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Applied AI·August 7, 2026·1 min read

Why AI infrastructure planning must happen now

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The argument for early, balanced, open AI infrastructure is really about avoiding three-year technical debt — proprietary traps, bandwidth ceilings, and GPU bottlenecks. This week, map where your data, models, and orchestration actually live and which vendors control each layer before you greenlight the next AI initiative.

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'Great music is made by people' — Suno, the biggest AI music company, is finally trying to solve a problem its own success helped create

When the largest AI music platform starts talking about putting the brakes on its own output, it’s a signal that pure volume has outrun both user experience and rights frameworks. Any AI content platform at scale will need active curation, provenance, and economic rules — not just better models — to stay viable with creators and regulators.

Applied AI

Analysis: Google DeepMind has lost frontier-model momentum amid leadership and RL talent departures, with Google Cloud emerging as a winner with more compute

If frontier-model leadership is fragmenting while Google Cloud’s AI revenue grows >100% YoY, the center of gravity is shifting from pure research to monetized infra and services. For buyers, that means more leverage to negotiate integrated compute + model + tooling bundles — but also more lock-in pressure as cloud becomes the AI control plane.