Explanation: The feature of OCI Language that would be most effective in helping you analyze customer sentiment from feedback written in different languages is to leverage OCI Language’s multilingual support. This feature enables the service to accurately analyze sentiment across multiple languages, enhancing your ability to gauge customer feedback effectively. When fine-tuning a Large Language Model (LLM) for a specific domain, which factor is most important to ensure the quality of the fine -tuned model?
(LLMs) in Oracle Cloud Infrastructure's AI services are: C: LLMs are pre-trained models designed to understand and generate human language, typically trained on vast amounts of text data using self -supervised learning. This foundational training allows them to perform a variety of language tasks. E: LLMs rely on Transformer architecture, where attention mechanisms allow the model to focus on specific parts of input data to handle long -range dependencies. This capability is crucial for understanding context and generating coherent responses in natural language. Which two statements accurately describe the limitations or challenges of Generative AI models, particularly large language models (LLMs)? (Select two)
and AI workloads are: A: OCI Compute Shapes for AI, which provide various configurations optimized for AI workloads. D: OCI GPU Instances, which are crucial for accelerating training and inference of deep learning models, enabling efficient processing of large datasets. You are tasked with creating a generative AI model for a company that wants to automatically generate product descriptions for an e -commerce website. The input will consist of brief product attributes like size, color, material, and category. The goal is to create coherent, detailed, and unique descriptions for each product. You are considering using a large language model (LLM) to generate these descriptions. However, the company is concerned about potential issues like the model generating inaccurate information, redundant descriptions, or overly generic content. Which strategy is the most effective to ensure the generated product descriptions are accurate, varied, and useful?
You are tasked with building an AI model on OCI to detect fraudulent transactions for an online retail company. You have access to a labeled dataset of previous transactions where each transaction is marked as either "fraudulent" or "non-fraudulent." What would be the most appropriate AI technique for building this model?
Which of the following are true about the use of regularization techniques in deep learning models? (Select two)
➢ TOTAL QUESTIONS:300 What is the key feature of Recurrent Neural Networks (RNNs)?
