ai and machine learning

You’ll want to read this to get an honest, first-hand look at the new Copilot for Azure during its limited public preview. I share my experience using this generative AI helper for tasks like generating KQL queries, highlighting both its potential to assist IT pros and its current limitations regarding context awareness and session length.

As a long-time Grammarly user, I recently tested the new GrammarlyGO premium feature to determine if its Generative AI capabilities justify the added cost. While the integration is fast and neat, I found the pricing steep and the loss of local prompt data frustrating, leaving me uncertain if it offers enough value to replace my existing workflow.

Discover how to run powerful generative AI models locally using Ollama, a free tool that simplifies hosting Large Language Models on your own machine. I will walk you through the setup process and demonstrate how to leverage Microsoft’s efficient Phi-2 model for high-performance, privacy-focused AI interactions.

If you are worried about the security risks associated with adopting generative AI tools like ChatGPT or Copilot, this post explains why Data Security Posture Management (DSPM) is becoming essential for protecting your organization's data. I explore how DSPM differs from traditional cloud security management and demonstrate how solutions like Microsoft Purview can help govern AI workloads, assess data risks, and ensure compliance in today’s rapidly evolving technological landscape.

As Microsoft Security Copilot nears release, I outline practical steps you can take today to prepare for its arrival. I recommend auditing your current security services to identify relevant data points and establishing a separate test tenant to safely trial the AI's capabilities without impacting your production environment.