A. Al systems that can perform any task autonomously
B. Al systems that can think and make decisions like humans
C. Al systems that can process beyond human capabilities
D. Al systems that can perform a specific task autonomously
A. Reinforcement Learning through Human Feedback (RLHF)
B. Transfer Learning
C. Adversarial Training
D. Self-supervised Learning
A. Feedforward Neural Networks
B. Latent Space
C. Random Seed
D. Self-Attention Mechanism
A. Supervised learning is common for fine tuning and customization, while unsupervised learning is common for base model training.
B. Supervised learning uses labeled data to teach the Al system what output is expected, while unsupervised learning feeds a large corpus of raw data into the Al system, which determines the appropriate weights in its neural network.
C. Supervised learning feeds a large corpus of raw data into the Al system, while unsupervised learning uses labeled data to teach the Al system what output is expected.
D. Supervised learning is common for base model training, while unsupervised learning is common for fine tuning and customization.
A. LLMs are used to increase the size of the neural network.
B. LLMs are used to shrink the size of the neural network.
C. LLMs are used to parse image, audio, and video data.
D. LLMs receive input in human language and produce output in human language.
A. Enhancing the model's features with real-time data
B. Selecting specific features of a model to keep while removing others
C. Training a model on entirely new features
D. Transferring the learning process to a new model
