A graphics processing unit (GPU) is a specialized hardware component that can perform parallel computations on large amounts of data. GPUs are widely used in deep learning to accelerate the training of deep neural networks, as they can execute many matrix operations and tensor operations simultaneously. GPUs can significantly reduce the training time and improve the performance of deep learning models compared to using CPUs alone678. Reference: Hardware Recommendations for Machine Learning / AI, New hardware offers faster computation for artificial intelligence …, The Best Hardware for Machine Learning - ReHack, Hardware for Deep Learning Inference: How to Choose the Best One for … What is the advantage of using Oracle Cloud Infrastructure Supercluster for AI workloads?
This instance is ideal for training large language models, computer vision models, and other complex AI tasks. Reference: Accelerated Computing and Oracle Cloud Infrastructure (OCI) - NVIDIA, Oracle Cloud Infrastructure Offers New NVIDIA GPU -Accelerated Compute …, GPU, Virtual Machines and Bare Metal | Oracle What is "in-context learning" in the realm of large Language Models (LLMs)?
What is the purpose of fine-tuning Large Language Models?
Which Deep Learning model is well-suited for processing sequential data, such as sentences?
unstructured text Reference: : Language Overview - Oracle, AI Text Analysis at Scale | Oracle How can Oracle Cloud Infrastructure Document Understanding service be applied in business processes?
➢ TOTAL QUESTIONS:300 What is the key feature of Recurrent Neural Networks (RNNs)?
