Carey Payette
Trillium Innovations
Columbus, Ohio, United States
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Carey Payette is a Senior Software Engineer with Trillium Innovations (a Solliance partner), an ASPInsider, Progress Developer Expert, HashiCorp Ambassador, Microsoft Certified Trainer, and a Microsoft Azure MVP. Her primary focus is Cloud integration and deployment for the web, mobile, big data, AI, machine learning, and IoT spaces. Always eager to learn, you will find her tinkering regularly with various sensors, microcontrollers, programming languages, and frameworks.
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Streamlining Custom AI Development with the Azure OpenAI Assistants API
If you were one of the early adopters of OpenAI's tech and set out to build an AI assistant, you probably remember it being a bit of a coding odyssey. The chat completions API was efficient and capable, albeit very simple. It gets provided with a prompt, and it supplies a response. These were stateless calls, so it didn't remember conversations, which meant a lot of manual development in terms of maintaining chat states and integrating with various systems to augment the prompts with custom data.
The Azure OpenAI Assistants API provides a stateful API that simplifies the developer experience by keeping track of the conversation threads, freeing you from managing those endless chat histories or worrying about model prompt context limits. The Assistants API also provides a standard way of integrating external systems and custom logic via the code interpreter and function calling tools.
In this session, we will get up close with the Assistants API, learn all about its features, and find out how it streamlines the development of custom AI assistants.
Prompt Engineering 101 with Azure OpenAI
Learn basic prompt engineering techniques that help guide Azure OpenAI models to better performance for specific use cases, resulting in models that yield more accurate and relevant output. Learn common patterns and strategies to get the most out of your LLM.
Fine-tuning Azure OpenAI models
Learn what fine-tuning is and isn't in the context of Azure OpenAI. Evaluate alternatives to fine-tuning and the cases when fine-tuning is necessary. The session ends with a demonstration of how to create a training dataset, fine-tune an Azure OpenAI Chat GPT-3.5 model, and consume it.
Terraform in Azure Workshop
Infrastructure as Code (IaC) has become a critical part of DevOps, allowing for declarative definition, configuration, deployment, and management of simple and complex IT solutions. In this session, we’ll review the importance of IaC and how it fits into the Continuous Delivery aspect of DevOps. In addition, you will get hands-on with Terraform with labs and start deploying solutions to the Azure cloud!
Introduction to Azure Infrastructure as Code
Infrastructure as Code (IaC) has become a critical part of DevOps, allowing for declarative definition, configuration, deployment, and management of simple and complex IT solutions. In this session, we’ll review the importance of IaC and how it fits into the Continuous Delivery aspect of DevOps. In addition, you will get a taste of different IaC technologies, such as ARM, Bicep, Terraform, Ansible, and Pulumi, to manage your Azure resources.
Azure MLOps Workshop
Many organizations are looking to train and deploy custom-trained machine learning models. MLOps provides environments, compute, data organization, versioning, and end-to-end pipelines that bring your models to fruition. This workshop provides an overview of MLOps in Azure and then proposes a series of challenges for you to solve alone or in a group.
Carey Payette
Trillium Innovations
Columbus, Ohio, United States
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