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Building LLM Powered Applications

You're reading from Building LLM Powered Applications

Product type Book

Published in May 2024

Publisher Packt

ISBN-13 9781835462317

Pages 342 pages

Edition 1st Edition

Languages

Concepts

Artificial Intelligence

Author (1):

Valentina Alto

Table of Contents (16) Chapters

Preface

1. Introduction to Large Language Models

2. LLMs for AI-Powered Applications

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

Option 1: Using an out-of-the-box toolkit for Azure AI Services

Formerly known as Azure Cognitive Services, Azure AI Services are a set of cloud-based APIs and AI services developed by Microsoft that enable developers and data scientists to add cognitive capabilities to their apps. AI Services are meant to provide every developer with AI models to be integrated with programming languages such as Python, C#, or JavaScript.

Azure AI Services cover various domains of AI, including speech, natural language, vision, and decision-making. All those services come with models that can be consumed via API, and you can decide to:

Leverage powerful pre-built models available as they are and ready to use.
Customize those pre-built models with custom data so that they are tailored to your use case.

Hence, considered all together, Azure AI Services can achieve the goal of multimodality, if properly orchestrated by an LLM as a reasoning engine, which is exactly the framework...

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Authors (1)

Valentina Alto

After completing her bachelor's degree in finance, Valentina Alto pursued a master's degree in data science in 2021. She began her professional career at Microsoft as an Azure Solution Specialist, and since 2022, she has been primarily focused on working with Data & AI solutions in the Manufacturing and Pharmaceutical industries. Valentina collaborates closely with system integrators on customer projects, with a particular emphasis on deploying cloud architectures that incorporate modern data platforms, data mesh frameworks, and applications of Machine Learning and Artificial Intelligence. Alongside her academic journey, she has been actively writing technical articles on Statistics, Machine Learning, Deep Learning, and AI for various publications, driven by her passion for AI and Python programming.

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