Generative AI vs. Large Language Models: What’s the Difference?

Generative artificial intelligence (GAI) and large language models (LLMs) are both forms of artificial intelligence systems. However, GAI refers to any artificial intelligence system that generates content, while LLMs can understand and generate language. Although these two systems differ, some technologies, such as Open AI’s GPT-4 encapsulate both. Learn more about GAI versus LLMs and what these technologies are capable of.

Generative AI

GAI is a deep learning model capable of generating various forms of content, such as text, video, images, and even music, depending on the training data it receives. Rather than taking training data and using it to make predictions like previous AI models, GAI instead uses it to learn to create its own unique, similar data. For example, you could give a GAI model a set of data consisting of pictures of cats. The model would then learn to recognize patterns and the distribution of pixels throughout the images to be able to produce its own pictures of cats.

What is generative AI used for?

GAI already has use cases across many different industries, such as manufacturing and health care. Some examples of how you can implement GAI include: 

• Manufacturing: In the manufacturing industry, GAI can recognize problems and suggest solutions to keep equipment functioning. GAI can also advise you on supply chain decisions by analyzing availability, costs, and logistics.

• Health care: GAI benefits the health care industry by enhancing the quality of medical images to improve the accuracy of diagnosis. It also allows health care providers to see how specific treatments may impact a patient's health based on the data.

• Insurance: For insurance companies, GAI helps automate administrative work. It can also detect fraud and assess risk by analyzing data and recognizing patterns.

• Automotive: In the automotive industry, GAI can play a valuable role in the design process by helping companies design cars more efficiently. This allows the auto companies to move towards production faster while also contributing to more innovative, creative car designs.

Advantages of generative AI

Choosing to implement GAI systems can offer your organization several advantages. For businesses, automating routine processes can lead to significant increases in productivity by freeing employees to focus on other work. Additionally, GAI can improve customer service by providing access to chatbots at any hour of the day. It can also help develop more personalized experiences and product offerings. 

Disadvantages of generative AI

Although GAI certainly has its benefits, some challenges and potential downsides also exist. One such challenge is the ethical concerns raised by GAI. Sometimes, people may use GAI to create fake content and misinform the public. Also, GAI models may contain sensitive data, making it important to encrypt data and follow data privacy regulations. 

Large language models

A large language model (LLM) is another type of artificial intelligence powered by deep learning that can generate human language. It allows the model to write text, translate different languages, answer questions, and perform other tasks related to language. LLMs work by analyzing massive amounts of training data and learning to predict what word will come next in a sentence by assigning words a probability score based on the surrounding context. Eventually, LLMs gain the knowledge to pick up on these patterns accurately and generate relevant text.

What are large language models used for?

LLMs have a range of useful business applications for industries such as marketing and computer programming. Examples of real-world use cases for LLMs include:

• Marketing: Developing marketing campaigns that consist of sending content through avenues such as social media and emails is simpler with the help of LLM text generation. LLMs can generate relevant responses by analyzing documents directly from your business and web content. It can also allow you to organize your customer base into segments to take a more personalized approach through sentiment analysis using natural language processing. 

• Computer programming: LLMs make coding easier for programmers by writing parts of code for them, debugging, increasing code-writing efficiency, and even translating code between programming languages.

• Education: LLMs offer benefits for teachers, making it possible to quickly take care of routine tasks such as creating lesson plans and grading quizzes. This frees up time for teachers to focus on more meaningful tasks.

Advantages of large language models

A significant advantage of utilizing LLMs is time-saving, since you can automate several different processes. Another benefit is their flexibility: You can train them to perform a wide range of tasks. They can provide innovative solutions to problems, offering a new perspective on challenges. 

Disadvantages of large language models

When working with LLMs, it’s important to consider some of their challenges. For example, to use LLMs effectively and generate usable results, you must know how to create the correct prompts. Additionally, the quality of your LLM output can vary depending on the training data it receives and how you use it.

Generative AI vs. large language models: Other things to consider

Since the term “GAI” describes artificial intelligence models that generate content, LLMs are technically a type of GAI because you can use LLMs to generate text. 

The GAI industry projects substantial growth over the next decade as businesses use the tool to operate more efficiently, minimize costs, and better serve their customers. Data from Statista suggests the global GAI market will reach $356 billion by 2030 [1].

Discover more about GAI and LLMs on Coursera.

GAI and LLMs are forms of artificial intelligence capable of generating text. GAI goes further than LLMs because it can generate images, videos, and more. Generative AI Fundamentals Specialization from IBM on Coursera covers various applications of GAI, with projects to help you practice generating text and images.

Generative AI with Large Language Models from DeepLearning.AI is another excellent option to grow your knowledge of generative AI, explore the architecture of LLMs, and discover practical applications for LLMs.