How ChatGPT Works: NLP and LLMs

Have you ever wondered how generative AI applications like ChatGPT work? Recently becoming wildly popular, ChatGPT brought generative AI to a general audience by creating an intuitive interface that built on existing technology: Large Language Models (LLMs), a subset of Natural Language Processing (NLP) as a whole. Let’s take a look at the tech behind ChatGPT and similar text-based generative AI programs. 

What Is Natural Language Processing and When Was It Created?

Natural language processing (NLP) describes the ways that computer systems try to understand, interpret, and use human language. The goals of NLP include translating between languages, understanding human speech, extracting meaning from text, and, importantly for generative AI applications, generating coherent written or spoken responses, among other capabilities.

The foundations of NLP emerged in approximately the 1950s when researchers began exploring ways for computers to translate between languages. Early NLP systems were coded by hand with linguistic rules and lexicons. Starting in the 1980s, statistical NLP techniques leveraged machine learning to train algorithms on a body of text and speech data. Using statistics to predict meaning allowed for more flexibility and accuracy in processing the nuances of natural language. Over time, the rise of neural networks and deep learning has revolutionized NLP by enabling more human-like language understanding and generation.

Key innovations like word embeddings, transformer architectures, and, thanks to the internet, vast datasets for training have improved NLP systems' abilities in areas like translation, conversational agents, and text summarization. With increasing computational power and accumulating training data, NLP models have become increasingly more competent at core linguistic tasks that were once only possible for humans.

What Is a Large Language Model?

Large language models (LLMs) are a type of NLP that uses powerful neural networks trained on huge amounts of text to generate human-like language. The next phase of NLPs, LLMs are trained using self-supervised learning–the model simply predicts the next “token” (often, a word)  in passages of text, learning associations and patterns that tend to occur within a language. LLMs may have the ability to change billions of parameters, allowing for strong linguistic capabilities, but also require a lot of computing power. Examples of LLMs include GPT-3, which ChatGPT was using when it became popular, BERT, and PaLM. As Large Language Models continue to evolve, the capabilities of generative AI will also expand.

How LLMs and Generative AI Are Changing The World and Modern Business

With the advent of large language models (LLMs) and generative AI, the world has already seen significant impacts on how individuals and organizations communicate, create, and operate. Nowadays, in theory anyone can create written documents or even works of art using these applications. In practice, there are limitations, but this technology has undeniably changed the course of life in general and business in particular in a very short time. These advances are enabled by the massive neural networks of LLMs like GPT-3 and DALL-E 2 which can generate impressive text, code, audio, and imagery, mimicking those normally generated by humans.

For businesses, marketing, design, and customer service functions are all being augmented by generative AI. Marketers can instantly generate banners, social posts, and even ad copy tailored to campaigns, with the caveat that humans must always review and edit these items before publication. Designers have an on-demand tool to get inspiration, iterations, and even fully formed creations, although there have been serious ethical concerns about the possibility that the model has learned the style of real artists without compensating them for the use of elements of their work. Customer service representatives can have an AI assistant that answers routine inquiries 24/7, although this cannot replace a conversation with a real person for any matter involving emotional or ethical concerns. These applications save costs and empower human team members to focus on creative, strategic work.

Why Generative AI Matters So Much

Across industries, generative AI is changing the process of coming up with ideas, accelerating discovery and innovation. Generative AI is great at brainstorming and refining lists of concepts in response to prompts from human beings. Additionally, by taking over the initial steps of some mundane tasks, such as drafting an email response, generative AI can free up human brainpower for tasks that require true creativity. Rather than replacing humans, generative AI can assist humans to do their jobs more efficiently and to rise to new levels of productivity and achievement.

As LLMs continue evolving, generative AI will continue to shape an ever-growing number of areas of, work, and business. When human intelligence collaborates with artificial intelligence, human capabilities are enhanced and efficiency increases, allowing for greater productivity. For this reason, it is important for business owners to understand the uses of ChatGPT and similar models in their daily operations, in order to remain competitive.

How These Elements Power ChatGPT

ChatGPT is powered by a large language model that has been trained on massive text datasets using machine learning techniques. NLP allows ChatGPT to analyze and understand human languages in a conversational format, rather than with specific commands entered into a command-line interface. It can generate text that sounds like a human wrote it, by predicting the most probable next words given the previous words and conversational context. The models also learn as they go. For example, as more people use ChatGPT, it incorporates these new interactions into its training data to continuously improve its NLP capabilities. With a neural network enabled by advances in computing power and model architecture, ChatGPT demonstrates the potential of LLMs to perform sophisticated linguistic tasks.

Square Peg Technologies Can Help Implement Tailored AI Solutions for Your Business

As we have discussed, knowledge of how ChatGPT can modernize your business operations has become essential. If your organization wants to get started with AI, you want to make sure you implement it in the right way. Square Peg Technologies’ experts can tailor AI solutions for your organization, ensuring that your goals drive the process and that all stakeholders’ interests are considered. Reach out today to get started and make sure that as AI transforms the world of business, your organization doesn't get left behind.