Google and Its Vast Compute: Maybe Not So Vast?
July 6, 2026
Google and Meta are rivals. They are always trying to advance themselves so one can out do the other. Google has finally been able to do that with their Gemini AI says The Next Web in the article, “Google Is Rationing Gemini Access To Meta Because It Cannot Provide Enough Compute.” In short, Meta wants to leverage Gemini, but Google has placed caps on the social media company’s usage. Google has placed caps on other companies’ Gemini usage as well.
Meta is not happy. Zuckerberg’s company told its staff to be more efficient with Gemini tokens. Meta used Gemini, because it was a better algorithm than its Llama open source model to automate safety processes. They have also shifted work over to Muse Spark to reduce dependence on external AI sources. Here is more information about what is going on behind the scenes with AI:
“Google itself is so compute-constrained that it agreed to pay SpaceX $920 million a month for access to 110,000 Nvidia GPUs, calling it “bridge capacity” to meet surging demand for Gemini Enterprise. The situation illustrates how the AI compute shortage is reshaping relationships between the industry’s largest companies. Google, which owns one of the world’s largest pools of AI infrastructure and is spending over $180 billion on capex this year, still cannot serve all of its customers’ demand. That it is rationing access to a company as large as Meta, while simultaneously renting GPUs from a rocket company, is the clearest signal yet that AI infrastructure buildouts have not kept pace with consumption.”
Meta doesn’t like replying on a competitor. In order to cut reliance on Google, they axed 8,000 jobs in May and redirected funds towards AI infrastructure. Another 7,000 employees were shifted to AI-related roles to build Muse Spark.
There’s a big demand:
“The broader pattern is consistent across the industry. Demand for AI compute is growing faster than even the most aggressive infrastructure spending can supply. Google is buying capacity from SpaceX. Anthropic is renting an entire data centre from SpaceX. Meta is being told to use fewer tokens by its own cloud provider. The AI boom’s most tangible bottleneck is not algorithms or talent. It is the physical infrastructure required to run them.”
In the last few days, we’ve Gemini output regress to “glue cheese on your pizza” and statements like “I can’t locate that information.” Google’s vast compute resources seem to be suffering from hyperbole or summer heat sickness.
Whitney Grace, July 6, 2026
If an LLM Falls in a Company, Does the CFO Know?
July 3, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
The title of this essay in Shift Mag intrigued me: “CTOs Agree: Cognitive Debt Is the New Technical Debt.” Since technical debt is a bit abstract for the accountants, lawyers, Wall Street wolves, and their genetically-related bros — now there is a new “debt” about which a “leadership type” can fret. Unlike technical debt which is easily ignored, the cognitive debt may come with an invoice.
The write up captures this new debt with this headline-scale statement:
The CFO has no control once they’ve signed the contract over what the actual investment is going to be. And if you can’t tell me the investment, what does projected return even mean?
The context for this statement is smart software that cranks out code, engineering solutions to problems, or legal mumbo jumbo complete with made-up citations. But that software in most cases comes with a subscription or a license. Instead of a fixed annual amount or an agreed upon monthly fee, the cost of an LLM is a “token.” This is not an old fashioned New York subway token that leaves one fingers grimy with Hantavirus-related goodies, this token is notional. It is not a thing; it is part of the taxi meter pricing scheme that BAIT (big AI tech) outfits have embraced in a somewhat interesting decision to try and stop tossing cash into a blazing dumpsters behind an Ollie’s discount store and data center.
The rhetorical question in the quote is going to be difficult for the BAIT outfits, the blue chip consulting firms with slogans like “We’re AI experts,” and the customers themselves to answer. The write up makes another interesting statement:
…organizations that bought the tools, signed the contracts, and then realized there’s no financial model inside the company to manage what comes next
Okay, no big surprise. Technology. The alleged next big thing. Everyone is doing it. Figure it out.
How’s that working out?
The write up reports:
The more pragmatic response, shared by more than one team: stop the free-for-all, start standardizing. This doesn’t mean we’re telling people to use AI less, but nudging from “use everything” to “use the same things, smarter.”
What are engineers doing to stay ahead of cognitive debt? Actually not much. The write up says:
The most interesting take came from someone who’d shifted their interviews toward code review rather than coding, precisely because that’s what engineers actually do now. I changed our interview process to focus on code review, because that’s what we’re actually doing. And implementation is now AI-assisted, however you choose to use your agents. If your team can generate code faster than it can review it, you have a bottleneck. The constraint is human judgment, not output.
Where does informed judgment originate? Yeah, no answer.
The article does bring up a human question that smart software has not yet de-hallucinated; to wit:
One company ran an anonymous survey and found 90% of engineers at that organization actually want to use AI, higher than expected. What surprised him wasn’t the enthusiasm but what came next: questions about performance management, about promotion criteria, about how individual contribution gets recognized when anyone can now generate code. The adoption had outrun the enablement.
My hunch is that once some metrics are slapped on AI code generation and the code is “good enough,” the human engineers or at least most of them will be given an opportunity to find their future elsewhere.
Thus, the problem:
Cognitive debt is the new technical debt. The room [the AI coders participating in the research session] had seen the same pattern: teams adding features at a pace that would have been impossible two years ago, now dealing with the maintenance overhead that comes with it. Legacy code that was already hard to understand is now harder, because the people who wrote it aren’t being careful. They’re being fast. And internal tools that were never meant to be permanent are now permanent because someone shipped them with three prompts.
Do those wild and crazy leadership people understand what problems the code may toss up in the future? Nope. Leadership thinks about staying out of the weeds, not getting in the weeds.
With the cost of verifying AI generated code looking like a significant expense, the write up says:
One practical suggestion that came out of this: invest in evals now, not later. The cost of building AI features isn’t the hard part. The cost of verification is. If you build a solid eval suite today, you can swap providers, survive model deprecations, or move to open source without starting from scratch.
That sounds great, but to leadership who want to invest in AI in order to reduce costs and add efficiency, spending an unknown about of money on institutionalizing human code reviews means one thing: Let AI do it.
For me, we have now surface the AI problem: Code is cheap. It may be okay, but someone with “judgment” should check it out and fix an error if one is spotted. But as more code is generated, can AI check itself? Can an organization figure out how to tap into humans with the requisite skill set? Dumping expensive engineers is easy. Spending an unknown amount to make sure the code does what someone hopes it will do is another form of taxi meter pricing. It seems to me that technical debt increases as cognitive debt rises as well.
What’s the fix? How about this concluding statement from the essay?
The practical advice: build internal UI wrappers over generic model APIs now, before your teams are locked into specific product interfaces. It’s cheap to do, and it means you can swap the model underneath without rebuilding the interface your teams depend on.
What?
Stephen E Arnold, July 3, 2026
It Is Waymo Fun When the Google Drives in Construction Zones
June 22, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
I have work stacked up. I am chasing down some interesting investments held by a high profile Web 3 outfit. I have to finish on of my upcoming lectures and move the “dots” slide. I have to visit the dog rescue facility. But I am making time to write about this allegedly spot on, dead accurate news article titled “Urgent Recall for 3,900 Robotaxis That Could Drive Passengers into Highway Construction Zones at High Speed.” Notice that the vehicle service with Googley software is not named in the headline. That’s okay. It was the water-fearing Waymo initiative from the world’s largest online ad service with AI outputs that a German court found responsible for what its smart software does. Yep, that outfit.
Thanks, Midjourney. Just good enough like so much AI outputs.
The news story which I assume to be accurate because I believe everything I read online says:
According to documents filed with the National Highway Traffic Safety Administration (NHTSA), more than a dozen incidents were recorded in California and Arizona since early April as Waymo vehicles failed to recognize highway ramp closure signs. As a result, the self-driving cars proceeded straight into construction areas and lanes where construction was underway. The company temporarily restricted highway driving for its robotaxis while engineers worked on a fix, and planned to roll out a software update designed to improve the vehicles’ ability to detect closed roads.
The write up helpfully provides some context about the Google Waymo engineering:
Waymo has launched a string of recalls over the past two years, including over concerns about how the cars detect poles and other objects along the road. Just weeks ago, Waymo recalled roughly 3,800 robotaxis over concerns they could enter flooded roads on high-speed routes. That decision was prompted by an April 20 incident in San Antonio, when a Waymo vehicle without any passengers drove into a flooded lane during severe weather.
Then a bit of history is added for a touch of color like those flashing yellow alarm lights:
Separately, the National Transportation Safety Board revealed it was investigating incidents in which Waymo vehicles illegally passed stopped school buses displaying flashing warning lights. The school bus issue had already triggered a separate recall by the company in December, adding to growing questions over whether self-driving technology is advancing faster than regulators can keep up.
I find the somewhat frightening information (if true) amusing. That’s because as a dinobaby I have a time-out-of-joint sense of humor; specifically:
- I thought the Google AI was able to do lots of great code and make Google products better like its search service. Note that the German judge would not agree with my taking Google smart output lightly. That “thought” of mine is demonstrably false. Hey, it’s just marketing, right?
- Google has been perfecting or semi-perfecting or hallucinating perfection for its Waymo technology since January 2009. My math, like other dinobaby functions, is not so good. But this 2009 to 2026 sure looks like slightly more than 17 years. And what do we have? The school bus thing. The water thing. The Cow Hollow cul de sac thing. The driving in construction zone thing. Are there other things that have not been given news coverage? Of course not. Google does not make errors most of the time. That’s the probability thing, of course.
- I continue to conflate Google’s push into smart eyewear with some of Google’s other interesting product and service demonstrations. Of the many projects Google has “invented” or acquired, many die on the vine or when the Googler pushing the skunky initiative loses interest, gets promoted, or becomes a Xoogler (that is, a former Google employee). The Waymo project has had legs, not the most robust pins on the playing field, but legs in terms of time: 17 years and counting.
Net net: I have to get back to real work. Thinking about Waymo was waymo time consuming than I thought. I had fun though. I know those riding at “high speed” (allegedly) will have the time of their lives until they don’t.
Stephen E Arnold, June 22, 2026
One AI Bottleneck Workaround: From the WEF No Less
June 5, 2026
The World Economic Forum discusses the barriers AI is finding when it comes to development: “AI Is Hitting A Wall. Here’s How We Rethink The Hardware To Break It.” When AI models grow larger that more time and energy needs to be spent moving data between memory and processors. It’s called “memory wall” and language-processing model grew 5,000 fold in size over four years.
Memory wall is a problem because large scale AI systems are increasing. This drives up costs and infrastructures. A second reason is that many valuable AI uses rely on fast decisions made locally instead of the cloud. Medical devices, autonomous vehicles, rescue drones, and more can’t rely on sharing information with data centers and waiting on responses. They need hardware that makes the AI more practical.
There are ways to overcome the AI memory wall bottleneck:
“…there are three main ways to ease this bottleneck: move computation closer to the data, draw on the brain’s event-driven information-processing method and use lower-precision or stochastic computing where exact arithmetic is unnecessary. Together, these approaches could support a new generation of AI hardware that is faster, more efficient and better suited to large-scale infrastructure and edge applications.”
These three options are the most powerful when they’re part of a single design solution. AI hardware that is designed in the future can’t rely on a single chip then fitting the algorithms on it as an afterthought. They need to be considered as part of the architecture during the design phase. Here’s what should be done:
“That is why hardware-algorithm co-design is becoming so important. Some workloads may benefit most from compute-in-memory; others may benefit from spiking networks and event-based sensing; and still others may rely on mixed-precision or stochastic methods. In many cases, the best solution may combine these approaches on the same platform. The larger implication is that the future of AI depends as much on hardware design as on model design. More efficient AI hardware could help contain the growing resource demands of large-scale systems while improving the safety and reliability of devices in the field.”
Interesting. But what if there is something other than the Google Transformer-centric method? The WEF will pivot, of course.
Whitney Grace, June 5, 2026
The AI – Catholic Church Issue
June 1, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
The New York Times published a short summary of five encyclicals. It is good to know that the NYT knows how to research the history of Papal actions. The story is paywalled, so paying, not praying, will reveal the truth. But the five encyclicals did not get to what I think is the crux of the matter or X marks the real spot.
Galileo Galilei makes it clear that he was very confused about the planets revolving around the sun and most of his other heretical thinking. House arrest made more sense to him than being burned at the stake. Thanks, Venice.ai. Good enough after three tries.
Not surprisingly, the Magnifica humanitas statement emphasizes guardrails, global regulation, and protection of humanoids. Anthropic’s “statement” was, and I summarize:
- Guardrails. Check
- Regulation. Check
- Protect humanoids. Check.
I interpreted the encyclical differently, probably because I worked on my graduate degree at Duquesne University (a Jesuit institution which like the idea of guardrails, regulation, and protection for humanoids. Believe it or not, I taught a couple of classes a requirement of my waived tuition, but I did get some money each month so I could enjoy a truly lavish lifestyle in Pittsburgh, Pennsylvania.)
The write ups about the encyclical did not talk about three interesting church actions. I will not talk about the Inquisition, but, please, keep that in mind if you doubt that the Catholic Church can take steps to clarify the thinking of certain of the church faithful.
I want to offer three examples of what happened when the tech bros did not line up with the Catholic Church.
First, Copernicus came up with the idea that lecturing and writing about his idea that the planets revolved around the sun deserved broad dissemination. The Church just grumbled but in 1616, that pot boiler De revolutionibus orbium coelestium was added to the Index of Forbidden Books.
Second, Galileo Galilei was into the Copernican concept. In 1633, he was tried by the Inquisition an found guilty. Galileo did the pragrmatic thing. He said, “I am sorry, very, very sorry.” The Church placed him under house arrest until he died.
The third example is one that calculus students don’t know much about. The Church determined that infinitesimals and by extension infinity bumped into Aristotelian philosophy. Those “teaching” about infinity were able to find jobs as farmers or buskers in Padua. Math bumped into this problem for decades until other issues pushed infinitesimals into an infinintely small segment of Catholic dogma.
My view of the encyclical about AI is, therefore, based on these historical actions. Thus, several observations can be offered:
- The Catholic Church can take direct and indirect action to suppress or cause information change
- Some of the methods tolerated by the Church involve indirect (house arrest) and direct (Iron maidens, heated fireplace pokers, etc.) to help individuals free their minds from certain thoughts
- The encyclical can spawn other statements that will be disseminated not by the Zuck-type or Telegram-type services. The message will be delivered to about 1.5 billion people. These indivdiuals with log on to the Zuck-type or Telegram-type services and comment about the Church message.
Net net: The Pope’s encyclical is a significant document and highly visible action. Additional communications and manifestations of the Pope’s guidance can be implemented with surprising ease and speed.
Stephen E Arnold, June 1, 2026
Is There More to Say about Waymo? Yep, Waymo
May 29, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
I don’t know if this story is actual factual. I really don’t care. I think it is hilarious and would make a wonderful Jack Benny TV show sketch. I wanted to run another Waymo folly story because a very earnest person commented about one of my previous tales of the self driving myth. The comments explained with appropriate jargon why certain types of sensors can be confused by rain. No problem. But it does rain, and it seems to me that in early 2009 a Googley wizard would have asked this question, “What if it rains?” Apparently no one did or no one had “time” to test the Googley self driving technology in inclement weather, heavy rain, water on a road, and lousy visibility for some types of sensors. I am probably incorrect, and I will be delighted when Googzilla once again corrects this cranky dinobaby.
An online “news” service published “Woman Trapped by Two Rogue Waymo Robotaxis for Nearly an Hour Calls 911: “Is the Officer Going to Argue With a Ghost?” The write up reports as actual factual:
Emily Offenkrantz did not wake up that morning expecting her biggest problem of the day to be two driverless cars. … a pair of Waymo robotaxis cut her off and then simply… stayed there…. Just two self-driving vehicles, parked in a digital standoff, while traffic piled up behind her and the minutes kept ticking.
Hey, thanks, Midjourney. Good enough.
The write up points out:
She eventually escaped not because the technology corrected itself in any graceful way, but because another driver helped guide her through a gap that opened when one of the Waymos unexpectedly reversed. It was less a resolution and more a lucky break.
Okay, Google.
The timing of this incident is notable. Around the same time Offenkrantz was playing automotive chess with two confused robotaxis, Waymo announced it was temporarily halting freeway operations across several U.S. markets. The reason: performance concerns related to construction zones.
Yeah, I assume in the 16 years of Waymo development road construction was not an issue. Orange cones and flashing lights are indeed a rare site on US 101 where self-driving cars were wished into reality.
The article adds:
In April, a Waymo in Los Angeles took a woman through a drive-thru the wrong way, leaving both her and bystanders in a state of bewildered amusement. A passenger in the vehicle was heard cheerfully narrating the chaos: “Way Way! You gotta go through the drive-thru the other way!”
I await a LinkedIn explanation. But I am still waiting for the magic cul de sac explanation in Cow Hollow.
Stephen E Arnold, May 29, 2026
Stupidization: A Long-Term Trend in US Education
May 22, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
I read “‘Learning Recession’ in US Schools Predates Pandemic: Report.” Usually I skip school-related articles. I am a dinobaby, and I am not sure I can remember my grade school teachers’ names or where my grade school is located. But this write up had a snappy phrase: Learning recession. I interpreted the two words in my lingo. I think “stupidization” better expresses the state of American grade, high, and college educational entities.
Thanks, Midjourney. Good enough.
This write up is more educated than I, so we have a “learning recession.” It sounds okay, but it does not communicate the issues in the US educational social construct. The write up states:
A new analysis of student test scores reveals that American schools were in a “learning recession” for seven years before the COVID-19 pandemic, with student test scores in math and reading on a steady decline since 2013…. The study reframes the narrative of pandemic-era learning loss, arguing that the crisis of the last few years was an acceleration of a problem that was already underway.
Okay, Covid, you did not cause stupidization. What did? What made “educated” people think that a computer in a middle school would improve a student’s ability to read, write, and do arithmetic? Why did people believe that a student would learn watching a lousy video delivered with amateur sound and poor lighting make clear how the Appalachian Mountains were formed?
The write up reports:
This long-term decline challenges the notion that a return to 2019 performance levels is the ultimate goal, as the data suggests those levels were already part of a downward trend. Today, eighth-grade reading scores on national assessments are at their lowest point since 1990. Compounding the problem, chronic student absenteeism remains a major obstacle to improving learning. Though down from its pandemic peak, 23% of students were chronically absent in the 2024–25 school year, far above the pre-pandemic rate of 15%.
The write up trots out the notion that the better education is enjoyed by those with the most money. Those without these resources and those in the big, plump middle of the bell curve are the folks who cannot make change, navigate a city without a mobile phone map, and read cursive.
Even the one bright spot comes with a caveat:
Nonetheless, the researchers caution that this is far from conclusive evidence that simply adopting “Science of Reading” policies will lead to improvements in reading skills. “There’s no silver bullet,” noted Reardon. “We need more research to understand what specific teacher training, coaching, and reading instruction practices are most effective, and for whom, and under what conditions. And we need the same for math.” The researchers also identified 108 “Districts on the Rise,” school systems of all income levels that are outpacing their peers. “Our hope is that people will learn from these states and districts and use them as models for improving our schools,” Reardon said.
I like my term stupidization. I know you are going to be thrilled with my personal observations:
- Learning requires the parentheses of a stable family and friends who want to learn and contribute to the community.
- Distractions make it very difficult to complete a task to the best of the student’s ability. The harder the task, the greater the need for a distraction free environment.
- School curricula should be anchored in the basics, not trends.
When an educational system cannot produce individuals who cannot read, make change, and engage in life-long learning — it is back to basics time. It is not time to buy every student a Mac Neo.
Net net: Skip jargon like learning recession and use plain, direct words like stupidization. That’s a small step forward in my opinion. Also, knock off the Covid thing. It’s getting long in the tooth.
Stephen E Arnold, May 18, 2026
Bedrock: Hackers Know the Bugs Will Not Be Fixed
May 11, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
Okay, we have Mythos. We have other LLMs that can find bugs. We have students in Estonia learning cyber security by banging away at Windows Azure, Windows 11, and Windows Teams. What do we learn from Tom’s Hardware? Answer: “We still have Windows 11 using ’90s code.”
What’s that suggest to you? I will share what my thoughts are once I take a look at a couple of passages from Tom’s “Microsoft CTO Confesses That 30-Year-Old Code from the Mid-90s Still Forms the Bedrock of Windows 11 — Ancient Win32 API Still the Backbone, But CTO Says It’s More Relevant Than Ever in 2026.”
Thanks, Venice.ai. Good enough.
The write up reports:
… the firm is currently in the midst of a major transformation, targeting enthusiast hot button areas like Windows performance, overhead, and reliability. This drastic pivot was cautiously welcomed in contrast to Microsoft being widely slammed for boasting about Windows “evolving into an agentic OS” last November. Currently, Microsoft seems to be flailing around, trying to stop folks straying to pastures greener like Mac and Linux.
I thought Microsoft made security job number one after SolarWinds. Now we have a “transformation.” But the company is transforming from what to what. Is it transforming to a security first outfit to an AI system? Is it transforming from desktop software to a cloudy solution? Is it transitioning from a baloney output machine to a horse feathers output system?
The write up states:
The CTO explains that Win32 has persisted even when facing targeted existential threats from within Microsoft, particularly in the Windows 8 era. “There’s been various times in Microsoft’s history where we thought we’d reboot the Windows API surface, like WinRT, that actually didn’t play out the way a lot of people expected it to.”
Explains? I think this means that Microsoft engineers cannot fix up, remediate, or reliably enhance Windows because of its bedrock. Yeah, that is helpful.
Okay, what’s my reaction?
- Windows is old code swathed in wrappers. Unlike “baby diapers” these wrappers cannot be cleaned. More digital diapers are added, thus increasing the attack surface for “germs” like the computer science students honing their cyber skills by hacking at Microsoft software.
- There is no fix. How do I know this? The WinRT statement means to me, “Yeah, we tried and failed.” The implication is that one pays for follies like the AI craziness in Notepad and the core issues from the 1990s are still there like defective protein strings that will one day go wacky so a system, like some people, fall over dead. Nifty.
- The trotting out of a tools person who was hired by Microsoft and then having him explain the value of bedrock and the persistence of old problems does zero for my confidence in the Microsoft outfit. Sure, it makes money, but it creates massive problems for its users, customers, and partners. Guess what? Too bad.
Net net: I have a number of Mac computers. Exactly zero of them present weird software failures like a failure to print, messages that a NAS cannot be found, or mice that don’t mouse. This article is a good promotion for a shift to greener pastures. Typical Microsoft. Hands waving and a shoulder shrug. Yeah, WinRT.
Stephen E Arnold, May 11, 2026
France Lines Up to Gore Some US Tech Bros
April 13, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
France has élan. My interest in the reactions of people who visit the country for the first time is keen. We live in rural Kentucky, and at get togethers which often involve cooking a freshly killed pig or wearing Derby pins and drinking local beverages, tales of travelers’ experiences are exchanged. Some people love the food, but report the waiters ignored them. Other say, “I entered a bakery and said, ‘Hello,’ and no one waited on me.” The tales of getting a hefty fine on the metro, visiting a small town and finding the shops closed for lunch, and the bafflement when a Kentuckians’ passport and wallet are stolen a few minutes after landing at the Marseille France Airport are far too common.
Venice.ai, you don’t know a French gendarme from a guardrail. Good enough.
Imagine how Americans working at Microslop, sorry, I meant to type Microsoft are reacting to this French decision: “France Says “Au Revoir” to Windows, “Bonjour” to Linux.” To be fair, I don’t know if French people who use Microsoft products will switch. The government agencies will adapt over time. Nevertheless, the decision is delightfully French.
The cited article reports:
France is planning a major shift in its government technology infrastructure, announcing its intention to move away from Microsoft Windows in favor of Linux. The decision marks a significant step in the country’s broader effort to reduce reliance on U.S.-based technology companies and regain control over its digital systems. The transition will begin with government workstations, particularly within key digital agencies, as part of a wider strategy to adopt open-source and locally controlled technologies.
From my point of view, this is just one example of the steps France and other countries will be taking to wean themselves from the tech bros’ approach to computers, online information, and software. Pressure is likely to be exerted on French government contractors to ensure that “digital sovereignty” is part of the work process.
What’s this mean for French technology firms? I would assume that big outfits like Dassault Systèmes-type organizations will comply, probably on a negotiated timeline. Private startups will use whatever is cheaper and does the job. If that means, Microsoft PowerPoint, those firms will do what they can until France ratchets up the pressure. Who can forget the arrest of Pavel Durov in August 2024. That action appears to have put a hitch in the Telegram git-along.
The write up points out:
Government leaders have emphasized the need to regain control over national data, infrastructure, and decision-making systems, rather than depending on foreign technology providers.
The write up adds:
France’s move highlights a growing shift in how nations view technology – not just as a tool for productivity, but as a strategic asset tied to sovereignty, security, and long-term independence.
My take: More bad news for US technology companies is coming. Next up will be actions directed at US firms’ business practices. In fact, at some point, I can see an American tech bro landing his private jet at a French airport. He will be detained and charges will be filed. He will be able to leave France, but the French wheels of justice will grind forward. Many things can result from this type of French direct action.
Today Linux Tomorrow maybe a Silicon Valley luminary. Just a thought.
Stephen E Arnold, April 13, 2026
Artemis: The Power of Eight Has Resolved to an Unpleasant Number
April 10, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
The flight around the moon has generated some interesting stories. One of these is “How NASA Built Artemis II’s Fault-Tolerant Computer.” The main point of the write up struck me as:
This month’s Artemis II mission carrying a crew of four around the Moon for the first time in over 50 years is supported by one of the most fault-tolerant computer system built for spaceflight. Unlike Apollo, the Orion capsule’s computing architecture manages nearly all of the vessel’s safety-critical functions, from life support to communication routing.
The article includes snappy subheads like “The Power of Eight.” That means to those in the know “triple redundancy.” A system, fail over system B, and a third backstop system.
Thanks, Venice.ai. Good enough just like the “triple redundancy” extolled by the ACM outfit.
The article points out:
This level of redundancy is specifically scaled for the rigors of deep space.
I found this statement fascinating:
The hardware itself is also reinforced. The system employs triple-modular-redundant memory that self-corrects single-bit errors on every read. Even the network interface cards utilize two lanes of traffic that are constantly compared, ensuring that a bit flip in the communication fabric results in a fail-silent event rather than a corrupted command. The network itself is triple redundant with three separate planes, and all network switches employ self-checking strategies.
The ACM write up concludes:
As spaceflight technology has historically seeded commercial advances, Orion’s zero-tolerance architecture offers a preview of a future where mainstream computing—from autonomous vehicles to industrial grids—can achieve the same always-on resilience that’s required for the stars.
Reassuring. However, when I thought about this explanation of the power of eight, I thought about three issues:
- Microsoft Outlook ran two instances and seemed to not match the rigor described in the cited ACM article
- The toilet failed, was “fixed,” and then failed again
- The heatshield will be a binary upon reentry. I hope that the triple redundancy and power of eight works appropriately.
Net net: Consumer software, a toilet obviously not designed for the rigors of space travel, and a heat shield that either works or does not work. To narrow the power of eight seems appropriate. Some systems are operating at a power of zero. No, that’s not correct. There are diapers.
Stephen E Arnold, April 10, 2026
-
- Subscribe to Beyond Search
Feature archive
News archive
-
