Oracle Cloud Infrastructure Supercluster is a cloud service that provides ultrafast cluster networking, HPC storage, and OCI Compute bare metal instances. OCI Supercluster is ideal for training generative AI, including conversational applications and diffusion models, as it can deploy up to tens of thousands of NVIDIA GPUs per cluster for much greater scalability than similar offerings from other providers. OCI Supercluster also reduces the time needed to train AI models with simple Ethernet network architecture that provides ultrahigh performance at massive scale. Additionally, OCI Supercluster offers cost savings and access to AI subjectmatter experts56. References: OCI Supercluster and AI Infrastructure | Oracle, Oracle Delivers More Choices for AI Infrastructure and General-Purpose …
Question # 7
What is the primary goal of machine learning?
A.
Enabling computers to learn and improve from experience
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 # 8
What is "in-context learning" in the realm of large Language Models (LLMs)?
A.
Teaching a mode! through zero-shot learning
B.
Training a model on a diverse range of tasks
C.
Modifying the behavior of a pretrained LLM permanently
D.
Providing a few examples of a target task via the input prompt
In-context learning is a technique that leverages the ability of large language models to learn from a few input-output examples provided in the input prompt. By conditioning on these examples, the model can infer the task and the format of the desired output, and generate a suitable response. In-context learning does not require any additional training or fine-tuning of the model, and can be used for various tasks such as text summarization, question answering, text generation, and more45. In-context learning is also known as few-shot learning or prompt-based learning. References: [2307.12375] In-Context Learning in Large Language Models Learns Label …](https://arxiv.org/abs/2307.12375), [2307.07164] Learning to Retrieve In-Context Examples for Large Language Models] (https://arxiv.org/abs/2307.07164)
Question # 9
In machine learning, what does the term "model training" mean?
A.
Analyzing the accuracy of a trained model
B.
Establishing a relationship between Input features and output
C.
Writing code for the entire program
D.
Performing data analysis on collected and labeled data
Model training is the process of finding the optimal values for the model parameters that minimize the error between the model predictions and the actual output. This is done by using a learning algorithm that iteratively updates the parameters based on the input features and the output1. References: Oracle Cloud Infrastructure Documentation
