The advent of ChatGPT and other large language models and generative AI has drawn global consumers, business entities, and C-suite interest.
Azure Machine Learning prompt flow is a development tool designed to streamline the entire development cycle of AI applications powered by Large Language Models (LLMs). As the momentum for LLM-based AI applications continues to grow across the globe, Azure Machine Learning prompt flow provides a comprehensive solution that simplifies the process of prototyping, experimenting, iterating, and deploying your AI applications.
In this demo-drive session, Microsoft Business Applications and AI MVP and Microsoft Certified Trainer Prashant G Bhoyar will delve deeper into several intricate details and technical aspects and will also cover Practical guidance on developing robust, scalable Custom next-gen applications using Azure OpenAI, and Azure Machine Learning Prompt Flow focusing on industry requirements and best practices.
Azure OpenAI Services: We will explore what these services are, their architecture, and their place within the broader AI ecosystem.
Prompt Engineering: An in-depth look at this critical aspect of large language model usage. We will cover how prompts work, why they are important, and the factors that influence their effectiveness.
Customizing Azure OpenAI Services: From configuration to deployment, we'll show you how to tailor these services to suit a range of specific needs.
Deep dive into Azure Open AI Services: We'll specifically focus on several of the models like GPT, Davinci, Ada, Babbage, Curie, and Cushman, discussing their unique features and optimal use cases.
Prompt Flow Overview: A development tool designed to streamline the entire development cycle of AI applications powered by Large Language Models (LLMs).
Creating Enterprise-Level next-gen Applications: Practical guidance on developing robust, scalable Copilot applications using Azure Open AI, ChatGPT, and Prompt Flow, focusing on industry requirements and best practices.