AI Today Podcast: Generative AI Series: Generative AI & Large Language Models (LLMs) – How Do They Work?
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LLM Basics
Large Language Models (LLMs) are at the heart of many AI applications today, including popular tools like ChatGPT. explains that these models are not just about size but also about the vast amount of data they are trained on, which allows them to understand and generate human-like text 1. The process involves tokenization, where text is broken down into smaller units that machines can process, enabling them to predict and generate language outputs 2.
Machines don't really understand words. They still fundamentally about numbers and just try to predict what they are based on what the input words are.
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This capability makes LLMs incredibly powerful for tasks like summarization, translation, and even creative content generation.
GPT Evolution
The evolution of the GPT series marks significant milestones in AI development. outlines the journey from GPT-1, with 117 million parameters, to GPT-3, which boasts 175 billion parameters, highlighting the exponential growth in model complexity and capability 3. These advancements have been driven by massive data sets and sophisticated neural network architectures, such as the transformer model, which enables the generation of coherent and contextually relevant text 4.
GPT-3 was trained on an extremely large amount of data collected from the Internet.
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This progression underscores the increasing computational demands and the collaborative efforts, like the partnership between OpenAI and Microsoft, to push the boundaries of AI.