Large Language Models (LLMs)

28.02.2024

Large Language Models (LLMs) , Daily Current Affairs , RACE IAS : Best IAS Coaching in Lucknow 

 Why in the news?

The ability of Generative AI models to “converse” with humans is due to something known as the Large Language Model, or LLM.

About Large Language Models (LLMs):

• A large language model (LLM) is a type of artificial intelligence (AI) program that can recognize and generate text, among other tasks.
• LLMs are trained on huge sets of data—hence the name "large."
• LLMs are built on machine learning: specifically, a type of neural network called a transformer model.
• In simpler terms, an LLM is a computer program that has been fed enough examples to be able to recognize and interpret human language or other types of complex data.
• Many LLMs are trained on data that has been gathered from the Internet—thousands or millions of gigabytes' worth of text.
• However, the quality of the samples impacts how well LLMs will learn natural language, so LLM's programmers may use a more curated data set.
• LLMs use a type of machine learning called deep learning in order to understand how characters, words, and sentences function together.
• Deep learning involves the probabilistic analysis of unstructured data, which eventually enables the deep learning model to recognize distinctions between pieces of content without human intervention.
• LLMs are then further trained via tuning: they are fine-tuned or prompt-tuned to the particular task that the programmer wants them to do, such as interpreting questions and generating responses, or translating text from one language to another.

Types of LLMs

There are various ways to categorize LLMS.

•  On the basis of architecture, there are three types — autoregressive, transformer-based, and encoder-decoder.

○ GPT-3 is an example of an autoregressive model as they predict the next word in a sequence based on previous words.

○Similarly, LaMDA or Gemini (formerly Bard) are transformer-based as they use a specific type of neural network architecture for language processing.

• Based on training data, there are three types of LLMs — pre trained and fine-tuned, multilingual or models that can understand and generate text in multiple languages, and domain-specific or models that are trained on data related to specific domains such as legal, finance or healthcare.

• They can also be categorized as open-source and closed-source based on availability as some are freely available while some are proprietary.

○ LLaMA2, BlOOM, Google BERT, Falcon 180B, OPT-175 B are some open-source LLMs, while Claude 2, Bard, GPT-4, are some proprietary LLMs.

What are LLMs used for?

• LLMs can be trained to do a number of tasks. One of the most well-known uses is their application as generative AI: when given a prompt or asked a question, they can produce text in reply.
• The publicly available LLM ChatGPT, for instance, can generate essays, poems, and other textual forms in response to user inputs.

                                                      Source: Indian Express