Posts tagged #ai

AI strategy advice is dangerous when organizations cannot tell fluent abstraction from earned judgment.

The same philosophical claim that justified building AI—patterns matter, not substrate—also explains why using it badly might hollow you out.

AI hasn't just made it easier to spread false information — it's broken the mechanism that truth uses to correct it.

AI has outpaced the instruments we use to evaluate it — and the institutional response of harder benchmarks and more metrics makes the problem worse.

Google's Gemini Embedding 2 is being covered as a RAG upgrade. The more important change is who can now build surveillance infrastructure.

Grammarly attached Casey Newton's name to AI-generated feedback without asking. The real story isn't about consent — it's that expertise is now technically separable from the person who built it.

Most knowledge workers are calibrated to an AI tool that no longer exists, and the research meant to measure the gap is structurally blind to the people who'd prove it.

Agentic AI deployments are stalling not because models are inadequate, but because the foundational data work that makes them usable doesn't demo, doesn't get funded, and won't until failure accumulates enough to force it.

The defining strategic move in AI right now isn't building better models — it's escaping your own supply chain before your supplier becomes your competitor.

Prediction markets — with real money on the line — are already pricing in a messier, more distributed AGI outcome. The finish line is a story we tell.