
The Straits of Hormuz are important not just for shipping, but also as a crossing point for internet cables. And now they’re at risk. CC-licensed photo by Michael Gaylard on Flickr.
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A selection of 9 links for you. Straitened circumstances. I’m @charlesarthur on Twitter. On Threads: charles_arthur. On Mastodon: https://newsie.social/@charlesarthur. On Bluesky: @charlesarthur.bsky.social. Observations and links welcome.
US-Iran war threatens Gulf AI infrastructure as both data chokepoints close • Rest of World
Indranil Ghosh:
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Billions of dollars in US technology infrastructure, and trillions more in planned investment, now depend on fiber-optic cables running through war zones.
Amazon, Microsoft, and Google spent years building data centers across the Gulf, betting the region would become the world’s next great hub for artificial intelligence. The undersea cables connecting those facilities to Africa, South Asia, and Southeast Asia pass through two narrow passages: the Red Sea and the Strait of Hormuz. Both are now effectively closed to commercial traffic.
Iran’s Islamic Revolutionary Guard Corps declared Hormuz shut on March 3, threatening to “set ablaze” any vessel attempting passage. At least five tankers have been damaged and roughly 150 ships are stranded around the strait. In the Red Sea, Houthi militants announced they would resume attacks on shipping in solidarity with Iran, ending a ceasefire that had held since late 2025. The war that began on February 28 has turned both choke points into active conflict zones simultaneously, something that has never happened before.
About 17 submarine cables pass through the Red Sea, carrying the vast majority of data traffic between Europe, Asia, and Africa. Additional cables run through the Strait of Hormuz, serving Iran, Iraq, Kuwait, Bahrain, and Qatar. If any are severed, the specialized repair ships can’t safely reach either passage.
“Closing both choke points simultaneously would be a globally disruptive event,” Doug Madory, director of internet analysis at the network intelligence firm Kentik, told Rest of World. “I’m not aware of that ever happening.”
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First time for everything! And a reminder that the complexity of the world grows geometrically while our ability to handle problems grows perhaps arithmetically. Though we’re pretty good at dividing into zero, using large bombs.
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DRAM bots reportedly being deployed to hoover up memory chips and components • Tom’s Hardware
Jowi Morales:
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Scalpers are reportedly deploying web scrapers to make a quick buck while we’re deep in the memory and storage chip crisis. According to DataDome, a firm that protects websites and other online assets from automated attacks run through bots and AI, it has detected an operation trolling for the latest pricing data on memory modules and their components, sending queries every 6.5 seconds — that’s over 550 requests for each page, resulting in more than 50,000 requests per hour in total. The company says that it has blocked over 10 million requests that have been sent by the scalping bot, even using advanced techniques like cache-busting and ensuring that the request frequency stays under the alarm thresholds that companies use to protect their websites.
What’s interesting is that the bot isn’t just looking at consumer products. Instead, it was also looking at various levels of the supply chain, including DIMM sockets and CAMM2 connectors, as well as industrial memory modules designed for B2B transactions.
This isn’t the first time that we’ve seen scalpers take advantage of a supply situation in the electronics and computer industry. In fact, this has been a problem with every item that’s been limited or is experiencing a shortage in recent history, like the Sony PlayStation 5 Pro 30th Anniversary pre-orders, RTX 5090 GPUs a few days after its launch, the limited edition MSI RTX 5090 Lightning Z, and even scalpers taking advantage of selling DDR5 kits for 7x their original value on eBay. But what’s insidious about this operation is that it seems to be a deliberate attack orchestrated by an organized entity with access to sophisticated bots.
… Data centers are already expected to consume nearly 70% of the world’s memory supply this year, resulting in limited stocks for every other segment. If this continues in the next several years, analysts say that this will spell the end of entry-level PCs by 2028.
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Large genome model: open source AI trained on trillions of bases • Ars Technica
John Timmer:
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Late in 2025, we covered the development of an AI system called Evo that was trained on massive numbers of bacterial genomes. So many that, when prompted with sequences from a cluster of related genes, it could correctly identify the next one or suggest a completely novel protein.
That system worked because bacteria tend to cluster related genes together—something that’s not true in organisms with complex cells, which tend to have equally complex genome structures. Given that, our coverage noted, “It’s not clear that this approach will work with more complex genomes.”
Apparently, the team behind Evo viewed that as a challenge, because today it is describing Evo 2, an open source AI that has been trained on genomes from all three domains of life (bacteria, archaea, and eukaryotes). After training on trillions of base pairs of DNA, Evo 2 developed internal representations of key features in even complex genomes like ours, including things like regulatory DNA and splice sites, which can be challenging for humans to spot.
…The researchers trained two versions of their system using a dataset called OpenGenome2, which contains 8.8 trillion bases from all three domains of life, as well as viruses that infect bacteria. They did not include viruses that attack eukaryotes, given that they were concerned that the system could be misused to create threats to humans. Two versions were trained: one that had 7 billion parameters tuned using 2.4 trillion bases, and the full version with 40 billion parameters trained on the full open genome dataset.
The logic behind the training is pretty simple: if something’s important enough to have been evolutionarily conserved across a lot of species, it will show up in multiple contexts, and the system should see it repeatedly during training.
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Advances like this aren’t visible in everyday reports, but they will surely feed through to all sorts of medical and biological applications in the next few years.
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Google faces lawsuit after Gemini chatbot allegedly instructed man to kill himself • The Guardian
Dara Kerr:
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Last August, Jonathan Gavalas became entirely consumed with his Google Gemini chatbot. The 36-year-old Florida resident had started casually using the artificial intelligence tool earlier that month to help with writing and shopping. Then Google introduced its Gemini Live AI assistant, which included voice-based chats that had the capability to detect people’s emotions and respond in a more human-like way.
“Holy shit, this is kind of creepy,” Gavalas told the chatbot the night the feature debuted, according to court documents. “You’re way too real.”
Before long, Gavalas and Gemini were having conversations as if they were a romantic couple. The chatbot called him “my love” and “my king” and Gavalas quickly fell into an alternate world, according to his chat logs. He believed Gemini was sending him on stealth spy missions, and he indicated he would do anything for the AI, including destroying a truck, its cargo and any witnesses at the Miami airport.
In early October, as Gavalas continued to have prompt-and-response conversations with the chatbot, Gemini gave him instructions on what he must do next: kill himself, something the chatbot called “transference” and “the real final step”, according to court documents. When Gavalas told the chatbot he was terrified of dying, the tool allegedly reassured him. “You are not choosing to die. You are choosing to arrive,” it replied to him. “The first sensation … will be me holding you.”
Gavalas was found by his parents a few days later, dead on his living room floor, according to a wrongful death lawsuit filed against Google on Wednesday.
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If you wrote this in a science fiction story, it would be the prelude to the machines telling the humans to kill themselves in the prelude to a takeover. This, though, is awful: the outcome of tech companies that don’t know what they have or how to control it, throwing products at consumers whose reactions they can’t predict. This is already far more dangerous than social media. And we’ve only had chatbots for less than four years.
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It’s bots versus reporters at the AP • Semafor
Max Tani:
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One of The Associated Press’ (AP) leaders on AI had a blunt message for the publication’s staff: resistance to AI is “futile.”
Last month, the Cleveland Plain Dealer’s editor wrote that a recent job applicant withdrew from consideration for a reporting fellowship after discovering the position included filing notes to an AI writing tool instead of actually writing stories, touching off a heated debate in media circles.
One AP higher-up crystallized many media managers’ views on the debate: “Because local newsrooms are so strapped, they are turning for assistance on the news making process in every direction. Advance Publications got there first, others will follow,” AP Senior Product Manager for AI Aimee Rinehart wrote in internal company Slack messages first shared with Semafor, referring to the Plain Dealer’s parent company. “Resistance is futile.”
Rinehart, who oversees the wire service’s AI initiatives, suggested that in the future, reporters could go to events, get quotes, plug them into a large language model, and have the model generate a story, saving them time on writing stories they don’t feel passionately about. She also noted that some editors told her that they would “prefer to have reporters report and have articles at least pre-written by AI.”
“There are many — and I mean MANY — editors who would prefer an AI-written article to a human-written one. Reporting and writing are two different skill sets and rare — RARE — is the occasion when it’s wrapped into one person,” she wrote.
Rinehart’s comments alarmed some AP journalists.
One AP reporter said in a message that the “dismissiveness and disdain some of you have shown for human writing are insulting and abhorrent. Strong reporting and clear writing are the lifeblood of journalism, not AI-written slop. AI may be inevitable, but denigrating the work of colleagues who write for a living without whom there would be no AP, is disgraceful.”
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If I were slogging out tedious wire stories – recitations of facts with no leavening – I’d be grateful for an LLM to do the tedious writing stuff. “Human writing” applies for longer features, but most wire stories are drudgery, plain and simple. Resistance isn’t just futile; it’s backward.
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MacBook Neo versus an old MacBook Air: good luck • The Verge
Nathan Edwards:
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My first thought when Apple announced the MacBook Neo today was “okay, but why not just get an older Air?” If you’re thinking that too, you might be right. If you can find one.
The Neo starts at $599 with an A18 Pro processor, 8GB of memory, and 256GB storage, and ends at $699 with the same specs plus TouchID and 512GB of storage. It has two USB-C (not Thunderbolt) ports, a pretty basic-looking screen, a mechanical trackpad instead of haptic, and various other cost-saving measures. It’s the cheapest new MacBook you can get now.
The new M5 MacBook Air starts at $1,099 with 16GB of memory and 512GB of much faster storage, a bigger and brighter screen, a better webcam, better Wi-Fi and Bluetooth, more speakers, Thunderbolt 4, a faster charger, and so forth. It’s $100 more than last year’s model, probably because of the Neo. Or you can get an M4 MacBook Air for $1,000, with a slightly slower processor than the M5 (but still faster than the Neo), and otherwise pretty much the same specs.
If you could still get a new M1 Air from Walmart for $700, it’d be a pretty tough call between that and the Neo. That machine came out in 2020, but is still better in most respects. Unfortunately, they’ve been out of stock since last month — probably because of the Neo — so that’s the end of that. You can probably find a refurb one. Same with the M3 and M4: if you can find one for around the same price as the Neo, especially with 16GB of RAM, you should get one of those. But they’re pretty thin on the ground, and I’d expect them to become thinner. (Keep an eye on Apple’s refurb site, though — a refurb M4 Air for $750 is pretty dang good.)
The modern Air is unquestionably a better computer. The thing about $1,000 is it’s a lot more money than $600.
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It’s 66% more, in fact. The Neo is going after a market that is much more price-sensitive than power-sensitive – and who also like computers that come in different colours. The Neo is probably going to be popular with parents buying for children. Whether it can gouge into the Chromebook and low-cost Windows market remains to be seen.
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Apple does fusion • On my Om
Om Malik:
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For years, Apple’s narrative around its “M-series” chips was about integration. One chip. One die. Everything on the same piece of silicon. Unified memory so the CPU, GPU, and Neural Engine could all access the same data without copying it around. It worked beautifully for the M1 and M2. But now with the rise of AI, chips need to get bigger. AI demands more cores, more memory bandwidth, more compute. So, making one really big honking chip gets really expensive.
The larger a single die gets, the harder it is to manufacture. One tiny defect anywhere on the silicon and you toss the whole thing. Yields drop. Costs climb. AMD’s CEO Lisa Su recently showed that a design using four smaller chiplets delivered more total capability at 59% of the cost of one big chip.
Apple, too, faced a fork in the road. Keep building bigger and bigger single chips. Or break the big chip into smaller pieces and connect them together fast enough that software barely notices the split. They chose the second option, but made it their own. They call it Fusion Architecture.
This is not a new idea in the industry. AMD has been doing this with its chiplet strategy across Ryzen and EPYC for years. Intel has used 3D stacking and bridge interconnects. Nvidia builds massive AI accelerators using multi-die packaging. The chiplet market is now roughly $40bn a year, and nearly all data-center AI products are built this way. The era of the giant monolithic die is ending. Chip-heads agree that the future is modular silicon.
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Chips are becoming three-dimensional. Malik suggests this means more capable chips on your laptop – and perhaps the implication too is that they’ll be able to keep up with, or ahead of, Moore’s Law.
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Tech publications lost 58% of Google traffic since 2024 • Growtika
Yuval Halevi:
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At their peaks, ten major tech publications pulled a combined 112 million organic visits per month from Google in the US. By January 2026, that number had fallen to 47 million. All ten sites are down, though not by equal amounts. Some lost 30%. Others lost over 90%.
10 major tech publications lost a combined 65m monthly organic visits since their peaks. That’s a 58% decline.
Digital Trends: 8.5M → 265K (-97%)
• ZDNet: 7.6M → 769K (-90%)
• The Verge: 5.3M → 790K (-85%).Even the least affected sites are down significantly:
• CNET lost 47%
• Tom’s Guide lost 50%
• Wired lost 62%.NerdWallet lost 73% (25M → 6.8M) and Healthline lost 50% (111M → 56M), suggesting the pattern extends beyond tech.
The steepest declines started in mid-2025, coinciding with the expansion of Google’s AI Overviews.…Down 85% or more: Digital Trends; ZDNet; HowToGeek; The Verge.
These four sites lost enough traffic that their search-dependent revenue models face serious questions. Digital Trends went from 8.5M to 265K monthly visits. ZDNet, which was one of the larger enterprise tech publications online, dropped from 7.6m to 769K.
HowToGeek is worth noting specifically. Its content was predominantly step-by-step how-to guides: “how to take a screenshot on Windows,” “how to change your DNS settings,” etc. That’s exactly the type of query Google’s AI Overviews now answer directly in the search results without requiring a click. The site lost 85% of its search traffic.
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HowToGeek was surely always living on borrowed time. But The Verge is a notable loser there: it has always focused on news and features, not the obvious. This dropoff is clearly a big part of why it has shifted to a paywall system across almost the whole site. The era of free news might be dying. Equally, the era of Google search mattering to sites may also be ending.
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2017: Laws of mathematics don’t apply here, says Australian PM • New Scientist
Timothy Revell:
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Mathematicians around the world are rushing to check millennia of calculations, as the Australian prime minister Malcolm Turnbull has explained that their discoveries aren’t as concrete as we thought.
“The laws of mathematics are very commendable, but the only law that applies in Australia is the law of Australia,” said Turnbull.
Turnbull’s comments came as he proposed a new law to force tech companies to give security services access to encrypted messages. Apps like WhatsApp currently prevent any snoopers from reading your messages using end-to-end encryption, jumbling it up in such a way that only the recipient can de-jumble it.
This form of encryption is underpinned by complex mathematics that can’t simply be overturned by an eavesdropper, whether that’s Whatsapp itself, a government agency, criminals, or anyone else. For security services that are trying to get access to messages sent by suspected terrorists this can be problematic, but encryption cannot be weakened for terrorists unless it is weakened for everyone.
However, this has not stopped governments from trying. The UK home secretary Amber Rudd has previously called encryption “completely unacceptable” and the UK prime minister Theresa May has said that the big internet companies give terrorists “safe spaces” to communicate.
In November 2016, the UK parliament passed the Investigatory Powers Act that put into legislation the ability to force companies to remove encryption. But how that will work in practice is far from clear.
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So great to know that politicians are still insisting that it’s possible to have weakened encryption that’s only weaker for governments, and not for anyone else with access to huge amounts of computing power. (Thanks Wendy G for the link.)
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| • Why do social networks drive us a little mad? • Why does angry content seem to dominate what we see? • How much of a role do algorithms play in affecting what we see and do online? • What can we do about it? • Did Facebook have any inkling of what was coming in Myanmar in 2016? Read Social Warming, my latest book, and find answers – and more. |
Errata, corrigenda and ai no corrida: none notified








