This is part 4 of a series on generative AI and the Azure OpenAI service. Click here to read Part 1, with an emphasis on basics, Click here for Part 2Microsoft Copilot details, and Click here for Part 3to learn more about the new Bing experience.
Earlier in this series, we discussed how the Azure OpenAI Copilot stack provides access to generative models that are pretrained in trillions of words and can understand natural language and code. With Azure OpenAI Copilot, you can use these models to create applications that can help you write, code-generate, infer, infer, and understand.
What is Azure OpenAI Copilot?
The Azure OpenAI Copilot stack is a service that provides access to large-scale generative AI models that can understand and generate natural language and code. These models can be used to power a wide range of scenarios such as authoring assistance, code generation, and data inference. For example, you can use Copilot to summarize your sales calls, segment your marketing campaigns, or generate code for your app based on your descriptions.
How can startups benefit from Azure OpenAI Copilot?
Startups may have limited resources and time to develop products and services. You may also face challenges such as finding the right talent, expanding your business, and competing with big players. The Azure OpenAI Copilot stack helps overcome these challenges by enabling:
- Save time and reduce costs by automating tasks that require natural language or code generation.
- Leverage state-of-the-art AI models to improve output quality and accuracy
- Customize AI models to your specific needs by fine-tuning them with your own data and hyperparameters
- Use AI responsibly by filtering and moderating request and response content
- Protect your data and workloads with Azure’s enterprise-grade security and compliance features
The Azure OpenAI Copilot stack is not a one-size-fits-all solution as models can be customized for specific needs and scenarios. For example, you can use your own data and hyperparameters to fine-tune your model, or use the few-shot learning feature to provide examples and get more relevant results. You can also apply responsible AI capabilities to filter and condition request and response content to ensure you’re using your models ethically and safely.
Azure AI Studio can help here. Azure AI Studio is a cloud-based platform that allows you to build, manage, and deploy AI solutions using various tools and services. Using Azure AI Studio, you can create your own Azure OpenAI Copilot stack by following these steps:
1. Create an Azure account using the Founders Hub and sign up for the Azure OpenAI service.
2. Create a copilot with the following command. Azure OpenAI Playground
3. Inject your own data into the model.
Azure OpenAI service support the data Connect to multiple sources such as:
- Azure Cognitive Search index: Connect your data to Azure Cognitive Search indexes and enable seamless integration with OpenAI models.
- Azure Blob storage container: Connect your data to Azure Blob Storage containers and easily access it for analysis and conversation using Azure OpenAI Service.
- Local file: Connecting to files in the Azure AI portal provides flexibility and convenience in connecting data. Ingest data and split it into Azure Cognitive Search indexes. File formats such as txt, md, html, Word files, PowerPoint, and PDF can be used for analysis and conversation.
4. Create a new project in Azure AI Studio
5. In the catalog, select the model that best fits your use case from the available options.
You can choose between the latest and most advanced model, GPT-4, or the still very powerful and widely used GPT-3.
6. Use Prompted Flows.
Prompted Flow is a Powerful Feature Azure machine learning (AzureML) streamlines rapid engineering project development, evaluation, continuous integration and deployment (CI/CD). Data scientists and LLM application developers can have an interactive experience that combines natural language prompts, a template language, a list of built-in tools, and Python code.
7. Deploy the model as an endpoint that can be called from any application.
Depending on your scalability and security needs, you can choose from various deployment options such as Azure Kubernetes Service and Azure Container Instances.
8. Integrate the model with your application using the endpoint URL and access key.
By following these 8 steps, you can use Azure AI Studio to build your own Azure OpenAI Copilot stack for your startup and benefit from large-scale AI models for coding and language tasks. You can also use Azure AI Studio’s dashboards and tools like metrics, logs, and alerts to monitor and manage your models to ensure quality and reliability.
Unleash your startup’s potential with Azure OpenAI Service
Generative AI technologies such as Microsoft’s Azure OpenAI platform offer many benefits for startups looking to build next-generation businesses. Leveraging advanced AI-powered tools and applications, entrepreneurs can streamline operations, improve customer experiences, and drive growth.
However, it is important to use AI responsibly, incorporating ethical principles such as transparency, fairness, and accountability. Azure OpenAI Service gives startups access to a wide range of pre-built AI models and tools while ensuring responsible AI practices. Success stories from companies like Duolingo, Jasper AI, and Stripe provide concrete examples of how AI can change the trajectory of startups. As the technology continues to evolve, it is clear that companies that adopt OpenAI will have a competitive edge in the startup world as long as they act responsibly.
Not yet part of the Microsoft for Startups Founders Hub? sign up today Earn OpenAI API credits, technical advisories, up to $150,000 in Azure credits, access to Microsoft startup experts and mentors, and more.
Tags: Azure OpenAI Copilot, Azure OpenAI Service, Generated AI