Recent Posts
- Wall Street Priced the Wrong Risk in AI Financial Advice
- Why Most Private Banks’ Generative AI Pilots Will Fail Their First FINMA Review
- When the Compliance Department Designs Your AI Training, This Is What You Get
- Agent Washing in the Boardroom: The Vanity Metric
- What Google Images Taught a Room Full of CFA Charterholders About AI Bias
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AI & Avalanches: Surviving the Risks of Intelligence—Human and Artificial
From the slopes of freeriding to the high-stakes world of finance, discover why managing risk—and keeping a sharp, human perspective—matters more than ever as AI accelerates its takeover.
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Apertus: The Swiss Answer to AI’s Messy Ethics and Business Fails
Apertus, Switzerland’s open AI, offers transparency and compliance. But what does it mean for businesses in real terms?
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Lynn Raebsamen Joins Ray Dalio at the MENA Investment Congress
Lynn Raebsamen, CFA, joins Ray Dalio at MENA Investment Congress in Abu Dhabi, sparking sharp, witty insights on AI, markets, and human scale.
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The Great AI Bubble: Why 95% of AI Projects Deliver Illusory ROI
95% of AI projects fail to deliver ROI, fueling a bubble. But some real-world use cases prove AI can boost productivity and cut costs.
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When Robots Have Meltdowns: Google’s Chatbot Spirals into Midlife Crisis
“AI Mental Awareness Month” kicked off as Google’s Gemini chatbot spiraled into dramatic loops of self-criticism, exposing the strange crossroads where AI glitches meet the quirks of human language.
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AI Isn’t the Villain: The Real Reasons of the Entry-Level Job Drop
While headlines blame AI for driving Gen Z toward blue-collar jobs, the data reveals a more complex story of economic pragmatism over technological displacement.
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Betting Billions on AGI: Why Most VC Tech Dreams Crash
Billions burn chasing tech hype—flying cars, the metaverse, AGI. The truth: real breakthroughs are much less predictable. The question: what happens to your money?
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Why AGI Isn’t Coming Soon—And What’s Holding It Back
Despite grand promises and billion-dollar bets, AGI remains a distant dream held back by soaring energy demands, the need for human-labeled data, hardware setbacks, and the challenge of real-world understanding.
