The following article is based on an extract from the Second Edition of Machine Learning Engineering with Python, Packt, 2023, by Andy McMahon.
Living It Large With LLMs
At the time of writing, GPT4 has been released only a few months previously, in March 2023, by OpenAI. This model is potentially the largest machine learning model ever developed, with a reported one trillion parameters, although OpenAI refuses to confirm this number. Since then, Microsoft and Google have announced advanced chat capabilities using similarly large models in their product suites, and a raft of open-source packages and toolkits have been released that it feels like everyone is trying to understand and apply. All of these solutions leverage some of the largest neural network models ever developed, Large Language Models (LLMs). LLMs are part of an even wider class of models known as Foundation Models, which span not just text applications but video and audio as well. These models are roughly classified by the author as being too large for most organizations to consider training, or potentially even hosting, themselves, and therefore, they will usually be consumed as a third-party service. Solving this integration challenge in a safe and reliable way represents one of the main challenges in modern machine learning engineering. There is no time to lose, as new models and capabilities seem to be released every day. Let’s go!