How a seminal 2017 paper by Google researchers laid the groundwork for the 2020s AI boom, causing a Silicon Valley frenzy not seen since the 1990s dot-com fever
it's chock full of historical perspective and excellent details RE the last several months of crazy— by @BradStone. https://twitter.com/... @scale_ai : “There are a lot of AI tourists pretending to be natives,” @alexandr_wang says. “Ultimately they're just selling vaporware.” Read more from @BradStone's opening essay in the AI issue of @BW https://www.bloomberg.com/... Alex Kantrowitz / @kantrowitz : “The young engineers and entrepreneurs flocking to Cerebral Valley and its environs weren't necessarily around to learn the painful lessons from the last cycle about the fickleness of trends and the risks of competing against the resource-rich tech giants” https://www.bloomberg.com/... Brad Stone / @bradstone : from the depths of layoffs, cratering valuations and doom loops... The AI hype cycle has produced a Silicon Valley frenzy not seen since the dot-com fever of the late 1990s. My opening essay for AI issue of @BW: https://www.bloomberg.com/... via @BW
Context & Ripple Effects
Brad Stone's opening essay for Bloomberg Businessweek's AI issue frames today's frenzy as the payoff to a long arc: the deep-learning pioneers who built momentum from 2012's ImageNet breakthrough set the stage for what a single 2017 Google research paper then industrialized into the boom now drawing founders and engineers to San Francisco.
The essay lands amid a crowded chorus of cycle-watching: Alexandr Wang calls out 'AI tourists' selling vaporware, Alex Kantrowitz worries the Cerebral Valley cohort never learned the last bubble's lessons, and the coverage already shows the froth in paychecks — senior AI and ML engineers commanding a 12% salary premium over non-AI peers.
First-order effects
- Startups crowding Cerebral Valley face immediate pressure to prove substance over hype, since Wang's 'vaporware' charge makes thin demos a reputational liability with customers and backers.
- Young founders without incumbent-scale resources must now compete directly against cash-rich tech giants — including Google itself, whose own paper seeded their products.
Second-order effects
- Investors burned by the last cycle have a fresh cautionary template: the COVID-era unicorn bubble that burst before the AI boom, detailed in Tiger Global's $12.7B 2021 fund reckoning, will shape how much runway tourists get this time.
- Talent pricing escalates further as every serious entrant bids for the scarce AI-specialist pool, widening the gap between funded natives and undercapitalized arrivals.
Third-order effects
- If the dot-com parallel holds, the current frenzy ends not with the technology but with a shakeout that separates durable builders from vaporware sellers — echoing how the last cycle's survivors defined Web 2.0.
- San Francisco's re-centering around an AI-dominated 'hard tech' culture, as the related coverage describes, suggests the post-shakeout Valley will be more sober and less perks-driven than either the dot-com or social-mobile eras.
The trend: Silicon Valley is replaying its classic boom-bust script — foundational research, tourist influx, insider skepticism — with the 2020s AI wave now at the stage where capital discipline decides which founders survive it.