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
Who Is Afraid of the Big Bad AI Wolf? Mr. Beast Perhaps?
October 14, 2025
This essay is the work of a dumb dinobaby. No smart software required.
The story “MrBeast Warns of ‘Scary Times’ as AI Threatens YouTube Creators” is apparently about You Tube creators. Mr. Beast, a notable YouTube personality, is the source of the information. Is the article about YouTube creators? Yep, but it is also about Mr. Beast.
The write up says:
MrBeast may not personally face the threat of being replaced by AI as his brand thrives on large-scale, real-world stunts that rely on authenticity and human emotion. But his concern runs deeper than self-preservation. It’s about the millions of smaller creators who depend on platforms like YouTube to make a living. As one of the most influential figures on the internet, his words carry weight. The 27-year-old recently topped Forbes’ 2025 list of highest-earning creators, earning roughly $85 million and building a following of over 630 million across platforms.
Okay, Mr. Beast’s fame depended on YouTube. He is still in the YouTube fold. However, he has other business enterprises. He recognizes that smart software could create problems for creators.
I think smart software is another software tool. It is becoming a utility like a PDF editor.
The problem with Mr. Beast’s analysis is that it appears to be focused on other creators. I am not so sure. I think the comments presented in the write up reveal more about Mr. Beast than they do about the “other” creators. One example is:
“When AI videos are just as good as normal videos, I wonder what that will do to YouTube and how it will impact the millions of creators currently making content for a living… scary times,” MrBeast — whose real name is Jimmy Donaldson — wrote on X.
I am no expert on human psychology, but I see the use of the word “impact” and “scary” as a glimpse of what Mr. Beast is thinking. His production costs allegedly rival those of traditional commercial video outfits. The ideas and tropes have become increasingly strained and bizarre. YouTube acts in a unilateral way and outputs smarm to the creators desperate to know why the flow of their money has been reduced if not cut off. Those disappearing van life videos are just one example of how video magnets can melt down and be crushed under the wheels of the Google bus.
My thought is that Google will use AI to create alterative Mr. Beast-type videos with AI. Then squeeze the Mr. Beast type creators and let the traffic flow to Mother Google. No royalties required, so Google wins. Mr. Beast-type creators can find their future and money elsewhere. Simple.
Stephen E Arnold, October 14, 2025
The Ka-Ching Game: The EU Rings the Big Tech Cash Register Tactic
October 14, 2025
This essay is the work of a dumb dinobaby. No smart software required.
The unusually tinted Financial Times published another “they will pay up and change, really” write up. The article is “Meta and Apple Close to Settling EU Cases.” [Note: You have to pay to read the FT’s orange write up.] The main idea is that these U S big technology outfits are cutting deals. The objective is to show that these two firms are interested in making friends with European Commission professionals. The combination of nice talk and multi-million euro payments should do the trick. That’s the hope.
Thanks, Venice.ai. Good enough.
The cute penalty method the EU crafted involved daily financial penalties for assorted alleged business practices. The penalties had an escalator feature. If the U S big tech outfits did not comply or pretend to comply, then the EU could send an invoice for up to five percent of the firm’s gross revenues. Could the E U collect? Well, that’s another issue. If Apple leaves the E U, the elected officials would have to use an Android mobile. If Meta departed, the elected officials would have to listen to their children’s complaints about their ruined social life. I think some grandmothers would be honked if the flow of grandchildren pictures were interrupted. (Who needs this? Take the money, Christina.)
Several observations:
- The EU will take money; the EU will cook up additional rules to make the Wild West outfits come to town but mostly behave
- The U S big tech companies will write a check, issue smarmy statements, and do exactly what they want to do. Decades of regulatory inefficacy creates certain opportunities. Some U S outfits spot those and figure out how to benefit from lack of action or ineptitude
- The efforts to curtail the U S big tech companies have historically been a rinse and repeat exercise. That won’t change.
The problem for the EU with regard to the U S is different from the other challenges it faces. In my opinion, the E U like other countries is:
- Unprepared for the new services in development by U S firms. I address these in a series of lectures I am doing for some government types in Colorado. Attendance at the talks is restricted, so I can’t provide any details about these five new services hurtling toward the online markets in the U S and elsewhere
- Unable to break its cycle of clever laws, U S company behavior, and accept money. More is needed. A good example of how one country addressed a problem online took place in France. That was a positive, decisive action and will interrupt the flow of cash from fines. Perhaps more E U countries should consider this French approach?
- The Big Tech outfits are not constrained by geographic borders. In case you have not caught up with some of the ideas of Silicon Valley, may I suggest you read the enervating and somewhat weird writings of a fellow named René Gerard?
Net net: Yep, a deal. No big surprise. Will it work? Nope.
Stephen E Arnold, October 15, 2025
AI and America: Not a Winner It Seems
October 13, 2025
This essay is the work of a dumb dinobaby. No smart software required.
Los Alamos National Laboratory perceives itself as one of the world’s leading science and research facilities. Jason Pruet is the Director of Los Alamos’s National Security AI Office and he was interviewed in “Q&A With Jason Pruet.” Pruet’s job is to prepare the laboratory for AI integration. He used to view AI as another tool for advancement, but Pruet now believes AI would disrupt the fundamental landscape of science, security, and more.
In the interview, Pruet states that the US government invested more in AI than any time in the past. He compared this investment to the World War II paradigm of science for the public good. Pruet explained that before the war, the US government wasn’t involved with science. After the war, Los Alamos shifted the dynamic and shaped modern America’s dedication to science, engineering, etc.
One of the biggest advances in AI technology is transformer architecture that allows huge progress to scale AI models, especially for mixing different information types. Pruet said that China is treating AI like a general purpose technology (i.e electricity) and they’ve launched a National AI strategy. The recent advances in AI are changing power structures. It’s turning into a new international arms race but that might not be the best metaphor:
“[Pruet:] All that said, I’m increasingly uncomfortable viewing this through the lens of a traditional arms race. Many thoughtful and respected people have emphasized that AI poses enormous risks for humanity. There are credible reports that China’s leadership has come to the same view, and that internally, they are trying to better balance the potential risks rather than recklessly seek advantage. It may be that the only path for managing these risks involves new kinds of international collaborations and agreements.”
Then Pruet had this to say about the state of the US’s AI development:
“Like we’re behind. The ability to use machines for general-purpose reasoning represents a seminal advance with enormous consequences. This will accelerate progress in science and technology and expand the frontiers of knowledge. It could also pose disruptions to national security paradigms, educational systems, energy, and other foundational aspects of our society. As with other powerful general-purpose technologies, making this transition will depend on creating the right ecosystem. To do that, we will need new kinds of partnerships with industry and universities.”
The sentiment seems to be focused on going faster and farther than any other country in the AI game. With the circular deals OpenAI has been crafting, AI seems to be more about financial innovation than technical innovation.
Whitney Grace, October 13, 2025
Weaponization of LLMs Is a Thing. Will Users Care? Nope
October 10, 2025
This essay is the work of a dumb dinobaby. No smart software required.
A European country’s intelligence agency learned about my research into automatic indexing. We did a series of lectures to a group of officers. Our research method, the results, and some examples preceded a hands on activity. Everyone was polite. I delivered versions of the lecture to some public audiences. At one event, I did a live demo with a couple of people in the audience. Each followed a procedure, and I showed the speed with which the method turned up in the Google index. These presentations took place in the early 2000s. I assumed that the behavior we discovered would be disseminated and then it would diffuse. It was obvious that:
- Weaponized content would be “noted” by daemons looking for new and changed information
- The systems were sensitive to what I called “pulses” of data. We showed how widely used algorithms react to sequences of content
- The systems would alter what they would output based on these “augmented content objects.”
In short, online systems could be manipulated or weaponized with specific actions. Most of these actions could be orchestrated and tuned to have maximum impact. One example in my talks was taking a particular word string and making it turn up in queries where one would not expect that behavior. Our research showed that a few as four weaponized content objects orchestrated in a specific time interval would do the trick. Yep, four. How many weaponized write ups can my local installation of LLMs produce in 15 minutes? Answer: Hundreds. How long does it take to push those content objects into information streams used for “training.” Seconds.
Fish live in an environment. Do fish know about the outside world? Thanks, Midjourney. Not a ringer but close enough in horseshoes.
I was surprised when I read “A Small Number of Samples Can Poison LLMs of Any Size.” You can read the paper and work through the prose. The basic idea is that selecting or shaping training data or new inputs to recalibrate training data can alter what the target system does. I quite like the phrase “weaponize information.” Not only does the method work, it can be automated.
What’s this mean?
The intentional selection of information or the use of a sample of information from a domain can generate biases in what the smart software knows, thinks, decides, and outputs. Dr. Timnit Gebru and her parrot colleagues were nibbling around the Google cafeteria. Their research caused the Google to put up a barrier to this line of thinking. My hunch is that she and her fellow travelers found that content that is representative will reflect the biases of the authors. This means that careful selection of content for training or updating training sets can be steered. That’s what the Anthropic write up make clear.
Several observations are warranted:
- Whoever selects training data or the information used to update and recalibrate training data can control what is displayed, recommended, or included in outputs like recommendations
- Users of online systems and smart software are like fish in a fish bowl. The LLM and smart software crowd are the people who fill the bowl and feed the fish. Fish have a tough time understanding what’s outside their bowl. I don’t like the word “bubble” because these pop. An information fish bowl is tough to escape and break.
- As smart software companies converge into essentially an oligopoly using the types of systems I described in the early 2000s with some added sizzle from the Transformer thinking, a new type of information industrial complex is being assembled on a very large scale. There’s a reason why Sam AI-Man can maintain his enthusiasm for ChatGPT. He sees the potential of seemingly innocuous functions like apps within ChatGPT.
There are some interesting knock on effects from this intentional or inadvertent weaponization of online systems. One is that the escalating violent incidents are an output of these online systems. Inject some René Girard-type content into training data sets. Watch what those systems output. “Real” journalists are explaining how they use smart software for background research. Student uses online systems without checking to see if the outputs line up with what other experts say. What about investment firms allowing smart software to make certain financial decisions.
Weaponize what the fish live in and consume. The fish are controlled and shaped by weaponized information. How long has this quirk of online been known? A couple of decades, maybe more. Why hasn’t “anything” been done to address this problem? Fish just ask, “What problem?”
Stephen E Arnold, October x, 2025
I spotted
AI Has a Secret: Humans Do the Work
October 10, 2025
A key component of artificial intelligence output is not artificial at all. The Guardian reveals “How Thousands of ‘Overworked, Underpaid’ Humans Train Google’s AI to Seem Smart.” From accuracy to content moderation, Google Gemini and other AI models rely on a host of humans employed by third-party contractors. Humans whose jobs get harder and harder as they are pressured to churn through the work faster and faster. Gee, what could go wrong?
Reporter Varsha Bansal relates:
“Each new model release comes with the promise of higher accuracy, which means that for each version, these AI raters are working hard to check if the model responses are safe for the user. Thousands of humans lend their intelligence to teach chatbots the right responses across domains as varied as medicine, architecture and astrophysics, correcting mistakes and steering away from harmful outputs.”
Very important work—which is why companies treat these folks as valued assets. Just kidding. We learn:
“Despite their significant contributions to these AI models, which would perhaps hallucinate if not for these quality control editors, these workers feel hidden. ‘AI isn’t magic; it’s a pyramid scheme of human labor,’ said Adio Dinika, a researcher at the Distributed AI Research Institute based in Bremen, Germany. ‘These raters are the middle rung: invisible, essential and expendable.’”
And, increasingly, rushed. The write-up continues:
“[One rater’s] timer of 30 minutes for each task shrank to 15 – which meant reading, fact-checking and rating approximately 500 words per response, sometimes more. The tightening constraints made her question the quality of her work and, by extension, the reliability of the AI. In May 2023, a contract worker for Appen submitted a letter to the US Congress that the pace imposed on him and others would make Google Bard, Gemini’s predecessor, a ‘faulty’ and ‘dangerous’ product.”
And that is how we get AI advice like using glue on pizza or adding rocks to one’s diet. After those actual suggestions went out, Google focused on quality over quantity. Briefly. But, according to workers, it was not long before they were again told to emphasize speed over accuracy. For example, last December, Google announced raters could no longer skip prompts on topics they knew little about. Think workers with no medical expertise reviewing health advice. Not great. Furthermore, guardrails around harmful content were perforated with new loopholes. Bansal quotes Rachael Sawyer, a rater employed by Gemini contractor GlobalLogic:
“It used to be that the model could not say racial slurs whatsoever. In February, that changed, and now, as long as the user uses a racial slur, the model can repeat it, but it can’t generate it. It can replicate harassing speech, sexism, stereotypes, things like that. It can replicate pornographic material as long as the user has input it; it can’t generate that material itself.”
Lovely. It is policies like this that leave many workers very uncomfortable with the software they are helping to produce. In fact, most say they avoid using LLMs and actively discourage friends and family from doing so.
On top of the disillusionment, pressure to perform full tilt, and low pay, raters also face job insecurity. We learn GlobalLogic has been rolling out layoffs since the beginning of the year. The article concludes with this quote from Sawyer:
‘I just want people to know that AI is being sold as this tech magic – that’s why there’s a little sparkle symbol next to an AI response,’ said Sawyer. ‘But it’s not. It’s built on the backs of overworked, underpaid human beings.’
We wish we could say we are surprised.
Cynthia Murrell, October 10, 2025
Google Bricks Up Its Walled Garden
October 8, 2025
Google is adding bricks to its garden wall, insisting Android-app developers must pay up or stay out. Neowin declares, “Google’s Shocking Developer Decree Struggles to Justify the Urgent Threat to F-Droid.” The new edict requires anyone developing an app for Android to register with Google, whether or not they sell through its Play Store. Registration requires paying a fee, uploading personal IDs, and agreeing to Google’s fine print.
The measure will have a large impact on alternative app stores like F-Droid. That open-source publisher, with its focus on privacy, is particularly concerned about the requirements. In fact, it would rather shutter its project than force developers to register with Google. That would mean thousands of verified apps will vanish from the Web, never to be downloaded or updated again. F-Droid suspects Google’s motives are far from pure. Writer Paul Hill tells us:
“F-Droid has questioned whether forced registration will really solve anything because lots of malware apps have been found in the Google Play Store over the years, demonstrating that corporate gatekeeping doesn’t mean users are protected. F-Droid also points out that Google already defends users against malicious third-party apps with the Play Protect services which scan and disable malware apps, regardless of their origin. While not true for all alternative app stores, F-Droid already has strong security because the apps it includes are all open source that anyone can audit, the build logs are public, and builds are reproducible. When you submit an app to F-Droid, the maintainers help set up your repository properly so that when you publish an update to your code, F-Droid’s servers manually build the executable, this prevents the addition of any malware not in the source code.”
Sounds at least as secure as the Play Store to us. So what is really going on? The write-up states:
“The F-Droid project has said that it doesn’t believe that the developer registration is motivated by security. Instead, it thinks that Google is trying to consolidate power by tightening control over a formerly open ecosystem. It said that by tying application identifiers to personal ID checks and fees, it creates a choke point that restricts competition and limits user freedom.”
F-Droid is responding with a call for regulators to scrutinize this and other Googley moves for monopolistic tendencies. It also wants safeguards for app stores that wish to protect developers’ privacy. Who will win this struggle between independent app stores and the tech giant?
Cynthia Murrell, October 8, 2025
Slopity Slopity Slop: Nice Work AI Leaders
October 8, 2025
Remember that article about academic and scientific publishers using AI to churn out pseudoscience and crap papers? Or how about that story relating to authors’ works being stolen to train AI algorithms? Did I mention they were stealing art too?
Techdirt literally has the dirt on AI creating more slop: “AI Slop Startup To Flood The Internet With Thousands Of AI Slop Podcasts, Calls Critics Of AI Slop ‘Luddites’.” AI is a helpful tool. It’s great to assist with mundane things of life or improve workflows. Automation, however, has become the newest sensation. Big Tech bigwigs and other corporate giants are using it to line their purses, while making lives worse for others.
Note this outstanding example of a startup that appears to be interested in slop:
“Case in point: a new startup named Inception Point AI is preparing to flood the internet with a thousands upon thousands of LLM-generated podcasts hosted by fake experts and influencers. The podcasts cost the startup a dollar or so to make, so even if just a few dozen folks subscribe they hope to break even…”
They’ll make the episodes for less than a dollar. Podcasting is already a saturated market, but Point AI plans to flush it with garbage. They don’t care about the ethics. It’s going to be the Temu of podcasts. It would be great if people would flock to true human-made stuff, but they probably won’t.
Another reason we’re in a knowledge swamp with crocodiles.
Whitney Grace, October 9, 2025
The Future: Autonomous Machines
October 7, 2025
This essay is the work of a dumb dinobaby. No smart software required.
Does mass customization ring a bell? I cannot remember whether it was Joe Pine or Al Toffler who popularized the idea. The concept has become a trendlet. Like many high-technology trends, a new term is required to help communication the sizzle of “new.”
An organization is now an “autonomous machine.” The concept is spelled out in “This Is Why Your Company Is Transforming into an Autonomous Machine.” The write up asserts:
Industries are undergoing a profound transformation as products, factories, and companies adopt the autonomous machine design model, treating each element as an integrated system that can sense, understand, decide, and act (SUDA business operating system) independently or in coordination with other platforms.
I assume SUDA rhymes with OODA (Observe, Orient, Decide, Act), but who knows?
The inspiration for the autonomous machine may be Elon Musk, who allegedly said: “I’m really thinking of the factory like a product.” Gnomic stuff.
The write up adds:
The Tesla is a cyber-physical system that improves over time through software updates, learns from millions of other vehicles, and can predict maintenance needs before problems occur.
I think this is an interesting idea. There is a logical progression at work; specifically:
- An autonomous “factory”
- Autonomous “companies” but I think one could just think about organizations and not be limited to commercial enterprises
- Agentic enterprises.
The future appears to be like this:
The path to becoming an autonomous enterprise, using a hybrid workforce of humans and digital labor powered by AI agents, will require constant experimentation and learning. Go fast, but don’t hurry. A balanced approach, using your organization’s brains and hearts, will be key to success. Once you start, you will never go back. Adopt a beginner’s mindset and build. Companies that are built like autonomous machines no longer have to decide between high performance and stability. Thanks to AI integration, business leaders are no longer forced to compromise. AI agents and physical AI can help business leaders design companies like a stealth aircraft. The technology is ready, and the design principles are proven in products and production. The fittest companies are autonomous companies.
I am glad I am a dinobaby, a really old dinobaby. Mass customization alright. Oligopolies producing what they want for humans who are supposed to have a job to buy the products and services. Yeah.
Stephen E Arnold, October 7, 2025
-
- Subscribe to Beyond Search
Feature archive
News archive
-
