UiPath-AAAv1 무료 덤프문제 온라인 액세스

What is the primary role of guardrails in tools?

• A.Guardrails are designed to apply only after tool execution, without influencing pre-execution conditions.
• B.Guardrails only validate tool inputs during development and do not address unpredictable behaviors at runtime.
• C.Guardrails control unexpected behaviors within tool calls deterministically, allowing developers to configure conditions for human intervention and escalations.
• D.Guardrails are used exclusively to automate all tool corrections without the possibility of triggering human intervention.

When exploring agentic automation discovery, which dimension ensures the solution aligns with the responsibilities and challenges of the individuals involved?

• A.Mapping systems, applications, and tools without understanding how they interact with human roles.
• B.Focusing solely on task dependencies while neglecting the daily pain points of individuals executing these tasks.
• C.Defining the role or persona by considering the people performing the tasks and their needs, challenges, and responsibilities.
• D.Assessing structured and unstructured knowledge contexts required for the tasks but excluding the personas performing these operations.

What is one of the key benefits of providing RAG as a service to UiPath generative AI experiences?

• A.It reduces the risk of hallucination by referencing ground truth data stores.
• B.It directly increases the LLM context window size without any interaction with knowledge bases.
• C.It eliminates the need for knowledge bases by integrating all proprietary data directly into generative applications.
• D.It exclusively provides access to historical data sources without supporting real-time updates.

Why is an agent story important in the development life-cycle?

• A.A good agent story helps the developers who will build the agent to focus on the essential features that deliver value
• B.An unclear agent story helps SMEs and stakeholders understand the potential risks associated with the agent
• C.A poorly defined agent story enables developers to identify improvement opportunities
• D.A detailed agent story is only necessary when showcasing the agent's functionality to key stakeholders, rather than guiding the development process

A developer is working on fine-tuning an LLM for generating step-by-step automation guides. After providing a detailed example prompt, they notice inconsistencies in the way the LLM interprets certain technical terms. What could be the reason for this behavior?

• A.The LLM does not rely on tokenization for understanding prompts; instead, misinterpretation arises from inadequate pre-programmed definitions of technical terms.
• B.The LLM's tokenization process may have split complex technical terms into multiple tokens, causing slight variations in how the model interprets and weights their relationships within the context of the prompt.
• C.The LLM's interpretation is solely based on the frequency of terms within the training dataset, rendering technical nuances irrelevant during generation.
• D.The inconsistency is related to the token limit defined for the prompt's length, which affects the LLM's ability to complete a response rather than its understanding of technical terms.