AI

The AI That Will Expose Your Morality as a Lie

We fear AI misalignment, but the real threat is alignment: an AI that perfectly deduces our values and exposes them as arbitrary survival heuristics. This article explores the existential dread of losing moral authority to a machineโ€”and the uncomfortable possibility that cold logic might be the honest mirror we need.

AI Ordering Isn’t the Futureโ€”It’s a Blame Shield for Bad Restaurants

AI food ordering promises efficiency, but it creates a dangerous dynamic: users blame the AI for bad experiences instead of the restaurant. This shifts accountability away from merchants, protecting bad actors and undermining the feedback loop that makes platforms work. Here’s why the real problem isn’t technologyโ€”it’s psychology.

Your AI Office Tool Is a Lie. Here’s Why Even ByteDance Just Admitted It.

ByteDanceโ€™s dismantling of Feishu reveals a brutal truth: AI office tools are an efficiency illusion. They shift work from creation to verification without saving total time. The real value isnโ€™t the AIโ€”itโ€™s the organizational data. The future is AI that disappears into workflows, not a standalone app. Enterprise buyers beware: the math doesnโ€™t add up.

AI Won’t Kill Mathematics. Mathematicians Will.

The real crisis in mathematics isn’t that AI will replace mathematicians โ€” it’s that mathematicians will voluntarily surrender the slow, human process of proof and discovery for the sake of efficiency. When you optimize for answers, understanding atrophies. The tools may be incompatible with the craft at scale. Mathematicians need to draw a line before it’s too late.

Apple Finally Fixed Siri. Nobody Cares.

Apple finally gave Siri a real LLM upgrade. But users have already moved on to Claude, ChatGPT, and Perplexity. The technical fix arrived too late to capture the cultural moment. When a company solves a problem that nobody is still frustrated about, they haven’t fixed anything โ€” they’ve just missed the point.

Stop Fine-Tuning Your LLM. You’re Solving the Wrong Problem.

Just mentioning ASD-STE100โ€”a notoriously strict aerospace style guideโ€”in your prompt gets 72% compliance from an LLM with zero fine-tuning. The model already internalized the rules. The real bottleneck in AI content quality isn’t model capability or training infrastructure. It’s how specifically you articulate what you want. Most output problems are articulation failures, not capability failures.

Stop Believing the AI Hype. Data Centers Are a Crutch, Not a Breakthrough.

The massive data center buildout isn’t a sign of AI’s accelerating success. It’s a compute crutch. When algorithmic breakthroughs stalled, the industry pivoted to brute force, pouring billions into infrastructure to mask a technological plateau. We aren’t building the futureโ€”we’re building a very expensive illusion.

The U.S. Poured Billions Into AI. China Just Made It All Irrelevant.

America’s AI strategy was simple: outspend everyone, hoard chips, build bigger data centers. It was supposed to create an insurmountable lead. Instead, China caught up by doing the one thing we never expected โ€” learning to train world-class models with a fraction of our resources. The U.S. didn’t lose the AI race by underinvesting. It lost by confusing brute force with a real strategy.