Large Language Models:
A government working paper released recently suggested that AI large language models (LLMs) like ChatGPT should, by default, have access to content freely available online, and that publishers should not have an opt-out mechanism for such content.
- An 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, which excels at handling sequences of words and capturing patterns in text.
- 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.
- But 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.
- LLMs can perform various language tasks, such as answering questions, summarizing text, translating between languages, and writing content.
- Businesses use LLM-based applications to help improve employee productivity and efficiency, provide personalized recommendations to customers, and accelerate ideation, innovation, and product development.
- LLMs serve as the foundational powerhouses behind some of today’s most used text-focused generative AI (GenAI) tools, such as ChatGPT, Claude, Microsoft Copilot, Gemini, and Meta AI.
- Since LLMs are now becoming multimodal (working with media types beyond text), they are now also called “foundation models”.
- LLMs face challenges that may include computational requirements, ethical concerns, and limitations in understanding context.
