The Hidden Factory Behind AI: Why Data Pipelines Now Matter as Much as Models
AI systems are only as useful as the data that reaches them, and that data rarely arrives in a clean, ready-to-train state. Data pipelines…
Plain-English reporting on AI, semiconductors, automation, robotics, compute, energy, and the future of work.
AI systems are only as useful as the data that reaches them, and that data rarely arrives in a clean, ready-to-train state. Data pipelines…
A new class of startups is not just selling AI infrastructure; it is exposing where the market is…
Cloud computing looks intangible from the outside, but every request rides on a stack of servers, networking gear,…
Google is no longer the only company that matters in AI, but it still occupies a uniquely powerful…
Google is not trying to win the AI market with a single product. It is competing by controlling the stack: models, chips, cloud infrastructure,…
Training models gets the headlines, but inference is where AI becomes a product, a cost center, and a competitive advantage. For chips, data centers,…
AI performance is often discussed in terms of bigger models and faster chips, but the real bottleneck is usually upstream: the data pipeline. In…
Large language models are often described as if they were magical text engines. In reality, they are expensive statistical systems built on enormous compute,…
A new generation of startups is attacking AI infrastructure from the bottom up—rebuilding the stack around utilization, latency, and power density instead of raw…
OpenAI’s approach to building and deploying frontier models shows that AI leadership is no longer just about smarter architectures. It is also about securing…