1z0-1122-23 Dumps - Oracle Cloud Infrastructure 2023 AI Foundations Associate
Note! Following 1z0-1122-23 Exam is Retired now. Please select the alternative replacement for your Exam Certification.
The new exam code is 1z0-1122-24
Machine learning is a branch of artificial intelligence that enables computers to learn from data and experience without being explicitly programmed. Machine learning algorithms can adapt to new data and situations and improve their performance over time2. References: Artificial Intelligence (AI) | Oracle
Question 2
How is "Prompt Engineering" different from "Fine-tuning" in the context of Large Language Models (LLMs)?
Options:
A.
Customizes the model architecture
B.
Trains a model from scratch
C.
Guides the model's response using predefined prompts
D.
Involves post-processing model outputs and optimizinghyper parameters
Answer:
C
Explanation:
Explanation:
Prompt engineering is the art of designing natural language instructions or queries that can elicit the desired response from a large language model. Prompt engineering does not modify the model parameters or architecture, but rather relies on the model’s existing knowledge and capabilities. Prompt engineering can be used to perform various tasks such as text generation, sentiment analysis, and code completion, by providing the model with the appropriate context, format, and constraints67. Prompt engineering is also known as zero-shot learning or query-based learning. References: [2211.01910] Large Language Models Are Human-Level Prompt Engineers] A developer’s guide to prompt engineering and LLMs - The GitHub Blog
Question 3
How can Oracle Cloud Infrastructure Document Understanding service be applied in business processes?
Options:
A.
By automating data extraction from documents
B.
By generating lifelike speech from text
C.
By transcribing spoken language
D.
By analyzing text sentiment
Answer:
A
Explanation:
Explanation:
Oracle Cloud Infrastructure Document Understanding service is a cloud-based AI service for automating data extraction from documents. It can process various types of documents, such as invoices, receipts, contracts, forms, etc., and extract key information fields from them using optical character recognition (OCR) and natural language understanding (NLU) techniques. It can also provide confidence scores for each extracted field and enable human verification if needed. By using this service, businesses can reduce manual efforts, improve accuracy, and accelerate workflows that involve document processing. Some of the use cases for Oracle Cloud Infrastructure Document Understanding service are:
Invoice Processing: Extract invoice details, such as invoice number, date, amount, vendor name, etc., and validate them against purchase orders or contracts.
Contract Analysis: Extract contract terms, such as parties, duration, clauses, obligations, etc., and compare them with standard templates or policies.
Form Processing: Extract form fields, such as name, address, phone number, email, etc., and populate them into databases or applications. References: : [Document Understanding Overview - Oracle], [AI Document Understanding at Scale | Oracle]