How is "Prompt Engineering" different from "Fine-tuning" in the context of Large Language Models (LLMs)?
What is "in-context learning" in the realm of large Language Models (LLMs)?
You are the lead developer of a Deep Learning research team, and you are tasked with improving the training speed of your deep neural networks. To accelerate the training process, you decide to leverage specialized hardware.
Which hardware component is commonly used in Deep Learning to accelerate model training?
What is the primary goal of machine learning?