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In this brief demo of the Selector platform, a user interacts with Selector Copilot to explore behavior within their network infrastructure. They first look into the latency of their transit routers, revealing a regional issue. The user drills down into network topology information to further investigate the latency, where they access details about devices, interfaces, sites, and circuits. Selector Copilot is then leveraged to surface circuit errors. Notably, each visualization provided by Selector Copilot can be copied and pasted onto a dedicated dashboard.

An LLM differs from a function in that it takes output and imputes, or infers, a function and its arguments. We first consider how this process works within Selector for an English phrase converted to a query. We then step through the design of Selector's LLM, which relies on a base LLM trained with English phrases and SQL translation, then fine-tuned, on-premises, with customer-specific entities. In this way, each of Selector's deployments relies on an LLM tailored to the customer at hand.

AI is hot, but it seems that many companies are haphazardly slapping AI onto their products. Often, these new AI-enabled tools seem more like a solution in search of a problem than a useful product. So how should we be incorporating AI to truly benefit our customers?

Join us for an exciting live demo as we explore how AI can transform your DevOps workflow using Pieces and Civo. In this comprehensive walkthrough, we'll dive into deploying an open-source large language model on Kubernetes, setting up GPU clusters, and leveraging AI to streamline development tasks.