Summary
This video explains the differences between machine learning model training and inference. During the training phase, models learn from a dataset to optimize parameters for making predictions. In contrast, the inference phase uses the trained model to make predictions on new unseen data with lower resource requirements. The video also touches on how Large Language Models (LLMs) generate synthetic content by applying patterns learned during training, showcasing their diverse applications.
ML Model Training vs Inference
Explanation of the differences between ML model training and inference, including the phases, resource requirements, and use cases.
Training Phase
Details about the training phase where machine learning models learn from a dataset to optimize parameters for making predictions.
Inference Phase
Description of the inference phase where the trained model is used to make predictions on new unseen data with lower resource requirements.
LLM Inferences
Discussion on how Large Language Models (LLMs) generate synthetic content using patterns learned during training for various applications.
Get your own AI Agent Today
Thousands of businesses worldwide are using Chaindesk Generative
AI platform.
Don't get left behind - start building your
own custom AI chatbot now!