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Developing and deploying AI applications at scale requires a flexible platform that can create solutions grounded in an organization's organizational data. How would you describe your current AI app process? If there's room for improvement, take a look at this @Microsoft blog post outlining the new capabilities of the Phi-3 small language models that give your dev teams greater choice and flexibility when creating AI solutions.

Imagine finding anything in your storage, no matter how siloed, in seconds. That's possible with the powerful Windows 11 tool Recall, combined with a machine designed specifically for the AI experience like #Microsoft's Copilot+PCs, powered by a neural processing unit capable of 40 trillion operations per second. See this technology in action: DM Abrahams Consulting LLC to get an eye-opening demo.

When your business is under cyberattack, you may need to do an emergency password reset. To learn how, read this expert advice from Microsoft's incident response team. @Microsoft Security

Elevate your customer service quality with AI assistance. ✅ Increased efficiency ✅ Reduced wait times ✅ Exceptional service with less onboarding. Explore the interactive tour for insights into how @Microsoft Dynamics 365 Customer Service can reshape the way you engage with customers.

The most critical part of the app building process is defining what exactly you need the solution to address. But if you're building an intelligent app, the next step is just as important: identifying the data required to train the machine-learning models that power it. See how this fits together in this @Microsoft Azure eBook outlining how to infuse your apps with AI and what these supercharged elements can do for your operations.