• 4 min read

Azure OpenAI Service powers the Microsoft Copilot ecosystem

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Copilot—powered by Microsoft Azure OpenAI Service—allows you to simplify how you design, operate, optimize, and troubleshoot apps and infrastructure from cloud to edge.

Many AI systems are designed for collaboration: Copilot is one of them. Copilot—powered by Microsoft Azure OpenAI Service—allows you to simplify how you design, operate, optimize, and troubleshoot apps and infrastructure from cloud to edge. It utilizes language models, the Azure control plane, and insights about your Azure and Arc-enabled assets. All of this is carried out within the framework of Azure’s steadfast commitment to safeguarding data security and privacy.

Azure OpenAI Service

Build your own copilot and generative AI applications

A brief history of AI collaboration with copilots

In aviation terms a copilot is responsible for assisting the pilot in command, sharing control of the airplane, and handling various navigational and operational tasks. Having a copilot ensures that there is a second trained professional who can take over controls if the main pilot is unable to perform their duties, thereby enhancing safety.

Microsoft originally introduced the concept of a copilot two years ago as an AI pair programmer in GitHub to assist developers in generating code, catching errors, and suggesting improvements. Today, Azure OpenAI Service powers more than just GitHub Copilot. Microsoft 365 Copilot performs as a digital companion for your whole life creating a single Copilot user experience across Bing, Edge, Microsoft 365, and Windows.

AI at the service of others

Microsoft Copilot represents a profound shift in how AI-powered software can support the user experience, the architecture, the services that it uses, and how we think about safety and security.

We now have machines that are so fluent in human language. Every place that you interact with a machine ought to be much more fluent in human natural language and I think we’ll start to see that change coming in a lot of different places as well and it will really redefine the interfaces that we’re used to.Eric Boyd, head of AI at Microsoft.

Copilots powered by Azure OpenAI Service can be trained on a specific set of data to adapt the model to a specific domain. We’re seeing developments across a variety of sectors. For example:

Language translation: Language translation models can help bridge communication gaps between people who speak different languages. This can be particularly useful in situations such as emergency response, disaster relief, and international diplomacy.

Educational support: Educational chatbots that can help students with homework, provide personalized tutoring, and answer questions related to different subjects.

Crime investigation: Financial crimes such as money laundering and fraud are linked to human trafficking, child exploitation, terrorism, theft, and wildlife trafficking. SymphonyAI’s new Sensa Copilot acts as a sophisticated AI assistant to a financial crime investigator by automatically collecting, collating, and summarizing financial and third-party information.

Medical reporting: Generative AI has the potential to increase the power and accessibility of self-service reporting, making it easier for healthcare organizations and their providers to identify operational improvements, including ways to reduce costs and to find answers to questions both locally and within a broader context. 

Climate change: Azure OpenAI Service can be used to generate educational materials or assist in research on topics related to climate change, including natural disasters, global warming, and environmental conservation.

Inclusive and diverse avatars: DeepBrain AI includes a library of photo-realistic and virtual avatars that businesses can use for training videos, news broadcasts, marketing videos, and more. An integral part of the digital world, avatars foster a sense of inclusivity and diversity by allowing people to choose representations that reflect their individuality, regardless of physical appearance or other limitations.

Industrial advances: ABB is partnering with Microsoft to integrate Azure OpenAI Service into its ABB Ability™ Genix Industrial Analytics and AI suite with the goal of boosting real-time insights and asset longevity by 20% and reducing unplanned downtimes by 60%. Additionally, it will aid in monitoring and optimizing industrial emissions and energy usage, contributing to sustainability goals.

Prioritizing human agency

The Copilot System powered by Azure OpenAI Service builds on our existing commitments to data security and privacy in the enterprise. Copilot automatically inherits your organization’s security, compliance, and privacy policies for Microsoft 365. Data is managed in line with our current commitments. Copilot prioritizes human agency and puts the user in control. This includes noting limitations, providing links to sources, and prompting users to review, fact-check, and fine-tune content based on their own knowledge and judgment.

AI systems can analyze and learn from copious amounts of data and help employees make decisions based on that data. They can be programmed for specific tasks such as image recognition and natural language processing.

While technology has the potential to generate both favorable and adverse consequences, technological developments such as Copilot are proving far more likely to help society steer a straight and humane course toward a future that benefits us all.

Learn, connect, and explore with the latest technologies announced at Microsoft Ignite.

Our commitment to responsible AI

With Responsible AI tools in Azure, Microsoft is empowering organizations to build the next generation of AI apps safely and responsibly. Microsoft has announced the general availability of Azure AI Content Safety, a state-of-the art AI system that helps organizations keep AI-generated content safe and create better online experiences for everyone. Customers—from startup to enterprise—are applying the capabilities of Azure AI Content Safety to social media, education, and employee engagement scenarios to help construct AI systems that operationalize fairness, privacy, security, and other responsible AI principles.

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