What’s new in Data & AI: Extend the reach of AI with data connectors and integrations
Data is the lifeblood of any business, and AI is the key to unlocking its full potential. However, harnessing the volume and complexity of data from apps, services, sensors, and more can be a significant challenge to fueling impactful AI. By investing in a unified, intelligent data platform, organizations can not only save on integration costs and improve their security posture, but also enable more advanced AI capabilities. Healthcare companies like Mercy, manufacturers like Aurobay, Financial Services providers like Manulife, and other companies across industries are paving the way for AI innovation by modernizing their data with Microsoft Azure.
The rise of generative AI presents an especially exciting opportunity to transform your data into a competitive advantage. For example, Atera is transforming IT Management by combining foundation models in Azure OpenAI Service with unique business data, providing customers with an all-encompassing view of IT activities to proactively identify issues, and recommend immediate solutions. Likewise, startup Commerce.AI is driving 30 to 50 percent increases in productivity for customers by using Azure OpenAI Service to extract insights from unstructured data, like customer support calls and online reviews, uncovering new growth opportunities, and automating workflows. By using foundation models as a reasoning engine—not a knowledge base—organizations can build more relevant, differentiated solutions for customers and end-users.
In this month’s blog post, I’ll explore new ways that organizations can connect their business data to Azure AI to unearth meaningful insights, predictions, and actions. First, here are new learning and skilling resources to help your teams get inspired and build a proof of concept quickly.
Skill up with the latest resources for Azure AI developers
Azure OpenAI Service provides organizations with access to OpenAI’s powerful large language models (LLMs), enabling various natural language processing (NLP) solutions to understand and generate content. Developers can access the service through REST APIs, SDKs, and a studio UI. Our new, free online course Develop generative AI solutions with Azure OpenAI Service provides developers with the skills they need to start building solutions with Azure OpenAI Service, and includes a module on responsible generative AI, with guidance and tools to implement solutions responsibly. For organizations that want more customization, we published a new course on how to Fine-tune a foundation model with Azure Machine Learning, providing machine learning professionals with step-by-step guidance on how to explore, fine-tune, and deploy LLMs, all from the model catalog in Azure Machine Learning.
Build a chatbot that uses your own organizational data with Power Virtual Agents and Azure OpenAI Service
Exciting news for chatbot developers: Microsoft now offers seamless integration between Power Virtual Agents and Azure OpenAI Service, helping you unlock the full potential of conversational experiences and generative AI together. Chatbot builders now have two ways to combine these popular services: using no-code out of the box generative AI features within the Power Virtual Agents studio, or through low-code or code-first experiences in Azure AI Studio. And, since you can combine Power Virtual Agents with over 1000 software as a service (SaaS) connectors using Power Automate, there’s limitless opportunities to enrich your chatbot conversations with enterprise services and contextual information.
This update expands the groundbreaking Azure OpenAI Service on your data feature, which enables effortless ingestion of data from any source—be it local or cloud-based—to ground your Azure OpenAI Service solution with contextual data. Grounding models on your data supports more accurate and relevant outputs. For example, a retail company may ground their Power Virtual Agent experience in return policies, discount codes for campaigns, and product catalogs to provide more helpful responses to customers on their website. Because the Azure OpenAI model has access to, and can reference these specific sources to support its responses, answers are not only based on its pretrained knowledge but also on the latest information available in these designated data sources. This grounding data also helps the model avoid generating responses based on outdated or incorrect information.
You must be logged in to post a comment.