Latest Blog
LFM2.5-24B-A2B Explained: What Total and Active Parameters Mean for Local AI Agents
LFM2.5-24B-A2B combines 24B total and 2B active parameters. Understand memory, agent tooling, local execution, and how a NAS fits the workflow.
IBM Granite Speech 5.0 Explained: What Compact ASR Means for Private Audio Archives
Granite Speech 5.0 TurboCTC is a compact ASR model with a multilingual update. Learn how local transcription can fit a NAS-backed audio archive.
Claude Duet Explained: Proactive Tasks, Connected Apps, and Personal Files
Claude Duet is a proactive-agent research preview. Learn about background tasks, connected accounts, review boundaries, and NAS-backed personal files.
GitHub Agentic Autofix Explained: From Security Alerts to Reviewable Pull Requests
GitHub Agentic Autofix turns eligible code-scanning alerts into draft pull requests. Learn what it validates and what still needs review before deployment.
GitHub AI Scan Explained: Security Checks for PHP, Shell, and Docker Projects
GitHub AI Scan adds advisory PR security findings for PHP, Shell, and Dockerfiles. Understand coverage, limitations, and the home-server deployment gap.
Reflection Beam 1.0 Explained: Open Weights, Coding Agents, and Deployment Choices
Reflection Beam 1.0 is an open-weight coding model. Understand total versus active parameters, deployment choices, and why NAS storage is a separate layer.
Mercury 3 Explained: Why Diffusion Language Models Matter for Fast AI Workflows
Mercury 3 uses diffusion language modeling for fast text generation. Learn what its speed claims mean for tool-driven agents and NAS-backed workflows.
MiniMax M3.1 Flash Explained: Coding, Computer Use, and Agent Workflows
MiniMax M3.1 Flash targets coding and computer-use agents. Understand the claims, API access, evaluation criteria, and boundaries for NAS workflows.
