Google Uses a Blue Light Special for the US Government (Sorry K-Meta You Lose)
August 27, 2025
No AI. Just a dinobaby working the old-fashioned way.
I read an interesting news item in Artificial Intelligence News, a publication unknown to me. Like most of the AI information I read online I believe every single word. AI radiates accuracy, trust, and factual information. Let’s treat this “real” news story as actual factual. To process the information, you will want to reflect on the sales tactics behind Filene’s Basement, K-Mart’s blue light specials, and the ShamWow guy.
“The US Federal Government Secures a Massive Google Gemini AI Deal at $0.47 per Agency” reports:
Google Gemini will soon power federal operations across the United States government following a sweeping new agreement between the General Services Administration (GSA) and Google that delivers comprehensive AI capabilities at unprecedented pricing.
I regret I don’t have Microsoft government sales professional or a Palantir forward deployed engineer to call and get their view of this deal. Oh, well, that’s what happens when one gets old. (Remember. For a LinkedIn audience NEVER reveal your age. Okay, too bad LinkedIn, I am 81.)
It so happens I was involved in Year 2000 in some meetings at which Google pitched its search-and-retrieval system for US government wide search. For a number of reasons, the Google did not win that procurement bake off. It took a formal protest and some more meetings to explain the concept of conforming to a Statement of Work and the bid analysis process used by the US government 25 years ago. Google took it on the snout.
Not this time.
By golly, Google figured out how to deal with RFPs, SOWs, the Q&A process, and the pricing dance. The write up says:
The “Gemini for Government” offering, announced by GSA, represents one of the most significant government AI procurement deals to date. Under the OneGov agreement extending through 2026, federal agencies will gain access to Google’s full artificial intelligence stack for just US$0.47 per agency—a pricing structure that industry observers note is remarkably aggressive for enterprise-level AI services.
What does the US government receive? According to the write up:
Google CEO Sundar Pichai characterized the partnership as building on existing relationships: “Building on our Workspace offer for federal employees, ‘Gemini for Government’ gives federal agencies access to our full stack approach to AI innovation, including tools like NotebookLM and Veo powered by our latest models and our secure cloud infrastructure.”
Yo, Microsoft. Yo, Palantir. Are you paying attention? This explanation suggests that a clever government professional can do what your firms do. But — get this — at a price that may be “unsustainable.” (Of course, I know that em dashes signal smart software. Believe me. I use em dashes all by myself. No AI needed.)
I also noted this statement in the write up:
The $0.47 per agency pricing model raises immediate concerns about market distortion and the sustainability of such aggressive government contracting. Industry analysts question whether this represents genuine cost efficiency or a loss-leader strategy designed to lock agencies into Google’s ecosystem before prices inevitably rise after 2026. Moreover, the deal’s sweeping scope—encompassing everything from basic productivity tools to custom AI agent development—may create dangerous vendor concentration risks. Should technical issues, security breaches, or contract disputes arise, the federal government could find itself heavily dependent on a single commercial provider for critical operational capabilities. The announcement notably lacks specific metrics for measuring success, implementation timelines, or safeguards against vendor lock-in—details that will ultimately determine whether this represents genuine modernization or expensive experimentation with taxpayer resources.
Several observations are warranted:
- Google has figured out that making AI too cheap to resist appeals to certain government procurement professionals. A deal is a deal, of course. Scope changes, engineering services, and government budget schedules may add some jerked chicken spice to the bargain meal.
- The existing government-wide incumbent types are probably going to be holding some meetings to discuss what “this deal” means to existing and new projects involving smart software.
- The budget issues about AI investments are significant. Adding more expense for what can be a very demanding client is likely to have a direct impact on advertisers who fund the Google fun bus. How much will that YouTube subscription go up? Would Google raise rates to fund this competitive strike at Microsoft and Palantir? Of course not, you silly goose.
I wish I were at liberty to share some of the Google-related outputs from the Year 2000 procurement. But, alas, I cannot. Let me close by saying, “Google has figured out some basics of dealing with the US government.” Hey, it only took a quarter century, not bad for an ageing Googzilla.
Stephen E Arnold, August 27, 2025
Think It. The * It * Becomes Real. Think Again?
August 27, 2025
No AI. Just a dinobaby working the old-fashioned way.
Fortune Magazine — once the gem for a now spinning-in-his-grave publisher —- posted “MIT Report: 95% of Generative AI Pilots at Companies Are Failing.” I take a skeptical view of MIT. Why? The esteemed university found Jeffrey Epstein a swell person.
The thrust of the story is that people stick smart software into an organization, allow it time to steep, cook up a use case, and find the result unpalatable. Research is useful. When it evokes a “Duh!”, I don’t get too excited.
But there was a phrase in the write up which caught my attention: Learning gap. AI or smart software is a “belief.” The idea of the next big thing creates an opportunity to move money. Flow, churn, motion — These are positive values in some business circles.
AI fits the bill. The technology demonstrates interesting capabilities. Use cases exist. Companies like Microsoft have put money into the idea. Moving money is proof that “something” is happening. And today that something is smart software. AI is the “it” for the next big thing.
Learning gap, however, is the issue. The hurdle is not Sam Altman’s fears about the end of humanity or his casual observation that trillions of dollars are needed to make AI progress. We have a learning gap.
But the driving vision for Internet era innovation is do something big, change the world, reinvent society. I think this idea goes back to the sales-oriented philosophy of visualizing a goal and aligning one’s actions to achieve that goal. I a fellow or persona named Napoleon Hill pulled together some ideas and crafted “Think and Grow Rich.” Today one just promotes the “next big thing,” gets some cash moving, and an innovation like smart software will revolutionize, remake, or redo the world.
The “it” seems to be stuck in the learning gap. Here’s the proof, and I quote:
But for 95% of companies in the dataset, generative AI implementation is falling short. The core issue? Not the quality of the AI models, but the “learning gap” for both tools and organizations. While executives often blame regulation or model performance, MIT’s research points to flawed enterprise integration. Generic tools like ChatGPT excel for individuals because of their flexibility, but they stall in enterprise use since they don’t learn from or adapt to workflows, Challapally explained. The data also reveals a misalignment in resource allocation. More than half of generative AI budgets are devoted to sales and marketing tools, yet MIT found the biggest ROI in back-office automation—eliminating business process outsourcing, cutting external agency costs, and streamlining operations.
Consider this question: What if smart software mostly works but makes humans uncomfortable in ways difficult for the user to articulate? What if humans lack the mental equipment to conceptualize what a smart system does? What if the smart software cannot answer certain user questions?
I find information about costs, failed use cases, hallucinations, and benefits plentiful. I don’t see much information about the “learning gap.” What causes a learning gap? Spell check makes sense. A click that produces a complete report on a complex topic is different. But in what way? What is the impact on the user?
I think the “learning gap” is a key phrase. I think there is money to be made in addressing it. I am not confident that visualizing a better AI is going to solve the problem which is similar to a bonfire of cash. The learning gap might be tough to fill with burning dollar bills.
Stephen E Arnold, August 27, 2025
A Better Telegram: Max (imum) Surveillance
August 27, 2025
No AI. Just a dinobaby working the old-fashioned way.
The super duper everything apps include many interesting functions. But one can spice up a messaging app with a bit of old-fashioned ingenuity. The newest “player” in the “secret” messaging game is not some knock off Silicon Valley service. The MAX app has arrived.
Reuters reported in “Russia Orders Sate-Backed MAX Messenger Ap, a WhatsApp Rival, Pre-Installed on Phones and Tablets.” (Did you notice the headline did not include Telegram?) The trusted news source says:
A Russian state-backed messenger application called MAX, a rival to WhatsApp that critics say could be used to track users, must be pre-installed on all mobile phones and tablets from next month, the Russian government said on Thursday. The decision to promote MAX comes as Moscow is seeking greater control over the internet space as it is locked in a standoff with the West over Ukraine, which it casts as part of an attempt to shape a new world order.
I like the inclusion of a reference to “a new world order.”
The trusted news source adds:
State media says accusations from Kremlin critics that MAX is a spying app are false and that it has fewer permissions to access user data than rivals WhatsApp and Telegram.
Yep, Telegram. Several questions:
- Are any of the companies supporting MAX providing services to Telegram?
- Were any of the technologists working on MAX associated with VKontakte or Telegram?
- Will other countries find the MAX mandated installation an interesting idea?
- How does MAX intersect with data captured from Russia-based telecom outfits and online service providers?
I can’t answer these questions, but I would think that a trusted news service would.
Stephen E Arnold, August 27, 2025
Apple and Meta: The After Market Route
August 26, 2025
No AI. Just a dinobaby working the old-fashioned way.
Two big outfits are emulating the creative motif for an American television series titled “Pimp My Ride.” The show was hosted by rapper Xzibit, who has a new album called “Kingmaker” in the works. He became the “meme” of the television program with his signature phrase, “Yo, dawg, I heard you like.”
A DVD of season one, is available for sale at www.bol.com.
Each episode a “lucky person” would be approached and told that his or her vehicle would be given a make over. Some of the make overs were memorable. Examples included the “Yellow Shag Disaster,” which featured yellow paint and yellow shag carpeting. The team removed a rat living in the 1976 Pacer. Another was the “Drive In Theater Car.” It included a pop up champagne dispenser and a TV screen installed under the hood for a viewing experience when people gathered outside the vehicle.
The idea was to take something that mostly worked and then add-on extras. Did the approach work? It made Xzibit even more famous and it contributed the phrase “Yo, dawg, I heard you like” to the US popular culture between 2004 and 2007.
I think the “Pimp My Ride” concept has returned for Apple and Meta. Let me share my thoughts with you.
First, I noted that Bloomberg is exploring the use of Google Gemini AI to Power the long suffering Siri. You can read the paywalled story at this link. Apple knows that Google’s payments are worth real money. The idea of adding more Google and getting paid for the decision probably makes sense to the estimable Apple. Will the elephants mate and produce more money or will the grass get trampled. I don’t know. It will be interesting to see what the creative wizards at both companies produce. There is no date for the release of the first episode. I will be watching.
Second, the story presented in fragments on X.com appears at this X.com page. The key item of information is the alleged tie up between Meta and MidJourney:
Today we’re proud to announce a partnership with @midjourney , to license their aesthetic technology for our future models and products, bringing beauty to billions.
Meta, like Apple, is partnering with an AI success in the arts and crafts sector of smart software. The idea seems to focus on “aesthetic excellence.” How will these outfits enhance Meta. Here’s what the X.com comment offers:
To ensure Meta is able to deliver the best possible products for people it will require taking an all-of-the-above approach. This means world-class talent, ambitious compute roadmap, and working with the best players across the industry.
Will these add-one approaches to AI deliver something useful to millions or will the respective organizations produce the equivalent of the “Pimp My Ride” Hot Tub Limousine. This after-market confection added a hot tub filled with water to a limousine. The owner of the vehicle could relax in the hot tub while the driver ferried the proud owner to the bank.
I assume the creations of the Apple, Google, Meta, and MidJourney teams will be captured on video and distributed on TikTok-type services as well as billions of computing devices. My hope is that Xzibit is asked to host the roll outs for the newly redone services. I would buy a hat, a T shirt, and a poster for the “winner” of this new AI enhanced effort.
Yo, dawg, I heard you like AI, right?
Stephen E Arnold, August 26, 2025
And the Problem for Enterprise AI Is … Essentially Unsolved
August 26, 2025
No AI. Just a dinobaby working the old-fashioned way.
I try not to let my blood pressure go up when I read “our system processes all your organization’s information.” Not only is this statement wildly incorrect it is probably some combination of [a] illegal, [b] too expensive, and [c] too time consuming.
Nevertheless, vendors either repeat the mantra or imply it. When I talk with representatives of these firms, over time, fewer and fewer recognize the craziness of the assertion. Apparently the reality of trying to process documents related to a legal matter, medical information, salary data, government-mandated secrecy cloaks, data on a work-from-home contractor’s laptop which contains information about payoffs in a certain country to win a contract, and similar information is not part of this Fantasyland.
I read “Immature Data Strategies Threaten Enterprise AI Plans.” The write up is a hoot. The information is presented in a way to avoid describing certain ideas as insane or impossible. Let’s take a look at a couple of examples. I will in italics offer my interpretation of what the online publication is trying to coat with sugar and stick inside a Godiva chocolate.
Here’s the first snippet:
Even as senior decision-makers hold their data strategies in high regard, enterprises face a multitude of challenges. Nearly 90% of data pros reported difficulty with scaling and complexity, and more than 4 in 5 pointed to governance and compliance issues. Organizations also grapple with access and security risks, as well as data quality, trust and skills gaps.
My interpretation: Executives (particularly leadership types) perceive their organizations as more buttoned up than they are in reality. Ask another employee, and you will probably hear something like “overall we do very well.” The fact of the matter is that leadership and satisfied employees have zero clue about what is required to address a problem. Looking too closely is not a popular way to get that promotion or to keep the Board of Directors and stakeholders happy. When you have to identify an error use a word like “governance” or “regulations.”
Here’s the second snippet:
To address the litany of obstacles, organizations are prioritizing data governance. More than half of those surveyed expect strengthened governance to significantly improve AI implementation, data quality and trust in business decisions.
My interpretation: Let’s talk about governance, not how poorly procurement is handled and the weird system problems that just persist. What is “governance”? Organizations are unsure how they continue to operate. The purpose of many organizations is — believe it or not — lost. Make money is the yardstick. Do what’s necessary to keep going. That’s why in certain organizations an employee from 30 years ago could return and go to a meeting. Why? No change. Same procedures, same thought processes, just different people. Incrementalism and momentum power the organization.
So what? Organizations are deciding to give AI a whirl or third parties are telling them to do AI. Guess what? Major change is difficult. Systems-related activities repeat the same cycle. Here’s one example: “We want to use Vendor X to create an enterprise knowledge base.” Then the time, cost, and risks are slowly explained. The project gets scaled back because there is neither time, money, employee cooperation, or totally addled attorneys to make organization spanning knowledge available to smart software.
The pitch sounds great. It has for more than 60 years. It is still a difficult deliverable, but it is much easier to market today. Data strategies are one thing; reality is anther.
Stephen E Arnold, August 26, 2025
Deal Breakers in Medical AI
August 26, 2025
No AI. Just a dinobaby working the old-fashioned way.
My newsfeed thing spit out a link to “Why Radiology AI Didn’t Work and What Comes Next.” I have zero interest in radiology. I don’t get too excited about smart software. So what did I do? Answer: I read the article. I was delighted to uncover a couple of points that, in my opinion, warrant capturing in my digital notebook.
The set up is that a wizard worked at a start up trying to get AI to make sense of the consistently fuzzy, murky, and baffling images cranked out by radiology gizmos. Tip: Follow the instructions and don’t wear certain items of jewelry. The start up fizzled. AI was part of the problem, but the Jaws-type sharp lurking in the murky image explains this type of AI implosion.
Let’s run though the points that struck me.
First, let’s look at this passage:
Unlike coding or mathematics, medicine rarely deals in absolutes. Clinical documentation, especially in radiology, is filled with hedge language — phrases like “cannot rule out,” “may represent,” or “follow-up recommended for correlation.” These aren’t careless ambiguities; they’re defensive signals, shaped by decades of legal precedent and diagnostic uncertainty.
Okay, lawyers play a significant role in establishing thought processes and normalizing ideas that appear to be purpose-built to vaporize like one of those nifty tattoo removing gadgets the smart system. I would have pegged insurance companies, then lawyers, but the write up directed my attention of the legal eagles’ role: Hedge language. Do I have disease X? The doctor responds, “Maybe, maybe not. Let’s wait 30 days and run more tests.” Fuzzy lingo, fuzzy images, perfect.
Second, the write up asks two questions:
- How do we improve model coverage at the tail without incurring prohibitive annotation costs?
- Can we combine automated systems with human-in-the-loop supervision to address the rare but dangerous edge cases?
The answers seem to be: You cannot afford to have humans do indexing and annotation. That’s why certain legal online services charge a lot for annotations. And, the second question, no, you cannot pull off automation with humans for events rarely covered in the training data. Why? Cost and finding enough humans who will do this work in a consistent way in a timely manner.
Here’s the third snippet:
Without direct billing mechanisms or CPT reimbursement codes, it was difficult to monetize the outcomes these tools enabled. Selling software alone meant capturing only a fraction of the value AI actually created. Ultimately, we were offering tools, not outcomes. And hospitals, rightly, were unwilling to pay for potential unless it came bundled with performance.
Finally, insurance procedures. Hospitals aren’t buying AI; they are buying ways to deliver “service” and “bill.” AI at this time does not sell what hospitals want to buy: A way to keep high rates and slash costs wherever possible.
Unlikely but perhaps some savvy AI outfit will create a system that can crack the issues the article identifies. Until then, no money, no AI.
Stephen E Arnold, August 26, 2025
Leave No Data Unslurped: A New Google T Shirt Slogan?
August 25, 2025
No AI. Just a dinobaby working the old-fashioned way.
That mobile phone is the A Number One surveillance device ever developed. Not surprisingly, companies have figured out how to monetize the data flowing through the device. Try explaining the machinations of those “Accept Defaults” to a clutch of 70-something bridge players. Then try explaining the same thing to the GenAI type of humanoid. One group looks at you with a baffled work on their faces. The other group stares into the distance and says, “Whatever.”
Now the Google wants more data, fresh information, easily updated. Because why not? “Google Expands AI-Based Age Verification System for Search Platform.” The write up says:
Google has begun implementing an artificial intelligence-based age verification system not only on YouTube but also on Google Search … Users in the US are reporting pop-ups on Google Search saying, “We’ve changed some of your settings because we couldn’t verify that you’re of legal age.” This is a sign of new rules in Google’s Terms of Service.
Why the scope creep from YouTube to “search” with its AI wonderfulness? The write up says:
The new restrictions could be another step in re-examining the balance between usability and privacy.
Wrong. The need for more data to stuff into the assorted AI “learning” services provide a reasonable rationale. Tossing in the “prevent harm” angle is just cover.
My view of the matter is:
- Mobile is a real time service. Capturing more information of a highly-specific nature is something that is an obvious benefit to the Google.
- Users have zero awareness of how the data interactions work and most don’t want to know to try to understand cross correlation.
- Google’s goals are not particularized. This type of “fingerprint” just makes sense.
The motto could be “Leave no data unslurped.” What’s this mean? Every Google service will require verification. The more one verifies, the fresher the identify information and the items that tag along and can be extracted. I think of this as similar to the process of rendering slaughtered livestock. The animal is dead, so what’s the harm.
None, of course. Google is busy explaining how little its data centers use to provide those helpful AI overview things.
Stephen E Arnold, August x, 2025
Stephen E Arnold, August 25, 2025
Learning Is Hard Work: AI Is Not Part of My Game Plan
August 25, 2025
No AI. Just a dinobaby working the old-fashioned way.
Dinobaby here—a lifetime of unusual education packed into a single childhood. I kicked off in a traditional Illinois kindergarten, then traded finger painting for experimental learning at a “new-idea” grade school in Maryland after a family move near DC. Soon, Brazil called: I landed in Campinas, but with zero English spoken, I lasted a month. Fifth through seventh grade became a solo mission—Calvert Course worksheets, a jungle missionary who mailed my work to Baltimore, and eventually, after the tutor died, pure self-guided study from thousands of miles away. I aced my assignments, but no one in Maryland had any idea of my world. My Portuguese tutor mixed French and German with local lingo; ironically, her English rocketed while my Portuguese crawled.
Back in the States, I dove into “advanced” classes and spent a high school semester at the University of Illinois—mainly reading, testing, and reading. A scholarship sent me to Bradley, a few weeks removed from a basketball cheating inquiry. A professor hooked me on coding in the library, building Latin sermon indexes using the school’s IBM. That led to a Duquesne fellowship; then the University of Arkansas wanted me for their PhD program. But I returned to Illinois, wrote code for Milton texts instead of Latin under Arthur Barker’s mentorship, and gave talks that landed me a job offer. One conference center chat brought me to DC and into the nuclear division at Halliburton. That’s my wild educational ride.
Notice that it did not involve much traditional go-to-class activity. I have done okay despite my somewhat odd educational journey. Most important: No smart software.
Now why did I provide this bit of biographical trivia? I read “AI in the Classroom Is Important for Real-World Skills, College Professors Say.” I did not have access to “regular” school through grade school, high school, and college. I am not sure how many high school students took classes at the U of I when they were 15 years old, but that experience was not typical among my high school class.
I did start working with computers and software in 1962, but there wasn’t much smart software floating around then. The trick for me has been my ability to read quickly, recognize what’s important, and remember information. Again there was no AI. Today, as I finish my Telegram Labyrinth monograph, AI has not been of any importance. Most of the source material is in Russian language documents. The English information is not thoroughly indexed by Telegram nor by the Web search engines. The LLM content suckers are not doing too much with information outside the English speaking world. Maybe China is pushing forward, but my tests with Chinese language Web search engines did not provide much, if any, information my team and I already had reviewed.
Obviously I don’t think AI is something that fits into my “real world skills.” The write up says:
“If integrated well, AI in the classroom can strengthen the fit between what students learn and what students will see in the workforce and world around them,” argued Victor Lee, associate professor at Stanford’s Graduate School of Education. GenAI companies are certainly doing their part to lure students into using their tools by offering new learning and essay-writing features. Google has gone so far as to offer Gemini free for one year, and OpenAI late last month introduced “Study Mode” to help students “work through problems step by step instead of just getting an answer,” the company said in a blog post.
Maybe.
My personal approach to learning involves libraries, for fee online databases, Web research, and more reading. I still take notes on 4×6 notecards just as I did when I was trying to index those Latin sermons. Once I process the “note”, I throw it away. I am lucky because once I read, write, and integrate the factoid into something I am writing — I remember the information. I don’t use digital calendars. I don’t use integrated to do lists. I just do what has been old fashioned information acquisition work.
The computer is wonderful for writing, Web research, and cooking up PowerPoint pablum. But the idea that using a tool that generates incorrect information strikes me as plain crazy.
The write up says:
Longji Cuo, an associate professor at the University of Colorado, in Boulder, teaches a course on AI and machine learning to help mechanical engineering students learn to use the technology to solve real-world engineering problems. Cuo encourages students to use AI as an agent to help with teamwork, projects, coding, and presentations in class. “My expectation on the quality of the work is much higher,” Cuo said, adding that students need to “demonstrate creativity on the level of a senior-level doctoral student or equivalent.”
Maybe. I am not convinced. Engineering issues are cascading across current and new systems. AI doesn’t seem to stem the tide. What about AI cyber security? Yeah, it’s working great. What about coding assistants? Yeah, super. I just uninstalled another Microsoft Windows 11 update. This one can kill my data storage devices. Copilot? Yeah, wonderful.
The write up concludes with this assertion from an “expert”:
one day, AI agents will be able to work with students on their personalized education needs. “Rather than having one teacher for 30 students, you’ll have one AI agent personalized to each student that will guide them along.”
Learning is hard work. The silliness of computer aid instruction, laptops, iPads, mobile phones, etc. makes one thing clear, learning is not easy. A human must focus, develop discipline, refine native talents, demonstrate motivate, curiosity, and an ability to process information into something more useful than remembering the TikTok icon’s design.
I don’t buy this. I am glad I am old.
Stephen E Arnold, August 25, 2025
Is Reading Necessary, Easy, and Fun? Sure
August 25, 2025
No AI. Just a dinobaby working the old-fashioned way.
The GenAI service person answered my questions this way:
- Is reading necessary? Answer: Not really
- Is reading easy? No, not for me
- Is reading fun? For me, no.
Was I shocked? No. I almost understand. Note: I said “almost.” The idea that the mental involvement associated with reading is, for my same of one, is not on the radar.
“Reading for Pleasure in Freefall: Research Finds 40% Drop Over Two Decades” presents information that caught my attention for two reasons:
- The decline appears to be gradual; that is, freefall. The time period in terms of my dinobaby years is wildly inaccurate.
- The inclusion of a fat round number like 40 percent strikes me as understatement
On what basis do I make these two observations about the headline? I have what I call a Barnes & Noble toy ratio. A bookstore is now filled with toys, knick-knacks and Temu-type products. That’s it. Book stores are tough to find. When one does locate a book store, it often is a toy store.
The write up is much more scientific than my toy algorithm. I noted this passage from a study conducted by two universities I view as anchors of opposite ends of the academic spectrum: The University of Florida and University College London. Here’s the passage:
the study analyzed data from over 236,000 Americans who participated in the American Time Use Survey between 2003 and 2023. The findings suggest a fundamental cultural shift: fewer people are carving out time in their day to read for enjoyment. This is not just a small dip—it’s a sustained, steady decline of about 3% per year…
I don’t want to be someone who criticizes the analysis of two esteemed institutions. I would suggest that the decrease is going to take much less time than a couple of centuries if the three percent erosion continues. I acknowledge that in the US print book sales in 2024 reached about 700 million (depending on whom one believes), an increase of over 2023. These data do not reflect books generated by smart software.
But book sales does not mean more people are reading material that requires attention. Old people read more books than a grade school student or a young person who is not in what a dinobaby would call a school. Hats off to the missionary who teaches one young person in a tough spot to read and provides the individual with access to books.
I want to acknowledge this statement in the write up:
The researchers also noted some more promising findings, including that reading with children did not change over the last 20 years. However, reading with children was a lot less common than reading for pleasure, which is concerning given that this activity is tied to early literacy development, academic success and family bonding….
I interpreted the two stellar institutions as mostly getting at these points:
- Some people read and read voraciously. Pleasure or psychological problem? Who knows. It happens.
- Many people don’t value books, don’t read books, and won’t by choice or mental set up can’t read books.
- The distractions of just existing today make reading a lower priority for some than other considerations; for example, not getting hit by a kinetic in a war zone, watching TikTok, creating YouTube videos about big thoughts, a mobile phone, etc.
Let’s go back to the book store and toys. The existence of toys in a book store make clear that selling books is a very tough business. To stay open, Temu-type stuff has to be pushed. If reading were “fun,” the book stores would be as plentiful as unsold bourbon in Kentucky.
Net net: We have reached a point at which the number of readers is a equivalent to the count of snow leopards. Reading for fun marks an individual as one at risk of becoming a fur coat.
Stephen E Arnold, August 29, 2025
Copilot, Can You Crash That Financial Analysis?
August 22, 2025
No AI. Just a dinobaby working the old-fashioned way.
The ever-insouciant online service The Verge published a story about Microsoft, smart software, and Excel. “Microsoft Excel Adds Copilot AI to Help Fill in Spreadsheet Cells” reports:
Microsoft Excel is testing a new AI-powered function that can automatically fill cells in your spreadsheets, which is similar to the feature that Google Sheets rolled out in June.
Okay, quite specific intentionality: Fill in cells. And a dash of me-too. I like it.
However, the key statement in my opinion is:
The COPILOT function comes with a couple of limitations, as it can’t access information outside your spreadsheet, and you can only use it to calculate 100 functions every 10 minutes. Microsoft also warns against using the AI function for numerical calculations or in “high-stakes scenarios” with legal, regulatory, and compliance implications, as COPILOT “can give incorrect responses.”
I don’t want to make a big deal out of this passage, but I will do it anyway. First, Microsoft makes clear that the outputs can be incorrect. Second, don’t use it too much because I assume one will have to pay to use a system that “can give incorrect results.” In short, MSFT is throttling Excel’s Copilot. Doesn’t everyone want to explore numbers with an addled Copilot known to flub numbers in a jet aircraft at 0.8 Mach?
I want to quote from “It Took Many Years And Billions Of Dollars, But Microsoft Finally Invented A Calculator That Is Wrong Sometimes”:
Think of it. Forty-five hundred years ago, if you were a Sumerian scribe, while your calculations on the world’s first abacus might have been laborious, you could be assured they’d be correct. Four hundred years ago, if you were palling around with William Oughtred, his new slide rule may have been a bit intimidating at first, but you could know its output was correct. In the 1980s, you could have bought the cheapest, shittiest Casio-knockoff calculator you could find, and used it exclusively, for every day of the rest of your life, and never once would it give anything but a correct answer. You could use it today! But now we have Microsoft apparently determining that “unpredictability” was something that some number of its customers wanted in their calculators.
I know that I sure do. I want to use a tool that is likely to convert “high-stakes scenarios” into an embarrassing failure. I mean who does not want this type of digital Copilot?
Why do I find this Excel with Copilot software interesting?
- It illustrates that accuracy has given way to close enough for horseshoes. Impressive for a company that can issue an update that could kill one’s storage devices.
- Microsoft no longer dances around hallucinations. The company just says, “The outputs can be wrong.” But I wonder, “Does Microsoft really mean it?” What about Red Bull-fueled MBAs handling one’s retirement accounts? Yeah, those people will be really careful.
- The article does not come and and say, “Looks like the AI rocket ship is losing altitude.”
- I cannot imagine sitting in a meeting and observing the rationalizations offered to justify releasing a product known to make NUMERICAL errors.
Net net: We are learning about the quality of [a] managerial processes at Microsoft, [b] the judgment of employees, and [c] the sheer craziness that an attorney said, “Sure, release the product just include an upfront statement that it will make mistakes.” Nothing builds trust more than a company anchored in customer-centric values.
Stephen E Arnold, August 22, 2025
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