-- In this paper, m ilitary use cases or applications and implementation thereof are considered for natural language processing and large language models, which have broken into fame with the invention of the generative pre - trained transformer (GPT) and the extensive foundation model pretraining done by OpenAI for ChatGPT and others . First, we interrogate a GPT - based language model (viz. Microsoft Copilot) to make it reveal its own knowledge about their potential military application s and then critically assess the information . Second, we study how commercial cloud services (viz. Microsoft Azure) could be used readily to build such applications and assess which of the m are feasible. We conclude that t he summarization and generative properties of language models directly facilitate many applications at large and other features may find particular uses . This paper was originally presented at the NATO Science and Technology Organization Symposium (ICMCIS) organized by ...

Smart phones were the first step in bringing the internet, data, and AI away from the desk and allowing us to be connected and sense some of the world around us wherever we go. The next step was wearables. These started as smart watches and fitness trackers, but this is slowly expanding into smart connected clothing and other devices. In this series we learn how to build some smart wearables, leveraging the power of the cloud to make our clothes come to life along with Raspberry Pi's amazing new board, the Pi Zero W 2! Learn how to add subtitles to your speech with a smart t-shirt, light up your hoodie when people say nice things about you, or have a parrot on your shoulder that reads to you. These events are run through the Microsoft Reactor Meetup group.

It is a central hub for learning in Teams with AI that recommends the right content at the right time. With Viva Learning, employees can easily discover and share training courses, and managers get all the tools to assign and track the completion of courses to help foster a learning culture. Individuals can build their own training environments and track their progress on courses. Team leaders and supervisors also have the option to assign specific learning tasks to individual members of staff. Hence, it's a great way to keep your team growing in any environment. It is a central hub for learning in Teams with AI that recommends the right content at the right time.

Whether in the cloud or hybrid environments, AI Engineers develop and deploy cognitive services, machine learning, and knowledge mining solutions to help their organization stay ahead of the game. Get the skills and knowledge needed to build your career as a successful AI Engineer.

Qualified data professionals and cloud experts have promising job prospects in today's world of digital transformation. These pros help migrate data to the cloud, use AI and analytics to provide actionable insights, and manage significant volumes of data--including reporting and visualizing. If this is your skill set, earning your Microsoft Certification can help you prove that you have the necessary knowledge and experience and that you're ready for the job. We're constantly working to keep our certifications current. Today, I'm excited to announce upcoming changes for two role-based Azure certifications for data and AI--Microsoft Certified: Azure AI Engineer Associate and Microsoft Certified: Azure Data Engineer Associate--taking these certifications to the next level.

Time to set goals for expanding your programming skills while perfecting what you already know. This year, why not make a resolution to learn a new computer language? A new language under your belt--or new tools and services-- doesn't just give you more choices when deciding what projects to work on. It also helps you to better understand the strengths and weaknesses of the computer language(s) you already know as you figure out why the new language does things the way it does. Throughout this month, we will continue to help you with setting your learning goals.