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Building LLM Powered  Applications

You're reading from   Building LLM Powered Applications Create intelligent apps and agents with large language models

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781835462317
Length 342 pages
Edition 1st Edition
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Author (1):
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Valentina Alto Valentina Alto
Author Profile Icon Valentina Alto
Valentina Alto
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Table of Contents (16) Chapters Close

Preface 1. Introduction to Large Language Models 2. LLMs for AI-Powered Applications FREE CHAPTER 3. Choosing an LLM for Your Application 4. Prompt Engineering 5. Embedding LLMs within Your Applications 6. Building Conversational Applications 7. Search and Recommendation Engines with LLMs 8. Using LLMs with Structured Data 9. Working with Code 10. Building Multimodal Applications with LLMs 11. Fine-Tuning Large Language Models 12. Responsible AI 13. Emerging Trends and Innovations 14. Other Books You May Enjoy
15. Index

The latest trends in language models and generative AI

As we saw in the previous chapters, LLMs set the basis for extremely powerful applications. Starting with LLMs, over the last months we have witnessed an explosive advancement in generative models, from multimodality to newly born frameworks, to enable multi-agent applications. In the next sections, we will see some examples of these new releases.

GPT-4V(ision)

GPT-4V(ision) is a large multimodal model (LMM) developed by OpenAI and officially released in September 2023. It enables users to instruct GPT-4 to analyze image inputs provided by the user. This integration of image analysis into LLMs represents a significant advancement in AI research and development. Model multimodality was achieved by using a technique called image tokenization, which converts images into sequences of tokens that can be processed by the same model as text. This allows the model to handle different types of data, such as text and images, and...

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