user-provided input that generative models use to produce outputs. Statement B is also correct because, for ChatGPT and similar models, prompts commonly appear as natural language text. Statement C is not fully correct because prompts are an important way to guide model output, but they are not the only possible control mechanism. Outputs can also be influenced by system instructions, model settings, retrieval context, fine-tuning, guardrails, and application design. Therefore, the best answer is D. a and b only .
質問 # 39
Which of the following is a CORRECT statement for Fine-tuning?
正解：E
解説：
The correct answer is E. a, b and c only because all three statements accurately describe fine-tuning. Fine- tuning is a machine learning and AI technique where a model that has already been trained on a large dataset is further trained or adapted for a more specific task, domain, or use case. This is common in natural language processing, generative AI, computer vision, and business AI applications.
Statement A is correct because fine-tuning adapts a pre-trained model to a new task. Statement B is also correct because during fine-tuning, some or all model parameters may be updated based on task-specific data.
Statement C is correct because the main advantage of fine-tuning is that it uses the general knowledge already learned by the pre-trained model instead of building a new model from the beginning. This saves time, data, compute resources, and often improves performance on specialized tasks. Therefore, the best answer is E .
質問 # 40
An AI agent learns to play a game by taking actions, receiving rewards for good moves, and penalties for poor moves. Over time, it improves its strategy to maximize total reward. This is an example of ______.
正解：B
解説：
Reinforcement learning is the correct answer because the AI agent learns by interacting with an environment and improving its behavior based on rewards and penalties. The goal of reinforcement learning is to learn a policy or strategy that maximizes cumulative reward over time. This differs from supervised learning, where the model learns from labeled input-output examples. It also differs from unsupervised learning, where the model searches for hidden patterns without labels or rewards. Semi-supervised learning is incorrect because the scenario does not involve a mix of labeled and unlabeled data. Regression learning is also incorrect because regression predicts continuous numerical values, while this example focuses on action selection and reward optimization. Therefore, the correct answer is C. reinforcement learning .
質問 # 41
Which of the following is MLOps?
正解：E
解説：
The correct answer is E. a, b and c only because MLOps includes workflow automation, continuous integration, and continuous deployment as important practices for managing the machine learning lifecycle.
MLOps, or Machine Learning Operations, applies DevOps-style principles to machine learning systems so models can be developed, tested, deployed, monitored, and maintained in a reliable and repeatable way.
Workflow automation is part of MLOps because machine learning pipelines often include data ingestion, data validation, feature engineering, model training, model evaluation, deployment, and monitoring. Continuous integration is also included because ML code, data pipelines, configuration files, and model components need regular testing and validation when changes are made. Continuous deployment is another key part because approved models should be deployed efficiently into production environments with version control, rollback options, and monitoring.
Since all three options describe important MLOps capabilities, the best answer is E. a, b and c only .
質問 # 42
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