Tracks vs. Trains: Why the Real Artificial Intelligence Boom Hasn’t Started Yet – Insights for 2026

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Read Time:19 Minute, 24 Second

1. Introduction: The Two Economies of Artificial Intelligence

The global artificial intelligence ecosystem stands at a definitive historical precipice as the calendar turns to 2026. For the past three years, the market has been dominated by a singular, overwhelming narrative: the frantic, capital-intensive construction of the physical and digital infrastructure required to birth machine intelligence. This period, characterized by the breathless accumulation of graphics processing units (GPUs), the groundbreaking of gigawatt-scale data centers, and the training of ever-larger foundation models, has generated trillions of dollars in paper wealth and fundamentally reshaped the capital expenditure profiles of the world’s largest corporations. However, a nuanced analysis of market dynamics, historical precedent, and emerging economic data suggests that this initial phase—the “Installation Phase”—is rapidly approaching its saturation point. We are witnessing a decoupling, a bifurcation of the AI economy into two distinct trajectories with inversely correlated fortunes: a saturating infrastructure layer facing deflationary pressures and margin compression, and a nascent application layer poised for a “Golden Age” of value creation. read more

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Digital Inbreeding: What Happens When AI Runs Out of “Surprise”?

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Read Time:4 Minute, 16 Second

We are living through a massive experiment in information dynamics, and I’m starting to worry about the results.

Initially, Large Language Models (LLMs) were trained on the “wild” internet—a chaotic, messy, and deeply human repository of text. It was a library written by people. But today, the internet is fundamentally changing. More and more of the content we consume (and that future models will train on) is heavily influenced, if not completely generated, by AI. read more

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12 Places To Intervene In A System, To Drive Systemic Change

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12 Places To Intervene In A System, To Drive Systemic ChamgeAfter reading quite a few books on systemic racism. I was compelled to find a book on discipline of Systems Thinking. I found "Thinking in Systems" by Donella Meadows to be a highly read and rated choice on the topic. Given the complex nature of systemic racism and racist actions, how do you tackle it. I believe systems thinking can provide a framework for doing just that. Given that we can’t just change a system directly, in "Thinking in Systems," Donella Meadows outlined a list of interventions you can lever to influence the system. She sorts the leverage points in increasing order of effectiveness, from the easiest to lever/least long term impact on the system; to the hardest to lever/most effective to long term impact on the system.   The easiest and least effective is effecting Numbers (e.g. effecting #'s and %'s); the hardest and most effective is Transcending Paradigms (which is almost spiritual), but 2nd to the hardest/most impactful is Paradigms (i.e. changing the societal culture around how we consider each other). I think racism needs to be attacked from the top and bottom, that is starting with Numbers AND Paradigms; converging where they do.

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Quick Take: The Great Decoupling of Retail

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Read Time:47 Second

There is a great decoupling happening in retail, a structural change. Similar to the decoupling that the computing industry went through, going from being vertically integrated to horizontal specialist. What does this mean for retailers? Retailers need to be clear on what their unique selling proposition is, that is why do customers choose them vs their competitor, or substitute; then double down on those things. Is it your wide assortment, price, convenience, customer service, maybe safety now, or some thing less rational. Everything else should be considered for outsourcing to horizontal specialist, those who are optimized to delivery a particular service, or product. read more

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