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How AI does its (or our) work
Large language models (LLMs) are the powerhouse behind all generative AI (GenAI) applications, designed to process and understand language in a way that mirrors human communication. Understanding LLMs gives users a glimpse behind the magic curtain of what’s happening behind AI software.
The process begins by feeding the LLM unimaginable volumes of training data, which allow the model to recognize intricate patterns. The LLM then generates numerous predictions about what should logically follow or how it should respond to a prompt. These predictions are ranked based on the likelihood of their accuracy, and the LLM selects the highest ranked prediction as its response.
Here’s an example.
Human to AI: What’s an LLM?
AI to human:
An LLM, or large language model, is a type of artificial intelligence model that is designed to understand and generate human-like text. These models are trained on vast amounts of text data and use deep learning techniques, particularly a type of neural network architecture known as a transformer, to predict the next word in a sentence given all the previous words. Large language Models are capable of performing a wide range of language-related tasks, such as translation, summarization, question answering and conversation. They can also be fine-tuned for specific applications or industries to provide more specialized responses. The model you are currently interacting with is an example of an LLM, designed to understand your questions and provide informative and contextually relevant answers.
Due to their reliance on training data, these models are becoming increasingly adept at mimicking human behavior across various scenarios. The advantage of this is that AI models are likely to provide answers that a human might give, creating an experience for the end user that is comparable, if not superior, to human interaction. However, there’s a potential downside: without a continuous influx of fresh content and ideas, AI models may become stale and repetitive, particularly in content creation. That points to a future where human-created content is valued as a premium offering.