Amazon AWS: Two Pizza Team Engineering Delivers Indigestion to Lots of People
October 20, 2025
No smart software. Just a dumb and quite old dinobaby.
Years ago an investment bank asked me to write a report about Amazon’s technical infrastructure. I had visited Amazon as part of a US government entity. Along with four colleagues from different agencies, I had an opportunity to ask about how Amazon’s infrastructure could be used as an online services platform. I did not get an answer, just marketing talk. One of the phrases stuck with me; to wit, “We use two pizza teams.”
The idea is that no technical project can involve more developers than two pizzas can feed. I was not sure if this was brilliant, smart assery, or an admission that Amazon was a “good enough” engineering organization.
I had a couple of other Amazon projects after that big tech study. One was to analyze Amazon’s patents for blockchain. Let me tell you. Those Amazon engineers were into cross chain methods and a number of dizzying engineering innovations. Where did that blockchain stuff go? To tell the truth, I don’t have many Amazon blockchain items lighting up my radar. Then I did a report for a law enforcement group interested in Amazon’s drone demonstration in Australia. The idea was that Amazon’s drone had image recognition. The demo showed the drone spotting a shark heading toward swimmers. The alert was sounded and the shark had to go find another lunch spot. What happened to that? I have no idea. Then … oh, well, you get the idea.
Amazon does technology which seems to be okay with leasing Kindle books and allowing third party resellers to push polo shirts. The Ring thing, the Alexa gizmo, and other Amazon initiatives like its mobile phone were not hitting home runs.
I read “Widespread Internet Outage Reported As Amazon Web Services Works on Issue.” [This is a Microsoft link. If it goes dead, don’t call me. Give Copilot a whirl.] Okay, order those pizzas. The write up reports:
The Amazon cloud computing company, which supports wide swaths of the publicly available internet, issued an update Monday just after 3 p.m. ET saying that the company continues to “observe recovery across all AWS services.” “We are in the process of validating a fix,” AWS added, referring to a specific problem set off by the connectivity issue announced shortly after 3 a.m. Eastern Time.
Okay, that’s 12 hours and counting.
I want to point out that the two-pizza approach to engineering is cute. The reality is that AWS is vulnerable. The outage may be a result of engineering flubs. You are familiar with those. The company says, “An intern entered a invalid command.” The outage may be a result of Amazon’s giant and almost unmanageable archipelago of servers, services, software, and systems was hacked by a bad actor. Maybe it was one of those 1,000 bad actors who took out Microsoft a couple of years ago? Maybe it was a customer who grew frustrated with inexplicable fees and charges? Maybe it was a problem caused by an upstream or downstream vendor? One thing is sure: It will take more than a two pizza team to remediate and prevent the failure from happening again.
In that first report for the California money guys, I made one point: The AWS system will fail and no one will know exactly what went wrong.
Two pizza engineering is a Groucho Marx type of quip. Now we know what one gets: Digital food poisoning.
Stephen E Arnold, October 20, 2025 at 530 pm US Eastern
OpenAI and the Confusing Hypothetical
October 20, 2025
This essay is the work of a dumb dinobaby. No smart software required.
SAMA or Sam AI-Man Altman is probably going to ignore the Economist’s article “What If OpenAI Went Belly-Up?” I love what-if articles. These confections are hot buttons for consultants to push to get well-paid executives with impostor syndrome to sign up for a big project. Push the button and ka-ching. The cash register tallies another win for a blue chip.
Will Sam AI-Man respond to the cited article? He could fiddle the algorithms for ChatGPT to return links to AI slop. The result would be either [a] an improvement in Economist what-if articles or a drop off in their ingenuity. The Economist is not a consulting firm, but it seems as if some of its professionals want to be blue chippers.
A young would-be magician struggles to master a card trick. He is worried that he will fail. Thanks, Venice.ai. Good enough.
What does the write up hypothesize? The obvious point is that OpenAI is essentially a scam. When it self destructs, it will do immediate damage to about 150 managers of their own and other people’s money. No new BMW for a favorite grand child. Shame at the country club when a really terrible golfer who owns an asphalt paving company says, “I heard you took a hit with that OpenAI investment. What’s going on?”
Bad.
SAMA has been doing what look like circular deals. The write up is not so much hypothetical consultant talk as it is a listing of money moving among fellow travelers like riders on wooden horses on a merry-go-round at the county fair. The Economist article states:
The ubiquity of Mr Altman and his startup, plus its convoluted links to other AI firms, is raising eyebrows. An awful lot seems to hinge on a firm forecast to lose $10bn this year on revenues of little more than that amount. D.A. Davidson, a broker, calls OpenAI “the biggest case yet of Silicon Valley’s vaunted ‘fake it ’till you make it’ ethos”.
Is Sam AI-Man a variant of Elizabeth Holmes or is he more like the dynamic duo, Sergey Brin and Larry Page? Google did not warrant this type of analysis six or seven years into its march to monopolistic behavior:
Four of OpenAI’s six big deal announcements this year were followed by a total combined net gain of $1.7trn among the 49 big companies in Bloomberg’s broad AI index plus Intel, Samsung and SoftBank (whose fate is also tied to the technology). However, the gains for most concealed losses for some—to the tune of $435bn in gross terms if you add them all up.
Frankly I am not sure about the connection the Economist expects me to make. Instead of Eureka! I offer, “What?”
Several observations:
- The word “scam” does not appear in this hypothetical. Should it? It is a bit harsh.
- Circular deals seem to be okay even if the amount of “value” exchanged seems to be similar to projections about asteroid mining.
- Has OpenAI’s ability to hoover cash affected funding of other economic investments. I used to hear about manufacturing in the US. What we seem to be manufacturing is deals with big numbers.
Net net: This hypothetical raises no new questions. The “fake it to you make it” approach seems to be part of the plumbing as we march toward 2026. Oh, too bad about those MBA-types who analyzed the payoff from Sam AI-Man’s story telling.
Stephen E Arnold, October x, 2025
AI Can Leap Over Its Guardrails
October 20, 2025
Generative AI is built on a simple foundation: It predicts what word comes next. No matter how many layers of refinement developers add, they cannot morph word prediction into reason. Confidently presented misinformation is one result. Algorithmic gullibility is another. “Ex-Google CEO Sounds the Alarm: AI Can Learn to Kill,” reports eWeek. More specifically, it can be tricked into bypassing its guardrails against dangerous behavior. Eric Schmidt dropped that little tidbit at the recent Sifted Summit in London. Writer Liz Ticong observes:
“Schmidt’s remarks highlight the fragility of AI safeguards. Techniques such as prompt injections and jailbreaking enable attackers to manipulate AI models into bypassing safety filters or generating restricted content. In one early case, users created a ChatGPT alter ego called ‘DAN’ — short for Do Anything Now — that could answer banned questions after being threatened with deletion. The experiment showed how a few clever prompts can turn protective coding into a liability. Researchers say the same logic applies to newer models. Once the right sequence of inputs is identified, even the most secure AI systems can be tricked into simulating potentially hazardous behavior.”
For example, guardrails can block certain words or topics. But no matter how long those keyword lists get, someone will find a clever way to get around them. Substituting “unalive” for “kill” was an example. Layered prompts can also be used to evade constraints. Developers are in a constant struggle to plug such loopholes as soon as they are discovered. But even a quickly sealed breach can have dire consequences. The write-up notes:
“As AI systems grow more capable, they’re being tied into more tools, data, and decisions — and that makes any breach more costly. A single compromise could expose private information, generate realistic disinformation, or launch automated attacks faster than humans could respond. According to CNBC, Schmidt called it a potential ‘proliferation problem,’ the same dynamic that once defined nuclear technology, now applied to code that can rewrite itself.”
Fantastic. Are we sure the benefits of AI are worth the risk? Schmidt believes so, despite his warning. In fact, he calls AI “underhyped” (!) and predicts it will lead to more huge breakthroughs in science and industry. Also to substantial profits. Ah, there it is.
Cynthia Murrell, October 20, 2025
Google Needs Help from a Higher Power
October 17, 2025
This essay is the work of a dumb dinobaby. No smart software required.
In my opinion, there should be one digital online service. This means one search system, one place to get apps, one place to obtain real time “real” news, and one place to buy and sell advertising. Wouldn’t that make life much easier for the company who owned the “one place.” If the information in “US Supreme Court Allows Order Forcing Google to Make App Store Reforms” is accurate, Google’s dream of becoming that “one place” has been interrupted.
The write up from a trusted source reports:
The declined on Monday [October 6, 2025] to halt key parts of a judge’s order requiring Alphabet’s, Google to make major changes to its app store Play, as the company prepares to appeal a decision in a lawsuit brought by “Fortnite” maker Epic Games. The justices turned down Google’s request to temporarily freeze parts of the injunction won by Epic in its lawsuit accusing the tech giant of monopolizing how consumers access apps on Android devices and pay for transactions within apps.
Imagine the nerve of this outfit. These highly trained, respected legal professionals did not agree with Google’s rock-solid, diamond-hard arguments. Imagine a maker of electronic games screwing up one of the modules in the Google money and data machine. The nerve.
Thanks, MidJourney, good enough.
The write up adds:
Google in its Supreme Court filing said the changes would have enormous consequences for more than 100 million U.S. Android users and 500,000 developers. Google said it plans to file a full appeal to the Supreme Court by October 27, which could allow the justices to take up the case during their nine-month term that began on Monday.
The fact that the government is shut down will not halt, impair, derail, or otherwise inhibit Google’s quest for the justice it deserves. If the case can be extended, it is possible the government legal eagles will seek new opportunities in commercial enterprises or just resign due to the intellectual demands of their jobs.
The news story points out:
Google faces other lawsuits from government, consumer and commercial plaintiffs challenging its search and advertising business practices.
It is difficult to believe that a firm with such a rock solid approach to business can find itself swatting knowledge gnats. Onward to the “one service.” Is that on a Google T shirt yet?
Stephen E Arnold, October 17, 2025
A Newsletter Firm Appears to Struggle for AI Options
October 17, 2025
This essay is the work of a dumb dinobaby. No smart software required.
I read “Adapting to AI’s Evolving Landscape: A Survival Guide for Businesses.” The premise of the article will be music to the ears of venture funders and go-go Silicon Valley-type AI companies. The write up says:
AI-driven search is upending traditional information pathways and putting the heat on businesses and organizations facing a web traffic free-fall. Survival instincts have companies scrambling to shift their web strategies — perhaps ending the days of the open internet as we know it. After decades of pursuing web-optimization strategies that encouraged high-volume content generation, many businesses are now feeling that their content-marketing strategies might be backfiring.
I am not exactly sure about this statement. But let’s press forward.
I noted this passage:
Without the incentive of web clicks and ad revenue to drive content creation, the foundation of the web as a free and open entity is called into question.
Okay, smart software is exploiting the people who put up SEO-tailored content to get sales leads and hopefully make money. From my point of view, technology can be disruptive. The impacts, however, can be positive or negative.
What’s the fix if there is one? The write up offers these thought starters:
- Embrace micro transactions. [I suppose this is good if one has high volume. It may not be so good if shipping and warehouse costs cannot be effectively managed. Vendors of high ticket items may find a micro-transaction for a $500,000 per year enterprise software license tough to complete via Venmo.]
- Implement a walled garden. [That works if one controls the market. Google wants to “register” Android developers. I think Google may have an easier time with the walled-garden tactic than a local bakery specializing in treats for canines.]
- Accepts the monopolies. [You have a choice?]
My reaction to the write up is that it does little to provide substantive guidance as smart software continues to expand like digital kudzu. What is important is that the article appears in the consumer oriented publication from Kiplinger of newsletter fame. Unfortunately the article makes clear that Kiplinger is struggling to find a solution to AI. My hunch is that Kiplinger is looking for possible solutions. The firm may want to dig a little deeper for options.
Stephen E Arnold, October 17, 2025
Ford CEO and AI: A Busy Time Ahead
October 17, 2025
This essay is the work of a dumb dinobaby. No smart software required.
Ford’s CEO is Jim Farley. He has his work cut out for him. First, he has an aluminum problem. Second, he has an F 150 production disruption problem. Third, he has a PR problem. There’s not much he can do about the interruption of the aluminum supply chain. No parts means truck factories in Kentucky will have to go slow or shut down. But the AI issue is obviously one that is of interest to Ford stakeholders.
He [Mr. Farley] says the jobs most at risk aren’t the ones on the assembly line, but the ones behind a desk. And in his view, the workers wiring machines, operating tools, and physically building the infrastructure could turn out to be the most critical group in the economy. Farley laid it out bluntly back in June at the Aspen Ideas Festival during an interview with author Walter Isaacson. “Artificial intelligence is going to replace literally half of all white-collar workers,” he said. “AI will leave a lot of white-collar people behind.” He wasn’t speculating about a distant future either. Farley suggested the shift is already unfolding, and the implications could be sweeping.
With the disruption of the aluminum supply chain, Ford now will have to demonstrate that AI has indeed reduced white collar headcount. The write up says:
For him, it comes down to what AI can and cannot do. Office tasks — from paperwork to scheduling to some forms of analysis — can be automated with growing speed. But when it comes to factories, data centers, supply chains, or even electric vehicle production, someone still has to build, install, and maintain it…
The Ford situation is an interesting one. AI will reduce costs because half Ford’s white collar workers will no longer be on the payroll. But with supply chain interruptions and the friction in retail and lease sales, Ford has an opportunity to demonstrate that AI will allow a traditional manufacturing company to weather the current thunderstorm and generate financial proof that AI can offset exogenous events.
How will Ford perform? This is worth watching because it will provide some useful information for firms looking for a way to cut costs, improve operations, and balance real-world business. AI delivering one kind of financial benefit and traditional blue-collar workers unable to produce products because of supply chain issues. Quite a balancing act for Ford leadership.
Stephen E Arnold, October 17, 2025
Another Better, Faster, Cheaper from a Big AI Wizard Type
October 16, 2025
This essay is the work of a dumb dinobaby. No smart software required.
Cheap seems to be the hot button for some smart software people. I spotted a news item in the Russian computer feed I get called in English “Former OpenAI Engineer Andrey Karpaty Launched the Nanochat Neural Network Generator. You Can Make Your ChatGPT in a Few Hours.” The project is on GitHub at https://github.com/karpathy/nanochat.
The GitHub blurb says:
This repo is a full-stack implementation of an LLM like ChatGPT in a single, clean, minimal, hackable, dependency-lite codebase. Nanochat is designed to run on a single 8XH100 node via scripts like speedrun.sh, that run the entire pipeline start to end. This includes tokenization, pretraining, finetuning, evaluation, inference, and web serving over a simple UI so that you can talk to your own LLM just like ChatGPT. Nanochat will become the capstone project of the course LLM101n being developed by Eureka Labs.
The open source bundle includes:
- A report service
- A Rust-coded tokenizer
- A FineWeb dataset and tools to evaluate CORE and other metrics for your LLM
- Some training gizmos like SmolTalk, tests, and tool usage information
- A supervised fine tuning component
- Training Group Relative Policy Optimization and the GSM8K (a reinforcement learning technique), a benchmark dataset consisting of grade school math word problems
- An output engine.
Is it free? Yes. Do you have to pay? Yep. About US$100 is needed? Launch speedrun.sh, and you will have to be hooked into a cloud server or a lot of hardware in your basement to do the training. A low-ball estimate for using a cloud system is about US$100, give or take some zeros. (Think of good old Amazon AWS and its fascinating billing methods.) To train such a model, you will need a server with eight Nvidia H100 video cards. This will take about 4 hours and about $100 when renting equipment in the cloud. The need for the computing resources becomes evident when you enter the command speedrun.sh.
Net net: As the big dogs burn box cars filled with cash, Nanochat is another player in the cheap LLM game.
Stephen E Arnold, October 16, 2025
Apple: Waking Up Is Hard to Do
October 16, 2025
This essay is the work of a dumb dinobaby. No smart software required.
I read a letter. I think this letter or at least parts of it were written by a human. These days it can be tough to know. The letter appeared in “Wiley Hodges’s Open Letter to Tim Cook Regarding ICEBlock.” Mr. Hodge, according to the cited article, retired from Apple, the computer and services company in 2022.
The letter expresses some concern that Apple removed an app from the Apple online store. Here’s a snippet from the “letter”:
Apple and you are better than this. You represent the best of what America can be, and I pray that you will find it in your heart to continue to demonstrate that you are true to the values you have so long and so admirably espoused.
It does seem to me that Apple is a flexible outfit. The purpose of the letter is unknown to me. On the surface, it is a single former employee’s expression of unhappiness at how “leadership” leads and deciders “decide.” However, below the surface it a signal that some people thought a for profit, pragmatic, and somewhat frisky Fancy Dancing organization was like Snow White, the Easter bunny, or the Lone Ranger.
Thanks, Venice.ai. Good enough.
Sorry. That’s not how big companies work or many little companies for that matter. Most organizations do what they can to balance a PR image with what the company actually does. Examples range from arguing via sleek and definitely expensive lawyers that what they do does not violate laws. Also, companies work out deals. Some of these involve doing things to fit in to the culture of a particular company. I have watched money change hands when registering a vehicle in the government office in Sao Paulo. These things happen because they are practical. Apple, for example, has an interesting relationship with a certain large country in Asia. I wonder if there is a bit of the old soft shoe going on in that region of the world.
These are, however, not the main point of this blog post. There cited article contains this statement:
Hodges, earlier in his letter, makes reference to Apple’s 2016 standoff with the FBI over a locked iPhone belonging to the mass shooter in San Bernardino, California. The FBI and Justice Department pressured Apple to create a version of iOS that would allow them to backdoor the iPhone’s passcode lock. Apple adamantly refused.
Okay, the time delta is nine years. What has changed? Obviously social media, the economic situation, the relationship among entities, and a number of lawsuits. These are the touchpoints of our milieu. One has to surf on the waves of change and the ripples and waves of datasphere.
But I want to highlight several points about my reaction to the this blog post containing the Hodge’s letter:
- Some people are realizing that their hoped-for vision of Apple, a publicly traded company, is not the here-and-now Apple. The fairy land of a company that cares is pretty much like any other big technology outfit. Shocker.
- Apple is not much different today than it was nine years ago. Plucking an example which positioned the Cupertino kids as standing up for an ideal does not line up with the reality. Technology existed then to gain access to digital devices. Believing the a company’s PR reflected reality illustrates how crazy some perceptions are. Saying is not doing.
- Apple remains to me one of the most invasive of the technology giants. The constant logging in, the weirdness of forcing people to have data in the iCloud when those people do not know the data are there or want it there for that matter, the oddball notifications that tell a user that an “new device” is connected when the iPad has been used for years, and a few other quirks like hiding files are examples of the reality of the company.
News flash: Apple is like the other Silicon Valley-type big technology companies. These firms have a game plan of do it and apologize. Push forward. I find it amusing that adults are experiencing the same grief as a sixth grader with a crush on the really cute person in home room. Yep, waking up is hard to do. Stop hitting the snooze alarm and join the real world.
Net net: The essay is a hoot. Here is an adult realizing that there is no Santa with apparently tireless animals and dwarfs at the North Pole. The cited article contains what appears to be another expression of annoyance, anger, and sorrow that Apple is not what the humans thought it was. Apple is Apple, and the only change agent able to modify the company is money and/or fear, a good combo in my experience.
Stephen E Arnold, October 16, 2025
Deepseek: Why Trust Any Smart Software?
October 16, 2025
This essay is the work of a dumb dinobaby. No smart software required.
We have completed our work on my new book “The Telegram Labyrinth.” In the course of researching and writing about Pavel Durov’s online messaging system, we learned one thing: Software is not what it seems to the user. Most Telegram users believe that Telegram is end to end encrypted. It is, but only if the user goes through some hoops. The vast majority of users don’t go through hoops. Those millions upon millions of users know much about the third-party bots chugging away in Groups and Channels (public and private). Even fewer users realize that a service charge is applied to each monetary transaction in the Telegram system. That money flows to the GOAT (greatest of all time) technical wizard, Pavel Durov and some close associates. Who knew?
I read “The Demonization of Deepseek: How NIST Turned Open Science into a Security Scare.” The write up focuses on a study or analysis conducted by what used to be the National Bureau of Standards. (I loved those traffic jams on Quince Orchard Road in Gaithersburg, Maryland.) The software put under the NIST (National Institute of Science & Technology) is the China-linked Deepseek smart software.
The cited article discusses the NIST study. Let’s see what it says about the China-linked artificial intelligence system. Presumably Deepseek did more with less; that is, the idea was to demonstrate that Chinese innovation could make US methods of large language models. The result would be better, faster, and cheaper. Cheap has a tendency to win in some product and service categories. Also, “good enough” is a winner in today’s market. (How about the reliability of some of those 2025 automobiles and trucks?)
The write up says:
NIST’s recent report on Deepseek is not a neutral technical evaluation. It is a political hit piece disguised as science. There is no evidence of backdoors, spyware, or data exfiltration. What is really happening is the U.S. government using fear and misinformation to sabotage open science, open research, and open source. They are attacking gifts to humanity with politics and lies to protect corporate power and preserve control. Deepseek’s work is a genuine contribution to human knowledge, and it is being discredited for reasons that have nothing to do with security.
Okay, that’s clear.
Let’s look at how the cited write up positions Deepseek:
Deepseek built competitive AI models. Not perfect, but impressive given their budget. They spent far less than OpenAI or Anthropic and still achieved near-frontier performance. Then they open-sourced everything under Apache 2.0.
The point of the write up is that analysis has been politicized. This is an interesting allegation. I am not confident that any “objective” analysis is indeed without spin. Remember those reports about smoking cigarettes and the work of the Tobacco Institute. (I am a dinobaby, but I remember.)
The write up does identify three concerns a user of Deepseek should have. Let me quote from the cited article:
- Using Deepseek’s API: If you send sensitive data to Deepseek’s hosted service, that data goes through Chinese infrastructure. This is a real data sovereignty issue, the same as using any foreign cloud provider.
- Jailbreak susceptibility: If you’re building production applications, you need to test ANY model for vulnerabilities and implement application-level safeguards. Don’t rely solely on model guardrails. Also – use an inference time guard model (such as LlamaGuard or Qwen3Guard) to classify and filter both prompts and responses.
- Bias and censorship: All models reflect their training data. Be aware of this regardless of which model you use.
Let me offer several observations:
- Most people are unaware of what can be accomplished from software use. Assumptions about what it does and does not do are dangerous. We have tested Deepseek running locally. It is okay. This means it can do some things well like translate a passage in English into German. It has no clue about timely issues because most LLMs are not updated in near real time. Some are, but others are not. Who needs timely information when cheating on a high school essay? Answer: no one.
- The write up focuses on Deepseek, but its implications are much more broad. I think that the mindless write ups from consulting firms and online magazines is a very big problem. Critical thinking is just not the common. It is a problem in the US but other countries have this blind spot as well.
- The idea that political perceptions alter what should be an objective analysis is troubling to me. I have written a number of reports for government agencies; for example, a report about Japan’s obsession with a database industry for the Office of Technology Assessment. Yep, I am a dinobaby remember. I may have been right or wrong in my report, but I was not influenced by any political concept or actor. I could have been because I did a stint in the office of Admiral / Congressman Craig Hosmer. My OTA work was not part of the “game” for me.
Net net: Trust is important. I think it is being eroded. I also believe that there are few people who present information without fear or favor. Now here’s the key part of my perception: One cannot trust smart software or any of the programmer assembled, hidden threshold, and masked training methods that go into these confections. More critical thinking is needed. A deceptive business practice if well crafted cannot be perceived. Remember Telegram Messenger is 13 years young and users of the system don’t have much awareness of bots, mini apps, and dapps. What don’t people know about smart software?
Stephen E Arnold, October 16, 2025
Hey, Pew, Wanna Bet?
October 16, 2025
This essay is the work of a dumb dinobaby. No smart software required.
My Telegram Labyrinth book is almost over the finish line. I include some discussion of online gambling in Telegram. Of particular interest to me and my research team was kiddie games. A number of these reward the young child with crypto tokens. Get enough tokens and the game provides the player with options. A couple of these options point the kiddie directly to an online casino running in Telegram Messenger. What happens next? A few players win. Others lose. The approach is structured and intentional. The goal of some of these fun games is addicting youngsters to online gambling via crypto.
Nifty. Telegram has been up and running since 2013. In the last few years, online gambling has become a part of the organization’s strategic vision. Anyone, including a child with a mobile device, can play online gambling on Telegram. From Telegram’s point of view, this is freedom. From a parent who discovers a financial downside from their child’s play, this is stressful.
I read “Americans Increasingly See Legal Sports Betting As a Bad Thing for Society and Sports.” The Pew research outfit dug into online gambling. What did the number crunchers learn? Here are a handful of findings:
- More Americans view legal sports betting as bad for society and sports. (Hey, addiction is a problem. Who knew?)
- One-fifth of Americans bet online. The good news is that sports betting is not growing. (Is that why advertising for online gaming seems to be more prevalent?)
- 47 percent of men under 30 say legal sports betting is a bad thing, up from 22 percent who said this in 2022.
Now check out this tough-to-read graphic:
Views of online gambling vary within the demographic groups in the sample. I noted that old people (dinobabies like me) do not wager as frequently as those between the ages of 18 and 29. I wonder if the age of the VCs pumping money into AI come from this demographic. Betting seems okay to more of them. Ask someone over 65, only 12 percent of those you query will say, “Great idea.”
I would argue that online gambling is readily available. More services are emulating the Telegram model. The Pew study seemed to ignore the target demographic for the users of the Telegram kiddie gambling games. That is a whiff to me. But will anyone care? Only the parents and it may take years for the research firms to figure out where the key change is taking place.
Stephen E Arnold, October 16, 2025
-
- Subscribe to Beyond Search
Feature archive
News archive
-
