PASS GUARANTEED QUIZ GOOGLE - GENERATIVE-AI-LEADER - GOOGLE CLOUD CERTIFIED - GENERATIVE AI LEADER EXAM USEFUL VALID BRAINDUMPS

Pass Guaranteed Quiz Google - Generative-AI-Leader - Google Cloud Certified - Generative AI Leader Exam Useful Valid Braindumps

Pass Guaranteed Quiz Google - Generative-AI-Leader - Google Cloud Certified - Generative AI Leader Exam Useful Valid Braindumps

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Google Cloud Certified - Generative AI Leader Exam Sample Questions (Q28-Q33):

NEW QUESTION # 28
What will Google Cloud's Agent Assist help a company achieve?

  • A. The ability to build and deploy deterministic and generative chatbot agents for automated customer support.
  • B. The infrastructure to provide an enterprise-grade contact center solution with omnichannel support, routing, and integration with CRM systems.
  • C. The ability to analyze conversational data to identify customer sentiment, common topics of discussion, and insights into agent performance and customer experience.
  • D. The ability to provide real-time assistance and recommended responses to live customer service agents during their interactions.

Answer: D

Explanation:
Google Cloud's Agent Assist is specifically designed to augment human customer service agents. It provides real-time suggestions, retrieves relevant information, and offers recommended responses to agents during live interactions, improving their efficiency and consistency.
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NEW QUESTION # 29
What is the definition of generative AI?

  • A. A type of machine learning algorithm inspired by the human brain that is made up of interconnected nodes.
  • B. A type of artificial intelligence that enables a system to autonomously learn and improve using neural networks and deep learning.4
  • C. A type of artificial intelligence that can create new content and ideas, including text, images, music, and code.
  • D. A type of predictive model that estimates a relationship by fitting a line to the observed data.

Answer: C

Explanation:
The defining characteristic of generative AI is its ability to create new, original content that resembles its training data. This includes various modalities like text, images, music, and code, rather than just classifying, predicting, or analyzing existing data.
________________________________________


NEW QUESTION # 30
An organization with a team of live customer service agents wants to improve agent efficiency and customer satisfaction during support interactions. They are looking for a tool that can provide real-time guidance to agents, suggest helpful information, and streamline the support process without fully automating customer conversations. Which component of Google's Customer Engagement Suite should they use?

  • A. Agent Assist
  • B. Conversational Agents
  • C. Google Cloud Contact Center as a Service
  • D. Conversational Insights

Answer: A

Explanation:
As previously mentioned, Agent Assist is specifically designed for real-time support to human agents, providing them with suggestions and relevant information during live customer interactions. Conversational Agents (chatbots) automate interactions, Conversational Insights analyze conversations after they occur, and Contact Center as a Service is the broader infrastructure.
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NEW QUESTION # 31
A company's large learning model (LLM) is producing hallucinations that are a result of the Knowledge cutoff. How does retrieval-augmented generation (RAG) overcome this limitation?

  • A. RAG enables the LLM to retrieve relevant and up-to-date information from knowledge sources.
  • B. RAG enhances the creative writing capabilities of the LLM to generate more engaging and informative responses.
  • C. RAG fine-tunes the LLM on specific customer query patterns to improve the speed and efficiency of response generation.
  • D. RAG uses human oversight to ensure accuracy before presenting information to the customer.

Answer: A

Explanation:
The primary purpose of RAG is to address the "knowledge cutoff" and hallucination issues of LLMs. It does this by retrieving relevant, up-to-date information from external knowledge sources (like databases or documents) at inference time and then using this retrieved information to ground the LLM's generation, ensuring factual accuracy and relevance to the specific query.
________________________________________


NEW QUESTION # 32
A development team is configuring a generative AI model for a customer-facing application and wants to ensure the generated content is appropriate and harmless. What is the primary function of the safety settings parameter in a generative AI model?

  • A. To filter out potentially harmful or inappropriate content from the model's output based on the desired level of filtering.
  • B. To determine the number of tokens the model can process at once by influencing the complexity and length of inputs and outputs.
  • C. To control the creativity and randomness of the model's output by adjusting the diversity of word choices.
  • D. To limit the maximum text length that the model generates by ensuring concise responses.

Answer: A

Explanation:
Safety settings in generative AI models are specifically designed to prevent the generation of content that could be harmful, offensive, or inappropriate. This includes filtering for categories like hate speech, sexually explicit content, self-harm, and violence, based on predefined thresholds. Options A, B, and D refer to other parameters like max_output_tokens or temperature, which control output length, input/output processing, and creativity, respectively, not safety.
________________________________________


NEW QUESTION # 33
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