Why Google Still Matters in AI
Google no longer owns the AI conversation by default, but it still controls some of the deepest infrastructure, distribution, and model-development advantages in the…
Plain-English reporting on AI, semiconductors, automation, robotics, compute, energy, and the future of work.
Google no longer owns the AI conversation by default, but it still controls some of the deepest infrastructure, distribution, and model-development advantages in the…
AI infrastructure is the physical and software stack that makes models usable at scale: chips, servers, networks, storage,…
Google is competing in AI by turning model development, product distribution, and custom silicon into one operating system….
A new wave of startups is attacking AI infrastructure from every layer of the stack, from networking and…
Google is competing in AI by combining frontier model development with an unmatched distribution layer across Search, Android, Cloud, and Workspace. That gives it…
AI models are only as good as the data streams feeding them. Data pipelines turn raw, messy information into training and inference fuel—and the…
OpenAI’s rise is not just a story about better models. It is a case study in how product decisions, training strategy, and compute access…
Large language models look like fluent software, but they are really prediction engines built on enormous datasets, vast compute budgets, and carefully tuned infrastructure….
A new class of startups is exploiting the gaps left by cloud giants and GPU incumbents. Their products reveal a market shifting from general-purpose…
Training gets the headlines, but inference is where AI turns into a product, a cost center, and a systems problem. Understanding it explains why…