If you can’t spot the sucker at the poker table, you’re the sucker. Also, if you think you can’t get phished, you’re the sucker.

I’ve been successfully scammed six times in my life. Each time, the scam relied on the confluence of several factors that yielded a fleeting moment of vulnerability that some scammer was able to exploit by being in the right place at the right time. I had to be lucky always, they only had to be lucky once.

Amid all the hype about artificial intelligence, quantum computers and advanced chipmaking — to say nothing of the mega-billion-dollar investments— is it possible that the United States still isn’t doing enough to maximize computers’ potential?

As Congress scrambles to put together a budget deal, some tech experts are worried about the ability of modern hardware to keep up with the demands of powerful AI tools — and arguing that government has a bigger role to play in keeping American computing globally competitive.

“Other countries are moving quickly, and without a national strategy, the U.S. risks falling behind,” wrote veteran computer scientist Jack Dongarra of the University of Tennessee in an essay published today by The Conversation. Citing the success of efforts like Europe’s EuroHPC program and Japan’s Fugaku supercomputer, Dongarra argues that “a U.S. national strategy should include funding new machines and training for people to use them,” as well as “partnerships with universities, national labs and private companies.”

This might seem almost deliberately contrarian in an age of radical research cuts, but President Donald Trump’s proposed budget actually maintains current spending levels for support of artificial intelligence, quantum computing and high-performance computing. Historically, at that, the U.S. has shown a willingness to make significant investments in what’s broadly known as “high-performance computing,” or supercomputers that often use millions of processors in concert to execute operations at lightning speed.

Something’s very different in tech. Once upon a time, every bad choice by tech companies — taking away features, locking out mods or plugins, nerfing the API — was countered, nearly instantaneously, by someone writing a program that overrode that choice.

Bad clients would be muscled aside by third-party clients. Locked bootloaders would be hacked and replaced. Code that confirmed you were using OEM parts, consumables or adapters would be found and nuked from orbit. Weak APIs would be replaced with muscular, unofficial APIs built out of unstoppable scrapers running on headless machines in some data-center. Every time some tech company erected a 10-foot enshittifying fence, someone would show up with an 11-foot disenshittifying ladder.

Those 11-foot ladders represented the power of interoperability, the inescapable bounty of the Turing-complete, universal von Neumann machine, which, by definition, is capable of running every valid program. Specifically, they represented the power of adversarial interoperability — when someone modifies a technology against its manufacturer’s wishes. Adversarial interoperability is the origin story of today’s tech giants, from Microsoft to Apple to Google:

https://www.eff.org/deeplinks/2019/10/adversarial-interoperability

“Understood: Who Broke the Internet?” is my new podcast for CBC about the enshittogenic policy decisions that gave rise to enshittification. Episode two just dropped: “ctrl-ctrl-ctrl”:

https://www.cbc.ca/listen/cbc-podcasts/1353-the-naked-emperor/episode/16145640-ctrl-ctrl-ctrl

The thesis of the show is straightforward: the internet wasn’t killed by ideological failings like “greed,” nor by economic concepts like “network effects,” nor by some cyclic force of history that drives towards “re-intermediation.” Rather, all of these things were able to conquer the open, wild, creative internet because of policies that meant that companies that yielded to greed were able to harness network effects in order to re-intermediate the internet.

My enshittification work starts with the symptoms of enshittification, the procession of pathological changes we can observe as platform users and sellers...

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As a working artist in his third decade of professional life, I’ve concluded that the point of art is to take a big, numinous, irreducible feeling that fills the artist’s mind, and attempt to infuse that feeling into some artistic vessel — a book, a painting, a song, a dance, a sculpture, etc — in the hopes that this work will cause a loose facsimile of that numinous, irreducible feeling to manifest in someone else’s mind.

Art, in other words, is an act of communication — and there you have the problem with AI art. 

For years, the U.S.- Saudi Arabia relationship revolved around oil and defense. But this week’s state visit by President Donald Trump to Riyadh strongly signals a pivot to technology, as the regions find common ground not in petroleum, but in rich wells of investment capital.

Trump’s visit included an aerial escort by Saudi F-16 planes and a ceremony in the opulent Saudi Royal Court. And it was attended by a who’s-who of AI’s high priests, including Nvidia CEO Jensen Huang, OpenAI CEO Sam Altman, Tesla CEO and “first buddy” Elon Musk, as well as leaders of Amazon, Google, Uber, Palantir and others. (There was also Boeing, Halliburton and plenty of banks — the world hasn’t completely changed.)

As the visit unfolded, the companies seemed to vie with each other in an avalanche of massive tech announcements.