Artificial intelligence is often said to be grown, not built. The phrase, often attributed to thinkers in AI safety circles, captures the idea that modern AI systems are not engineered like traditional software. They are cultivated through data and experience, shaped by feedback, and refined through countless iterations until patterns begin to emerge. AI did… Read More »
If someone walked you through what they did to “create an AI,” you might be surprised, or even a little disappointed, by how simple it actually was to bring it to life. AI coding often sounds far more mysterious than it really is. When people hear “AI development,” they tend to imagine complex systems being… Read More »
Traditional SIEMs follow a predictable model: collect logs from many sources, ingest them into a central store, normalize them into a readable schema, index them, and then use queries, dashboards, and alerts to investigate and respond. This design exists because data is scattered, inconsistent, and hard to retrieve. Centralization solves those problems but introduces challenges… Read More »