History is littered with similar stories. The South Sea Bubble of 1720 operated more like a modern scam than genuine commerce, wiping out fortunes—including that of Benjamin Franklin. The railway mania of the 19th century saw investors frantically pour money into rail companies, fuelling massive construction across Britain and America. While some railroads did revolutionise transport and commerce, many were speculative ventures lacking realistic returns. By mid-century, overinvestment led to numerous bankruptcies and financial crises, echoing earlier bubbles.

Fast forward to the the 2010s startup bubble, boosted by virtual reality’s perpetual ’imminent breakthrough,’ demonstrated how these cycles continue to evolve. Meanwhile, climate hysteria has provided its own variant: fear-based hype, perhaps more effective precisely because it leverages anxiety rather than optimism.

Most modern hypes exploit psychological quirks. ’FOMO’—the fear of missing out—and nostalgia drive consumers, especially as they grapple with disappointment. After all, when nothing ever matches your first experience, satisfaction inevitably fades. Social media’s dopamine loops compound the issue: likes, videos, and memes are empty calories, prompting an endless scroll driven by hope, without ever giving fulfillment. For those participating in the hype economy the redefinition of work - detached from classical definitions of the production of added value, yet amounting to little more than toil - has come full circle. Freed from the shackles of productivity of old, subjects of the hype have become enslaved to the rules of a concept that they hoped would set them free.

Like it or not, hype remains an excellent monetisation strategy. Its sensitivity to narrative shifts makes markets volatile yet profitable. Consider Goldman Sachs’ 2024 report claiming declining ChatGPT user numbers, triggering an immediate stock plunge. Yet when subsequent reports indicated annual growth overall, stability quickly returned. Investors were betting on narratives, not facts.

Real-world Ripples

Obscure examples from tech bubbles illustrate the tangible power of hype. Dogecoin languished unnoticed until Elon Musk's tweets suddenly thrust it into the spotlight. From fractions of a cent, Dogecoin soared to an $80 billion market cap by May 2021, only to crash soon after. Trump's return to office briefly resuscitated it, but it was Musk's appointment as the head of DOGE that truly gave the meme coin another short-lived spike, vividly demonstrating not only the fickle nature of hypes, but also the intrinsic dependence of cryptocurrencies on narratives and myths - rather than technology and code.

Not all hype cycles are rollercoasters. ChatGPT became history’s fastest-growing consumer app, reaching 100 million users within two months. McKinsey subsequently estimated generative AI’s potential market value at $4.4 trillion—more than Britain's GDP. Morgan Stanley upped the ante, predicting a $6 trillion market.

With the hype around renewable energy fully exhausted, AI emerged as the new darling of investors, drawing the financial caravan toward greener pastures. Just like the climate catastrophe, the much-feared AI singularity always seems to be just six months away. Yet the outcomes for end-users remain sobering. Hardware shortages, enormous energy consumption, hallucinations, and ’AI inbreeding’ highlight that, beyond flashy tech demos, the path to widespread and practical AI use remains rocky and steep.Harvard researchers David Gray Widder and Mar Hicks wrote in a late 2024 report, that “in many cases, LLMs fail to automate the labor that CEOs confidently claimed they could, and instead often decrease employee productivity.”

Those familiar with hype cycles weren’t surprised when advisory group Gartner's late 2024 ’Hype Cycle’ placed generative AI firmly past the ’peak of inflated expectations,’ hurtling towards the ’trough of disillusionment.’ Comparing current AI hopes to the internet’s early days reveals a stark contrast between lofty aspirations and reality: from open knowledge sharing to online trolling and endless pornography. AI risks a similar fate: instead of ushering in a singularity, it may become a singularly efficient tool for meme creation and OnlyFans content. At least that's reliably profitable.

The Hangover Effect

Yet hype cycles aren’t just faster; they're also more consequential. Decades of green energy fixation triggered energy shortages in Western economies. Now, sprawling AI data centres fuel unprecedented hardware and energetic demands, likely lingering long after AI enthusiasm wanes. Hype doesn’t just create temporary bubbles—it shapes lasting dependencies.

Missed the AI boom? Maybe it’s time to invest in cheap energy. Whether or not it becomes the next hype, demand is guaranteed to keep climbing. Hypes, however, are here to stay and have real market power. Not all of them turn out to be bubbles, but they do play by the rules of narratives. And he who controls the narrative, controls the hype.

Statement

Hype is now the currency of modern economies, driving investors and consumers from bubble to bubble, from Dutch tulips to Dogecoin and AI. As anticipation replaces reality, markets become volatile, inflated by FOMO, nostalgia, and endless narratives. But beneath the excitement lies a troubling truth: expectations rarely align with outcomes. Today's generative AI craze mirrors past cycles—promising revolutionary change yet risking a descent into trivial uses. These rapid hype cycles aren't merely speculative; they create lasting dependencies and disruptions, leaving societies vulnerable when enthusiasm inevitably fades. The real risk isn’t missing the next trend but surviving the aftermath when attention shifts again.