The following article originally appeared on Vanishing Gradients and is being republished here with the authors’ permission When an AI agent can explore a dataset, choose a modeling approach, run the analysis, and explain its findings, what should the data scientist do? Traditionally, data scientists chose each step and implemented much of the analysis themselves. […]

The buildings and physical infrastructure for a new hyperscale data-center region are complete. Power is live and redundant, the cooling loops are balanced, the network fabric is up, and tens of thousands of machines are racked, cabled, and reporting healthy. Every milestone on the construction schedule is closed. The region will not carry production traffic […]

I’ve been thinking about a gap in the way we discuss graphs in AI. Most of the conversation starts after the graph already exists. We talk about graph neural networks, GraphRAG, graph agents, and graph foundation models. We spend much less time on the step that determines what all of them can do: turning raw […]

To keep pace with modern business, data strategy is shifting toward more autonomous real-time systems that deliver intelligence at the moment decisions are made. Driven by agentic AI, modern data teams are moving beyond simply looking at what happened. Now they’re automating complex workflows that analyze what’s happening, anticipate what might happen next, and recommend […]