There's a DGX Spark sitting in my home office running OpenClaw. It's connected to my phone and my laptop through secure tunnels, and it has become, without exaggeration, the operating system for how my family runs. My wife and I use it to plan our
Today, Cisco launched the LLM Security Leaderboard, a comprehensive resource for evaluating model risk and susceptibility to adversarial attacks. By providing transparent, adversarial evaluation signals, this leaderboard contextualizes model
When we launched Cisco AI Defense early last year, it marked a major milestone in our greater mission to enable secure AI adoption. It was the industry’s first comprehensive AI security solution, offering centralized visibility into AI assets, robust
Before we can understand how AI changes the security landscape, we need to understand what data protection means in enterprise contexts. This is not compliance. This is architecture. Enterprise data security rests on the principle that data has a
How can network engineers approach AI in a sensible manner? Here's how you can maintain a balanced, realistic perspective on AI's capabilities and limitations.
For technical practitioners, responsible, secure, strategic AI adoption starts with the AITECH Learning Path and Certification.
Enterprise Autonomous Agents: Powered by NVIDIA’s Open Source AI Runtime and Secured by Cisco AI Defense OpenClaw showed the world how autonomous, self-evolving agents are a step-change in how software works. Yet, in the enterprise, this type of
From Search on the Web to Search in the IDE Last year we launched AI-driven semantic search for Meraki API docs on developer.cisco.com—but developers live in their IDEs, not the browser. Without the right context, AI assistants in the IDE fall back to
Prompt injections and jailbreaks remain a major concern for AI security, and for good reason: models remain susceptible to users tricking models into doing or saying things like bypassing guardrails or leaking system prompts. But AI deployments don’t
