Deploying an ML model is just the beginning of the journey. Like any sophisticated engine, AI models require constant vigilance to ensure they’re performing optimally, fairly, and reliably.
The rapid proliferation of Large Language Models (LLMs) has catalyzed a demand for robust frameworks capable of harnessing their power to build sophisticated applications.
As you watch a Major League Baseball game, you're witnessing a data explosion, meticulously captured and crunched in near real-time to bring you an unprecedented understanding of the game.
When faced with the choice between these two options, how do you decide which one is the right fit for your specific deep learning endeavors? This blog post aims to demystify GPUs and TPUs, diving deep into their architectures and how they handle the critical matrix calculations that underpin AI.
