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What is LLM? Understanding the Large Language Models
Understanding the Power and Potential of Large Language Models (LLMs)
In the last few years, the term LLM has gained a lot of popularity in artificial intelligence. LLM stands for Large Language Model, an AI model designed to understand, generate, and process human language. These models are trained on vast volumes of textual data using deep learning techniques. They can generate texts, summarize, and respond to questions, among other language-related tasks.
But what makes a model “Large” and why are they important? Let’s understand the concept of LLMs and their significance in AI and machine learning in detail.
What Makes a Model “Large”?
A critical characteristic of LLM is the size, which, generally, refers to the number of parameters the model uses to predict. These parameters are adjusted during training to make the model better able to understand and produce language. In essence, the more parameters a model has, the better it is at understanding complex patterns in data.
For instance, GPT-3, an LLM that is popularly known and created by OpenAI, has 175 billion parameters. Models such as GPT-4 even have more of these. Therefore, it is also pretty efficient in complex tasks like understanding middle-level languages and developing responses that are not only consistent but also contextually relevant.
How Do LLMs Work?
LLMs are the core of the Transformer neural network architecture, released in 2017. They are more powerful in dealing with sequences of data, e.g., by joining the content to the relationships among the words even if the position in the sequence is different. This process is named self-attention, and it allows the model to capture the context and make use of the data with the help of attention neurons.
In order to produce the LLMs, vast arrays of text (like books, articles, and websites) are required, and it is in this manner that the model succeeds in predicting the next word in a sequence, which in turn yields the model sentence and the whole article.
