The Atlantic has often included end of the year round up of interesting stories. In fact, my wife and I were just discussing one of these stories last night and indeed, found it amazing: a hawk has learned how to use a crosswalk as a tool in hunting prey. For subscribers like us, it’s a nice chance to check out the smaller stories we missed. Gift link below, it was number 18 on the Atlantic’s list.
The crossing signal—a loud, rhythmic click audible from at least half a block away—was more of a pre-attack cue, or so the hawk had realized, Dinets, a zoologist now at the University of Tennessee at Knoxville, told me. On weekday mornings, when pedestrians would activate the signal during rush hour, roughly 10 cars would usually be backed up down a side street. This jam turned out to be the perfect cover for a stealth attack: Once the cars had assembled, the bird would swoop down from its perch in a nearby tree, fly low to the ground along the line of vehicles, then veer abruptly into a residential yard, where a small flock of sparrows, doves, and starlings would often gather to eat crumbs—blissfully unaware of their impending doom.
The hawk had masterminded a strategy, Dinets told me: To pull off the attacks, the bird had to create a mental map of the neighborhood—and, maybe even more important, understand that the rhythmic ticktock of the crossing signal would prompt a pileup of cars long enough to facilitate its assaults. The hawk, in other words, appears to have learned to interpret a traffic signal and take advantage of it, in its quest to hunt. Which is, with all due respect, more impressive than how most humans use a pedestrian crosswalk.
I do a lot of scrolling through the display of videos that YouTube expects that I might want to watch. Many of them are just wrong. Many are sloppily researched. Most of them are titled in ways that greatly exaggerate the importance of the facts gathered in them. I suspect that many of them are put together by AI.
Because it’s all too probable that in a post-labor society the output of the cornucopia machines will belong entirely to the descendants of the original stockholders. Everyone else will be scavengers scrabbling through the ruins looking for rats to eat.
Well, more or less. RGB space is a pretty good approximation to the space of colors humans can actually see, but there are still some colors on the edges that can’t be accurately represented by RGB values. Or, to put it another way, you could assign RGB values to them, but some of the values would be negative.
It’s clear that AI is both drowning out and obscuring other stories about the wobbling American economy. That’s a concern. But even worse: What if AI’s promise for American business proves to be a mirage? What happens then?
The yawning gap between data-center expenditures and the rest of the economy has caused whispers of bubble to rise to a chorus. A growing number of financial and industry analysts have pointed out the enormous divergence between the historic investments in AI and the tech’s relatively modest revenues. For instance, according to The Information, OpenAI likely made $4 billion last year but lost $5 billion (making the idea of a $1 trillion IPO valuation that much more staggering). From July through September, Microsoft’s investments in OpenAI resulted in losses totaling more than $3 billion. For that same time period, Meta reported rapidly growing costs due to its AI investments, spooking investors and sending its stock down 9 percent….
The biggest lesson of the past two decades of Silicon Valley is that Meta, Amazon, and Google—and even the newer AI labs such as OpenAI—have remade our world and have become unfathomably rich for it, all while being mostly oblivious or uninterested in the fallout. They have chased growth and scale at all costs, and largely, they’ve won. The data-center build-out is the ultimate culmination of that chase: the pursuit of scale for scale itself. In all scenarios, the outcome seems only to be real, painful disruption for the rest of us.
But I wonder how your data and conclusions compare to the leadup to the dotcom bust? And, more importantly, how they compare to the boom that followed that bust.
The major difference with the current fever in infrastructure investment vs the dotcom bubble of 2000, is that in large part the companies funding it are among the most profitable companies in the world. And so far, there has not been indications of cracks in the business model of advertising that is both funding their investments, and their market capitalizations (along with so many massive companies people wouldn’t think about being in the advertising business).
But if AI does disrupt, or even break, the current advertising model, the shock to the economy and markets would be far greater than most could imagine.
I saw it on wikipedia. It’s a wonderful vibrant turquois-ish green. I would look marvelous in Olo. In better times, it would be a good color of the year. (The Pantone color of the year is white. I guess they’ve officially thrown in the towel.)
