Copilot Chat: Understand its Potential and Leveraging it in Healthcare
Key Takeaways from Our Recent Webinar In our recent webinar, hosted on Feburary 27th, 2025, we explored the transformative potential of Copilot Chat in the healthcare sector, a tool designed to enhance productivity and streamline a varity of workflows for clinical, administrative, and executives. The session was hosted by Taylor Kirkland, a Modern Work Specialist, Michael Goad, a Coilot Technical Specialist, and Nick Stillings, a Principal Cloud Solutions Architect. Together, they provided an in-depth overview of Copilot Chat, covering: Understanding Microsoft Copilot Chat Copilot Chat Security Deployment of Microsoft Copilot Chat Real-World Applications and Demo in Healthcare Resources and Support Q&A Session Introduction to Copilot Chat Taylor Kirkland kicked the webinar off, outlining the agenda, which encompassed an understanding of Copilot Chat, its security measures, deployment strategies, and live demonstrations. With the objective to equip attendees with a foundational grasp of Copilot Chat and its significance for healthcare customers. The Imperative for AI in the Workplace The webinar switched gears to discuss how employees across various generations are increasingly integrating AI into their personal and professional routines. Over 70% of individuals acknowledge incorporating AI into their work processes, underscoring the necessity for a unified solution like Copilot Chat to address these evolving needs. Features and Benefits of Copilot Chat Michale Goad took the reigns and elaborated on how Copilot Chat is engineered to deliver a consistent user experience with standardized governance and controls, which is important to healthcare, providing AI for everyone in a secure way and providing standrarization for how and where users use AI. Nick Stillings provided a live demonstration of Copilot in action! Understanding Copilot as a UI for AI Michael Goad also provided an analogy, likening Copilot to a smartphone that serves as a gateway to various applications or agents. These agents perform diverse tasks, such as answering queries or automating processes. Copilot Chat aims to democratize access to AI, enabling users to leverage AI securely and efficiently. Enterprise Data Protection and Security A significant segment of the webinar was dedicated to the security features of Copilot Chat and emphasized the critical importance of Enterprise Data Protection (EDP), which ensures that data is encrypted both at rest and in transit and discussed how data remains confidential and is not utilized to train AI models. Live Demos and Practical Applications The webinar featured live demonstrations showcasing the practical applications of Copilot Chat. Alongside Nick Stillings, a Modern Work User Architect, demonstrated how Copilot Chat can be utilized to summarize content, generate images, and interact with agents. These demos underscored the versatility and potential of Copilot Chat in various business scenarios. Conclusion and Q&A The session concluded with Q&A segment, where participants had the opportunity to pose questions and gain deeper insights into Copilot Chat. If you are interested in learning more about Copilot and Copilot Chat, please reach out to your Microsoft account teams for more detailed explorations of specific topics and to utilize the resources available on adoption.microsoft.com.Generating Videos in Microsoft 365 Copilot Using Visual Creator Agent
Video content has become an essential medium for communication, learning, and marketing. Microsoft 365 Copilot, combined with the Visual Creator Agent, is redefining the way professionals create videos. By leveraging AI-driven automation, users can generate high-quality videos with minimal effort. In this blog, we’ll explore how the Visual Creator Agent works within Microsoft 365 Copilot, its key features, and how you can use it to streamline video production. Full details in this blog https://dellenny.com/generating-videos-in-microsoft-365-copilot-using-visual-creator-agent/Blog about How to Use Power Automate to Automatically Send Copilot-Generated Tasks to To Do
Microsoft Teams Copilot makes it easy to track action items from meetings and discussions. By integrating these tasks with Microsoft To Do, you can streamline your workflow and stay on top of your responsibilities. With Power Automate, you can take this a step further by automating the process of sending Copilot-generated tasks directly to Microsoft To Do, reducing manual effort and improving productivity. This blog will guide you through setting up this automation. https://dellenny.com/how-to-use-power-automate-to-automatically-send-copilot-generated-tasks-to-microsoft-to-do/
Consumption-based pricing for SharePoint agents
Learn more about the pay-as-you-go pricing model as it relates to SharePoint agents in Microsoft 365. Last month, we introduced consumption-based pricing for SharePoint agents. This new billing model offers greater flexibility for organizations looking to start using SharePoint agents. The pay-as-you-go (PAYGO) meter enables customers to pay only for the messages they consume, providing an alternative to a per user/per month license. This model is designed to accommodate varying usage patterns, making it ideal for businesses with fluctuating demands.Construyendo una Aplicación Web con Inteligencia Artificial usando Python
En la segunda sesión del GitHub Copilot Bootcamp LATAM, organizado por Microsoft Reactor, el ingeniero Manuel Ortiz, Embajador de Microsoft Learn y líder comunitario en GitHub, guió a desarrolladores en la creación de una aplicación web con capacidades de inteligencia artificial. Este taller práctico combinó fundamentos de desarrollo backend en Python con técnicas avanzadas de integración de modelos de lenguaje de Azure OpenAI. Introducción a Azure Open AI Azure Open AI es una colaboración entre Microsoft y OpenAI que permite a los desarrolladores integrar modelos avanzados de inteligencia artificial en sus aplicaciones utilizando la infraestructura de Azure. Esto ofrece acceso a modelos poderosos como GPT-4, que pueden ser utilizados para una variedad de tareas, desde procesamiento de lenguaje natural hasta generación de texto. Configuración de Azure Open AI Para comenzar a usar Azure Open AI, debes seguir algunos pasos básicos: Crear una Cuenta en Azure: Si aún no tienes una cuenta, puedes crear una en el portal de Azure. Los estudiantes pueden solicitar créditos gratuitos para usar los servicios de Azure. Crear un Servicio Azure Open AI: Accede al portal de Azure y busca "Azure Open AI". Haz clic en "Crear" y selecciona tu suscripción y grupo de recursos. Elige la región y configura el nombre del servicio, que debe ser alfanumérico y sin caracteres especiales. Selecciona el plan de precios adecuado y finaliza la creación del servicio. Obtener las Credenciales: Después de crear el servicio, necesitarás las credenciales (clave de API y endpoint) para autenticar tus solicitudes. Estas credenciales se pueden encontrar en la sección de "Claves y Endpoints" del servicio creado. Integración con Python y Flask Python es uno de los lenguajes de programación más populares para el desarrollo de aplicaciones de inteligencia artificial debido a su simplicidad y vasta biblioteca de herramientas. Durante la configuración, puedes usar varias bibliotecas y herramientas que facilitan el desarrollo de IA con Python, incluyendo: TensorFlow: Una biblioteca de código abierto para aprendizaje automático. Keras: Una API de alto nivel para redes neuronales, que funciona sobre TensorFlow. Scikit-learn: Una biblioteca para aprendizaje automático en Python. Flask: Un microframework para desarrollo de aplicaciones web. Una vez configurado el servicio Azure Open AI, puedes integrarlo en tus aplicaciones Python usando Flask. Aquí tienes un ejemplo de cómo hacerlo: Instalación de las Bibliotecas Necesarias: Crea un entorno virtual e instala las bibliotecas necesarias, como flask y openai. Configuración del Proyecto: Crea un archivo .env para almacenar tus credenciales de forma segura. Configura tu aplicación Flask para cargar estas credenciales y conectarse al servicio Azure Open AI. Creación del Modelo de IA: Utiliza la biblioteca openai para enviar prompts al modelo y recibir respuestas. Integra estas respuestas en tu aplicación web para proporcionar funcionalidades de IA a los usuarios. Ejemplo de Código Aquí tienes un ejemplo simplificado de cómo configurar y usar Azure Open AI en una aplicación Flask: from flask import Flask, request, render_template import openai import os app = Flask(__name__) # Cargar las credenciales del archivo .env openai.api_key = os.getenv("AZURE_OPENAI_API_KEY") openai.api_base = os.getenv("AZURE_OPENAI_ENDPOINT") @app.route("/", methods=["GET", "POST"]) def index(): response_text = "" if request.method == "POST": prompt = request.form["prompt"] response = openai.Completion.create( engine="text-davinci-003", prompt=prompt, max_tokens=100 ) response_text = response.choices.text.strip() return render_template("index.html", response_text=response_text) if __name__ == "__main__": app.run(debug=True) Beneficios de Azure Open AI Acceso a Modelos Avanzados: Utiliza los modelos más recientes y poderosos de OpenAI. Escalabilidad: La infraestructura de Azure permite escalar tus aplicaciones según sea necesario. Seguridad y Conformidad: Benefíciate de las robustas medidas de seguridad y conformidad de Azure. Sigue aprendiendo Si deseas aprender más sobre estas técnicas, mira las grabaciones del GitHub Copilot Bootcamp, comienza a utilizar el GitHub Copilot gratuito y descubre cómo transformar tu manera de programar utilizando inteligencia artificial.GitHub Copilot 2025년 3월 업데이트
Visual Studio Code 2025년 2월 릴리스에 오신 것을 환영합니다. 이번 버전에서는 다양한 기능을 추가했으며, 특히 GitHub Copilot과 관련한 주요 업데이트는 다음과 같습니다: Next Edit Suggestions (미리보기) - Copilot이 다음으로 수정할 가능성이 높은 코드를 예측합니다. Agent 모드 (미리보기) - Copilot이 자동으로 작업을 완료합니다. Copilot Edits의 노트북 지원 - 노트북 파일의 편집을 쉽게 할 수 있습니다. 코드 검색 - Copilot이 채팅 프롬프트와 관련된 파일을 검색합니다. 사용자 지정 지침 GA - Copilot을 사용자의 요구에 맞게 설정할 수 있습니다.
