In the world of Machine Learning (ML), Matrices are not merely arrangements of numbers; they are the foundation stones upon which complex algorithms are built. Their properties—determinant, rank, singularity, and echelon forms—are critical in shaping the efficacy of ML models. Let’s take a closer look at these properties and elucidate their significance through a case study in the automotive industry, particularly in the application of image classification for autonomous vehicles. Determinant: The Indicator of Linear Independence The determinant of a matrix serves as an indicator of linear independence among vectors. In the context of ML, a non-zero determinant is indicative […]
LLM Fine-Tuning : Through the Lens of Security
2023 has seen a big boom in the sector of AI. Large Language Models (LLMs), the words in every household these days , have emerged as both a marvel and a mystery. With their human-like text generation capabilities, LLMs are reshaping our digital landscape. But, as with any powerful tool, there is a catch. Let’s unravel the security intricacies of fine-tuning LLMs and chart a course towards a safer AI future. The Fine-Tuning Conundrum Customizing LLMs for niche applications has garnered a lot of hype . While this promises enhanced performance and bias reduction, recent findings from VentureBeat suggest a […]