Semantic Kernel is a model-agnostic SDK that empowers developers to build, orchestrate, and deploy AI agents and multi-agent systems. Whether you're building a simple chatbot or a complex multi-agent ...

Cybersecurity researchers have discovered two malicious packages in the Python Package Index (PyPI) repository that masquerade as spellcheckers but contain functionality to deliver a remote access ...

The North Korean threat actor known as Konni has been observed using PowerShell malware generated using artificial intelligence (AI) tools to target developers and engineering teams in the blockchain ...

Abstract: Semantic mapping aims to construct a 3D semantic representation of the environment, providing essential knowledge for robots operating in complex outdoor settings. While Bayesian Kernel ...

Abstract: Vision Transformer, with the distinctive architecture and self-attention mechanisms, had profoundly influenced the field of computer vision, establishing Transformer-based models as ...

Workflow is still at the heart of the new framework. Building on the strengths of the Semantic Kernel and AutoGen agent implementations, the new framework offers support for workflow orchestration and ...

AI agents are reshaping enterprise analytics, and AtScale, a leader in semantic layer solutions, is helping organizations navigate this shift from "ask-a-question BI chatbots" to autonomous agents ...

Microsoft’s multi-agent framework, AutoGen, acts as the backbone for many enterprise projects, particularly with the release of AutoGen v0.4 in January. However, the company aims to harmonize all of ...

A Main Router Agent is responsible for routing queries. Several specialized agents (screening, fundflow, counter, pivot, irregularities, file_chat, general) are wrapped with their own logic (token ...

In this tutorial, we build an advanced AI agent using Semantic Kernel combined with Google’s Gemini free model, and we run it seamlessly on Google Colab. We start by wiring Semantic Kernel plugins as ...