This chapter covers
- Using pretrained large language models for text, image, speech, and code generation
- Few-shot, one-shot, and zero-shot prompting techniques
- Creating a zero-shot personal assistant with LangChain
- Limitations and ethical concerns of generative AI
The rise of pretrained large language models (LLMs) has transformed the field of natural language processing (NLP) and generative tasks. OpenAI’s GPT series, a notable example, showcases the extensive capabilities of these models in producing life-like text, images, speech, and even code. The effective utilization of these pretrained LLMs is essential for several reasons. It enables us to deploy advanced AI functionalities without the need for vast resources to develop and train these models. Moreover, understanding these LLMs paves the way for innovative applications that leverage NLP and generative AI, fostering progress across various industries.
In a world increasingly influenced by AI, mastering the integration and customization of pretrained LLMs offers a crucial competitive advantage. As AI evolves, leveraging these sophisticated models becomes vital for innovation and success in the digital landscape.