If you’re working with Azure Functions and need to pass custom data or properties during execution, you’ll find that the built-in context parameter doesn’t support adding arbitrary properties directly ...

Microsoft has moved its Model Context Protocol (MCP) support for Azure Functions to General Availability, signaling a shift toward standardized, identity-secure agentic workflows. By integrating ...

As agent-based AI systems grow more sophisticated, developers are moving well beyond basic Retrieval-Augmented Generation (RAG) into a new era of autonomous, tool-integrated, and multi-agent ...

The .NET Isolated Worker Model allows developers to create Azure Functions using a .NET console app project that targets a supported .NET runtime. Compared to the in-process model, the Isolated Worker ...

Azure Blob Storage, like any object data service, is a high-value target for threat actors due to its critical role in storing and managing massive amounts of unstructured data at scale across diverse ...

At Microsoft Ignite 2024, the company unveiled a series of advancements that signify a strategic shift towards autonomous AI agents, aiming to enhance operational efficiency and productivity across ...

At Ignite 2024, Microsoft announced a new hybrid and edge computing platform branded as Azure Local. Built on the solid foundation of Azure Arc, Azure Local aims to bridge the gap between on-premises ...

At its annual Ignite conference, Microsoft on Tuesday announced the Azure AI Foundry, a new offering that brings together a number of Microsoft’s existing AI services for enterprises under a single ...

Microsoft on Tuesday revealed new custom chips aimed at powering workloads on its Azure cloud and bolstering security, particularly a new hardware accelerator that can manage data processing, ...

Microsoft’s Azure platform is a significant player in the cloud storage market. According to Microsoft figures, by the start of 2024, Azure storage clocked up more than 100 exabytes of data reads and ...

Abstract: Activation functions are pivotal in neural networks, determining the output of each neuron. Traditionally, functions like sigmoid and ReLU have been static and deterministic. However, the ...