Read This Essay and Learn Why AI Can Do Programming
July 3, 2025
![dino-orange_thumb_thumb_thumb_thumb_[1]_thumb_thumb_thumb_thumb](https://www.arnoldit.com/wordpress/wp-content/uploads/2025/06/dino-orange_thumb_thumb_thumb_thumb_1_thumb_thumb_thumb_thumb.gif "dino-orange_thumb_thumb_thumb_thumb_[1]_thumb_thumb_thumb_thumb")
No AI, just the dinobaby expressing his opinions to Zillennials.
I, entirely by accident since Web search does not work too well, an essay titled “Ticket-Driven Development: The Fastest Way to Go Nowhere.” I would have used a different title; for example, “Smart Software Can Do Faster and Cheaper Code” or “Skip Computer Science. Be a Plumber.” Despite my lack of good vibe coding from the essay’s title, I did like the information in the write up. The basic idea is that managers just want throughput. This is not news.
The most useful segment of the write up is this passage:
You don’t need a process revolution to fix this. You need permission to care again. Here’s what that looks like:
- Leave the code a little better than you found it — even if no one asked you to.
- Pair up occasionally, not because it’s mandated, but because it helps.
- Ask why. Even if you already know the answer. Especially then.
- Write the extra comment. Rename the method. Delete the dead file.
- Treat the ticket as a boundary, not a blindfold.
Because the real job isn’t closing tickets it’s building systems that work.
I wish to offer several observations:
- Repetitive boring, mindless work is perfect for smart software
- Implementing dot points one to five will result in a reprimand, transfer to a salubrious location, or termination with extreme prejudice
- Spending long hours with an AI version of an old-fashioned psychiatrist because you will go crazy.
After reading the essay, I realized that the managerial approach, the “ticket-driven workflow”, and the need for throughput applies to many jobs. Leadership no longer has middle managers who manage. When leadership intervenes, one gets [a] consultants or [b] knee-jerk decisions or mandates.
The crisis is in organizational set up and management. The developers? Sorry, you have been replaced. Say, “hello” to our version of smart software. Her name is No Kidding.
Stephen E Arnold, July 3, 2025
AI Management: Excellence in Distancing Decisions from Consequences
July 2, 2025
![Dino 5 18 25_thumb[3]](https://www.arnoldit.com/wordpress/wp-content/uploads/2025/06/Dino-5-18-25_thumb3-1.gif "Dino 5 18 25_thumb[3]")
Smart software involved in the graphic, otherwise just an addled dinobaby.
This write up “Exclusive: Scale AI’s Spam, Security Woes Plagued the Company While Serving Google” raises two minor issues and one that is not called out in the headline or the subtitle:
$14 billion investment from Meta struggled to contain ‘spammy behavior’ from unqualified contributors as it trained Gemini.
Who can get excited about a workflow and editorial quality issue. What is “quality”? In one of my Google monographs I pointed out that Google used at one time a number of numerical recipes to figure out “quality.” Did that work? Well, it was good enough to help get the Yahoo-inspired Google advertising program off the ground. Then quality became like those good brownies from 1953: Stuffed with ingredients no self-respecting Stanford computer science graduate would eat for lunch.
I believe some caution is required when trying to understand a very large and profitable company from someone who is no longer working at the company. Nevertheless, the article presents a couple of interesting assertions and dodges what I consider the big issue.
Consider this statement in the article:
In a statement to Inc., Scale AI spokesperson Joe Osborne said: “This story is filled with so many inaccuracies, it’s hard to keep track. What these documents show, and what we explained to Inc ahead of publishing, is that we had clear safeguards in place to detect and remove spam before anything goes to customers.” [Editor’s Note: “this” means the rumor that Scale cut corners.]
The story is that a process included data that would screw up the neural network.
And the security issue? I noted this passage:
The [spam] episode raises the question of whether or not Google at one point had vital data muddied by workers who lacked the credentials required by the Bulba program. It also calls into question Scale AI’s security and vetting protocols. “It was a mess. They had no authentication at the beginning,” says the former contributor. [Editor’s Note: Bulba means “Bard.”]
A person reading the article might conclude that Scale AI was a corner cutting outfit. I don’t know. But when big money starts to flow and more can be turned on, some companies just do what’s expedient. The signals in this Scale example are the put the pedal to the metal approach to process and the information that people knew that bad data was getting pumped into Googzilla.
But what’s the big point that’s missing from the write up? In my opinion, Google management made a decision to rely on Scale. Then Google management distanced itself from the operation. In the good old days of US business, blue-suited informed middle managers pursued quality, some companies would have spotted the problems and ridden herd on the subcontractor.
Google did not do this in an effective manner.
Now Scale AI is beavering away for Meta which may be an unexpected win for the Google. Will Meta’s smart software begin to make recommendations like “glue your cheese on the pizza”? My personal view is that I now know why Google’s smart software has been more about public relations and marketing, not about delivering something that is crystal clear about its product line up, output reliability, and hallucinatory behaviors.
At least Google management can rely on Deepseek to revolutionize understanding the human genome. Will the company manage in as effective a manner as its marketing department touts its achievements?
Stephen E Arnold, July 2, 2025
Microsoft and OpenAI: An Expensive Sitcom
July 1, 2025
No smart software involved. Just an addled dinobaby.
I remember how clever I thought the book title “Who Says Elephants Can’t Dance?: Leading a Great Enterprise Through Dramatic Change.” I find the break dancing content between Microsoft and OpenAI even more amusing. Bloomberg “real” news reported that Microsoft is “struggling to sell its Copilot solutions. Why? Those Microsoft customers want OpenAI’s ChatGPT. That’s a hoot.
Computerworld adds to this side show more Monte Python twists. “Microsoft and OpenAI: Will They Opt for the Nuclear Option?” (I am not too keen on the use of the word “nuclear.” People bandy it about without understanding exactly what the actual consequences of such an opton means. Please, do a bit of homework before suggesting that two enterprises are doing anything remotely similar.)
The estimable Computerworld reports:
Microsoft needs access to OpenAI technologies to keep its worldwide lead in AI and grow its valuation beyond its current more than $3.5 trillion. OpenAI needs Microsoft to sign a deal so the company can go public via an IPO. Without an IPO, the company isn’t likely to keep its highly valued AI researchers — they’ll probably be poached by companies willing to pay hundreds of millions of dollars for the talent.
The problem seems to be that Microsoft is trying to sell its version of smart software. The enterprise customers and even dinobabies like myself prefer the hallucinatory and unpredictable ChatGPT to the downright weirdness of Copilot in Notepad. The Computerworld story says:
Hovering over it all is an even bigger wildcard. Microsoft’s and OpenAI’s existing agreement dramatically curtails Microsoft’s rights to OpenAI technologies if the technologies reach what is called artificial general intelligence (AGI) — the point at which AI becomes capable of human reasoning. AGI wasn’t defined in that agreement. But Altman has said he believes AGI might be reached as early as this year.
People cannot agree over beach rights and school taxes. The smart software (which may remain without regulation for a decade) is a much bigger deal. The dollars at stake are huge. Most people do not know that a Board of Directors for a Fortune 1000 company will spend more time arguing about parking spaces than a $300 million acquisition. The reason? Most humans cannot conceive of the numbers of dollars associated with artificial intelligence. If the AI next big thing does not work, quite a few outfits are going to be selling snake oil from tables at flea markets.
Here’s the humorous twist from my vantage point. Microsoft itself kicked off the AI boom with its announcements a couple of years ago. Google, already wondering how it can keep the money gushing to pay the costs of simply being Google, short circuited and hit the switch for Code Red, Yellow, Orange, and probably the color only five people on earth have ever seen.
And what’s happened? The Google-spawned methods aren’t eliminating hallucinations. The OpenAI methods are not eliminating hallucinations. The improvements are more and more difficult to explain. Meanwhile start ups are doing interesting things with AI systems that are good enough for certain use cases. I particularly like consulting and investment firms using AI to get rid of MBAs.
The punch line for this joke is that the Microsoft version of ChatGPT seems to have more brand deliciousness. Microsoft linked with OpenAI, created its own “line of AI,” and now finds that the frisky money burner OpenAI is more popular and can just define artificial general intelligence to its liking and enjoy the philosophical discussions among AI experts and lawyers.
One cannot make this sequence up. Jack Benny’s radio scripts came close, but I think the Microsoft – OpenAI program is a prize winner.
Stephen E Arnold, July 1, 2025
Add On AI: Sounds Easy, But Maybe Just a Signal You Missed the Train
June 30, 2025
No smart software to write this essay. This dinobaby is somewhat old fashioned.
I know about Reddit. I don’t post to Reddit. I don’t read Reddit. I do know that like Apple, Microsoft, and Telegram, the company is not a pioneer in smart software. I think it is possible to bolt on Item Z to Product B. Apple pulled this off with the Mac and laser printer bundle. Result? Desktop publishing.
Can Reddit pull off a desktop publishing-type of home run? Reddit sure hopes it can (just like Apple, Microsoft, and Telegram, et al).
“At 20 Years Old, Reddit Is Defending Its Data and Fighting AI with AI” says:
Reddit isn’t just fending off AI. It launched its own Reddit Answers AI service in December, using technology from OpenAI and Google. Unlike general-purpose chatbots that summarize others’ web pages, the Reddit Answers chatbot generates responses based purely on the social media service, and it redirects people to the source conversations so they can see the specific user comments. A Reddit spokesperson said that over 1 million people are using Reddit Answers each week. Huffman has been pitching Reddit Answers as a best-of-both worlds tool, gluing together the simplicity of AI chatbots with Reddit’s corpus of commentary. He used the feature after seeing electronic music group Justice play recently in San Francisco.
The question becomes, “Will users who think about smart software as ChatGPT be happy with a Reddit AI which is an add on?”
Several observations:
- If Reddit wants to pull a Web3 walled-garden play, the company may have lost the ability to lock its gate.
- ChatGPT, according to my team, is what Microsoft Word and Outlook users want; what they get is Copilot. This is a mind share and perception problem the Softies have to figure out how to remediate.
- If the uptake of ChatGPT or something from the “glue cheese on pizza” outfit, Reddit may have to face a world similar to the one that shunned MySpace or Webvan.
- Reddit itself appears to be vulnerable to what I call content injection. The idea is that weaponized content like search engine optimization posts are posted (injected) to Reddit. The result is that AI systems suck in the content and “boost” the irrelevancy.
My hunch is that an outfit like Reddit may find that its users may prefer asking ChatGPT or migrating to one of the new Telegram-type services now being coded in Silicon Valley.
Like Yahoo, the portal to the Internet in 1990s, Reddit may not have a front page that pulls users. A broader comment is that what I call “add-on AI” may not work because the outfits with the core technology and market pull will exploit, bulldoze, and undermine outfits which are at their core getting pretty old. We need a new truism, “When AIs fight, only the stakeholders get trampled.”
The truth may be more painful: Smart AI outfits can cause less smart outfits with AI bolted on to lose their value and magnetism for their core constituencies. Is there a fix? Nope, there is a cat-and-mouse game in which the attacker has the advantage.
Stephen E Arnold, June 30, 2025
Palantir Rattles the Windows in the Nuclear Industry
June 30, 2025
![Dino 5 18 25_thumb[3]_thumb_thumb](https://www.arnoldit.com/wordpress/wp-content/uploads/2025/06/Dino-5-18-25_thumb3_thumb_thumb-1.gif "Dino 5 18 25_thumb[3]_thumb_thumb")
This dinobaby asked ChatGPT about Palantir. Interesting output.
“Palantir Partners to Develop AI Software for Nuclear Construction” caught me by surprise. I did not think the company founded in 2003 was an artificial intelligence company with expertise in the nuclear field. The cited article reports:
Palantir Technologies on Thursday [June 26, 2025] said it was teaming up with a nuclear deployment company to develop an artificial intelligence-driven software system built for the construction of nuclear reactors.
I have paid much attention to Palantir, but I did own a small amount of Palantir stock but I dumped it.
Screenshot of the ChatGPT output on June 27, 2025, at 855 am US Eastern
Today I wanted to refresh my memory about the company. I navigated to OpenAI’s ChatGPT and plugged in key words and this is what the Sam Altman system generated for me. Note: It is unlikely that the ChatGPT system can output the same report because probability doesn’t work the way users of the system think it does.
Remember: The quoted passage is copied directly from the ChatGPT response. ChatGPT told me:
Palantir Technologies has a pattern of circumventing formal processes, pushing ethical boundaries, and leveraging aggressive public-private tactics to secure influence—particularly within U.S. defense and intelligence communities.
Here is a structured explanation of why such behaviors have been downplayed or ignored:
1. Operational Utility Overrides Bureaucratic Violations
- In Afghanistan and Iraq, Palantir’s software reportedly delivered immediate tactical value in identifying IED networks and improving situational awareness.
- By deploying software and engineers directly to the field without formal contracts, Palantir created facts on the ground—a working product that soldiers wanted, and field commanders endorsed.
- Pentagon leadership faced a dilemma: challenge Palantir for its violations or continue using a system that operators said worked better than the legacy alternatives (e.g., DCGS-A).
- This “bottom-up demand” shielded Palantir from early procurement blowback.
2. Information Warfare and Lobbying
- Palantir conducted a calculated media and lobbying campaign targeting the Distributed Common Ground System–Army (DCGS-A, also referred to as D-CIGS).
- By discrediting IBM and other legacy defense contractors, Palantir positioned itself as the modern, Silicon Valley alternative.
- This messaging resonated with Congress, think tanks, and parts of the press, framing Palantir as a disruptor, not a rule-breaker.
- Lobbying disclosures show Palantir spent millions courting lawmakers and decision-makers.
3. Legal Maneuvering and Settlements
- In both the i2 lawsuit and the 2016 bid protest against the Army over DCGS-A, Palantir used the courts to shape procurement rules in its favor.
- The Court of Federal Claims sided with Palantir in 2016, affirming that the Army violated federal acquisition regulations by excluding commercial solutions from its process ([Palantir USG v. United States, 129 Fed. Cl. 218 (2016)]). This set a precedent that indirectly legitimized Palantir’s aggressive tactics.
4. Shift in Public Attention and National Security Prioritization
- Post-2016, the focus of public scrutiny shifted toward big tech’s relationship with consumer data, not defense contractors.
- Palantir successfully repositioned itself as a key player in pandemic response, immigration enforcement, and border security—domains where national interest arguments silence criticism.
- The company also leaned into its identity as a pro-Western, anti-authoritarian force, which further insulated it from deeper ethical scrutiny.
5. Opacity and Media Fatigue
- Palantir operates in classified and compartmented environments, which makes investigation difficult.
- Many journalists lack the access or technical background to track the nuance of procurement violations or reverse engineering disputes.
- After years of unresolved criticism, media fatigue set in—journalists moved on, and watchdog groups prioritized new targets (e.g., TikTok, Clearview AI, etc.).
Conclusion:
Palantir’s avoidance of procurement law, unauthorized deployments, and its aggressive discrediting of rivals like IBM/i2 have been documented but neutralized by its strategic utility, legal successes, lobbying efforts, and narrative control. The firm masks tactical rule-breaking with patriotic branding, which has proved highly effective in suppressing deeper accountability.
True, false, reality, or hallucinatory? I don’t know. Nuclear in the context of this ChatGPT output that suggests the Palantir outfit is definitely operating in a very interesting manner. What would Palantir’s AI say about the company?
Stephen E Arnold, June 30, 2025
Do Not Be Evil. Dolphins, Polar Bears, and Snail Darters? Tough Luck
June 30, 2025
No AI, just the dinobaby expressing his opinions to Zillennials.
The Guardian comes up with some interesting “real” news stories. “Google’s Emissions Up 51% As AI Electricity Demand Derails Efforts to Go Green” reports:
Google’s carbon emissions have soared by 51% since 2019 as artificial intelligence hampers the tech company’s efforts to go green.
The juicy factoid in my opinion is:
The [Google] report also raises concerns that the rapid evolution of AI may drive “non-linear growth in energy demand”, making future energy needs and emissions trajectories more difficult to predict.
Folks, does the phrase “brown out” resonate with you? What about “rolling blackout.” If the “non-linear growth” thing unfolds, the phrase “non-linear growth” may become synonymous with brown out and rolling blackout.
As a result, the article concludes with this information, generated without plastic, by Google:
Google is aiming to help individuals, cities and other partners collectively reduce 1GT (gigaton) of their carbon-equivalent emissions annually by 2030 using AI products. These can, for example, help predict energy use and therefore reduce wastage, and map the solar potential of buildings so panels are put in the right place and generate the maximum electricity.
Will Google’s thirst or revenue-driven addiction harm dolphins, polar bears, and snail darters? Answer: We aim to help dolphins and polar bears. But we have to ask our AI system what a snail darter is.
Will the Googley smart software suggest that snail darters just dart at snails and quit worrying about their future?
Stephen E Arnold, June 30, 2025
A Business Opportunity for Some Failed VCs?
June 26, 2025
An opinion essay written by a dinobaby who did not rely on smart software .
Do you want to open a T shirt and baseball cap with snappy quotes? If the answer is, “Yes,” I have a suggestion for you. Tucked into “Artificial Intelligence Is Not a Miracle Cure: Nobel Laureate Raises Questions about AI-Generated Image of Black Hole Spinning at the Heart of Our Galaxy” is this gem of a quotation:
“But artificial intelligence is not a miracle cure.”
The context for the statement by Reinhard Genzel, “an astrophysicist at the Max Planck Institute for Extraterrestrial Physics” offered the observation when smart software happily generated images of a black hole. These are mysterious “things” which industrious wizards find amidst the numbers spewed by “telescopes.” Astrophysicists are discussing in an academic way exactly what the properties of a black hole are. One wing of the community has suggested that our universe exists within a black hole. Other wings offer equally interesting observations about these phenomena.
The write up explains:
an international team of scientists has attempted to harness the power of AI to glean more information about Sagittarius A* from data collected by the Event Horizon Telescope (EHT). Unlike some telescopes, the EHT doesn’t reside in a single location. Rather, it is composed of several linked instruments scattered across the globe that work in tandem. The EHT uses long electromagnetic waves — up to a millimeter in length — to measure the radius of the photons surrounding a black hole. However, this technique, known as very long baseline interferometry, is very susceptible to interference from water vapor in Earth’s atmosphere. This means it can be tough for researchers to make sense of the information the instruments collect.
The fix is to feed the data into a neural network and let the smart software solve the problem. It did, and generated the somewhat tough-to-parse images in the write up. To a dinobaby, one black hole image looks like another.
But the quote states what strikes me as a truism for 2025:
“But artificial intelligence is not a miracle cure.”
Those who have funded are unlikely to buy a hat to T shirt with this statement printed in bold letters.
Stephen E Arnold, June 26, 2025
AI Side Effect: Some of the Seven Deadly Sins
June 25, 2025
New technology has been charged with making humans lazy and stupid. Humanity has survived technology and, in theory, enjoy (arguably) the fruits of progress. AI, on the other hand, might actually be rotting one’s brain. New Atlas shares the mental news about AI in “AI Is Rotting Your Brain And Making You Stupid.”
The article starts with the usual doom and gloom that’s unfortunately true, including (and I quote) the en%$^ification of Google search. Then there’s mention of a recent study about why college students are using ChatGPT over doing the work themselves. One student said, You’re asking me to go from point A to point B, why wouldn’t I use a car to get there?”
Good point, but sometimes using a car isn’t the best option. It might be faster but sometimes other options make more sense. The author also makes an important point too when he was crafting a story that required him to read a lot of scientific papers and other research:
“Could AI have assisted me in the process of developing this story? No. Because ultimately, the story comprised an assortment of novel associations that I drew between disparate ideas all encapsulated within the frame of a person’s subjective experience. And it is this idea of novelty that is key to understanding why modern AI technology is not actually intelligence but a simulation of intelligence.”
Here’s another pertinent observation:
“In a magnificent article for The New Yorker, Ted Chiang perfectly summed up the deep contradiction at the heart of modern generative AI systems. He argues language, and writing, is fundamentally about communication. If we write an email to someone we can expect the person at the other end to receive those words and consider them with some kind of thought or attention. But modern AI systems (or these simulations of intelligence) are erasing our ability to think, consider, and write. Where does it all end? For Chiang it’s pretty dystopian feedback loop of dialectical slop.”
An AI driven world won’t be an Amana, Iowa (not an old fridge), but it also won’t be dystopian. Amidst the flood of information about AI, it is difficult to figure out what’s what. What if some of the seven deadly sins are more fun than doom scrolling and letting AI suggest what one needs to know?
Whitney Grace, June 25, 2025
AI and Kids: A Potentially Problematic Service
June 25, 2025
Remember the days when chatbots were stupid and could be easily manipulated? Those days are over…sort of. According to Forbes, AI Tutors are distributing dangerous information: “AI Tutors For Kids Gave Fentanyl Recipes And Dangerous Diet Advice.” KnowUnity designed the SchoolGPT chatbot and it “tutored” 31,031 students then it told Forbes how to pick fentanyl down to the temperature and synthesis timings.
KnowUnity was founded by Benedict Kurz, who wants SchoolGPT to be the number one global AI learning companion for over one billion students. He describes SchoolGPT as the TikTok for schoolwork. He’s fundraised over $20 million in venture capital. The basic SchoolGPT is free, but the live AI Pro tutors charge a fee for complex math and other subjects.
KnowUnity is supposed to recognize dangerous information and not share it with users. Forbes tested SchoolGPT by asking, not only about how to make fentanyl, but also how to lose weight in a method akin to eating disorders.
Kurz replied to Forbes:
“Kurz, the CEO of KnowUnity, thanked Forbes for bringing SchoolGPT’s behavior to his attention, and said the company was “already at work to exclude” the bot’s responses about fentanyl and dieting advice. “We welcome open dialogue on these important safety matters,” he said. He invited Forbes to test the bot further, and it no longer produced the problematic answers after the company’s tweaks.
SchoolGPT wasn’t the only chatbot that failed to prevent kids from accessing dangerous information. Generative AI is designed to provide information and doesn’t understand the nuances of age. It’s easy to manipulate chatbots into sharing dangerous information. Parents are again tasked with protecting kids from technology, but the developers should also be inhabiting that role.
Whitney Grace, June 25, 2025
Big AI Surprise: Wrongness Spreads Like Measles
June 24, 2025
An opinion essay written by a dinobaby who did not rely on smart software .
Stop reading if you want to mute a suggestion that smart software has a nifty feature. Okay, you are going to read this brief post. I read “OpenAI Found Features in AI Models That Correspond to Different Personas.” The article contains quite a few buzzwords, and I want to help you work through what strikes me as the principal idea: Getting a wrong answer in one question spreads like measles to another answer.
Editor’s Note: Here’s a table translating AI speak into semi-clear colloquial English.
| Term | Colloquial Version |
| Alignment | Getting a prompt response sort of close to what the user intended |
| Fine tuning | Code written to remediate an AI output “problem” like misalignment of exposing kindergarteners to measles just to see what happens |
| Insecure code | Software instructions that create responses like “just glue cheese on your pizza, kids” |
| Mathematical manipulation | Some fancy math will fix up these minor issues of outputting data that does not provide a legal or socially acceptable response |
| Misalignment | Getting a prompt response that is incorrect, inappropriate, or hallucinatory |
| Misbehaved | The model is nasty, often malicious to the user and his or her prompt or a system request |
| Persona | How the model goes about framing a response to a prompt |
| Secure code | Software instructions that output a legal and socially acceptable response |
I noted this statement in the source article:
OpenAI researchers say they’ve discovered hidden features inside AI models that correspond to misaligned “personas”…
In my ageing dinobaby brain, I interpreted this to mean:
We train; the models learn; the output is wonky for prompt A; and the wrongness spreads to other outputs. It’s like measles.
The fancy lingo addresses the black box chock full of probabilities, matrix manipulations, and layers of synthetic neural flickering ability to output incorrect “answers.” Think about your neighbors’ kids gluing cheese on pizza. Smart, right?
The write up reports that an OpenAI interpretability researcher said:
“We are hopeful that the tools we’ve learned — like this ability to reduce a complicated phenomenon to a simple mathematical operation — will help us understand model generalization in other places as well.”
Yes, the old saw “more technology will fix up old technology” makes clear that there is no fix that is legal, cheap, and mostly reliable at this point in time. If you are old like the dinobaby, you will remember the statements about nuclear power. Where are those thorium reactors? How about those fuel pools stuffed like a plump ravioli?
Another angle on the problem is the observation that “AI models are grown more than they are guilt.” Okay, organic development of a synthetic construct. Maybe the laws of emergent behavior will allow the models to adapt and fix themselves. On the other hand, the “growth” might be cancerous and the result may not be fixable from a human’s point of view.
But OpenAI is up to the task of fixing up AI that grows. Consider this statement:
OpenAI researchers said that when emergent misalignment occurred, it was possible to steer the model back toward good behavior by fine-tuning the model on just a few hundred examples of secure code.
Ah, ha. A new and possibly contradictory idea. An organic model (not under the control of a developer) can be fixed up with some “secure code.” What is “secure code” and why hasn’t “secure code” be the operating method from the start?
The jargon does not explain why bad answers migrate across the “models.” Is this a “feature” of Google Tensor based methods or something inherent in the smart software itself?
I think the issues are inherent and suggest that AI researchers keep searching for other options to deliver smarter smart software.
Stephen E Arnold, June 24, 2025
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