A Deep Dive into Local Language Models: Exploring Power and Privacy on Personal Machines
In the ever-evolving landscape of artificial intelligence and machine learning, language models have emerged as powerful tools capable of generating text, answering queries, and even assisting with coding tasks. One intriguing aspect of these models is the ability to run them locally, providing a unique insight into their capabilities and limitations.
The text sheds light on the experiences of individuals interacting with local language models (LLMs) and delves into the intricacies of their development and practical applications. One notable aspect highlighted is the process of developing math kernels within the CUDA framework, aiming to streamline the execution of complex mathematical operations without relying on external dependencies like cuBLAS.