The rise of Big Data I want to take you back to 2012 . In those early years, our focus was big data, and everyone else was looking at the cloud. We were pioneering, but in a world that was still beginning to understand the value of data.
Remember J.A.R.V.I.S. from Iron Man? That intelligent assistant that seemed to have a solution for everything? While we’re not quite there yet, the rapid evolution of Large Language Models (LLMs) like GPT-4, Claude, and Gemini is bringing us closer than ever. Today’s LLMs are impressive. They can generate content, translate languages, and even write code. But let’s be real — they’re still pretty much glorified text processors.
Over the past few months, there has been a surge of interest in large language models (LLMs). These models, which use artificial intelligence to generate human-like language, have captured public interest like never before, thanks mainly to the release of OpenAI’s ChatGPT. This explosion of public interest has meant that other companies and groups have followed suit, either by releasing base models like Meta AI’s LLaMA or instruction tuning previously released base models like Databricks’ Dolly or BAIR’s Koala.