Grok and the Dog Which Ate the Homework
May 16, 2025
![dino-orange_thumb_thumb_thumb_thumb_[1]_thumb_thumb_thumb](https://www.arnoldit.com/wordpress/wp-content/uploads/2025/05/dino-orange_thumb_thumb_thumb_thumb_1_thumb_thumb_thumb-1.gif "dino-orange_thumb_thumb_thumb_thumb_[1]_thumb_thumb_thumb")
No AI, just the dinobaby expressing his opinions to Zillennials.
I remember the Tesla full self driving service. Is that available? I remember the big SpaceX rocket ship. Are those blowing up after launch? I now have to remember an “unauthorized modification” to xAI’s smart software Grok. Wow. So many items to tuck into my 80 year old brain.
I read “xAI Blames Grok’s Obsession with White Genocide on an Unauthorized Modification.” Do I believe this assertion? Of course, I believe everything I read on the sad, ad-choked, AI content bedeviled Internet.
Let’s look at the gems of truth in the report.
First, what is an unauthorized modification of a complex software humming along happily in Silicon Valley and— of all places — Memphis, a lovely town indeed. The unauthorized modification— whatever that is— caused a “bug in its AI-powered Grok chatbot.” If I understand this, a savvy person changed something he, she, or it was not supposed to modify. That change then caused a “bug.” I thought Grace Hopper nailed the idea of a “bug” when she pulled an insect from one of the dinobaby’s favorite systems, the Harvard Mark II. Are their insects at the X shops? Are these unauthorized insects interacting with unauthorized entities making changes that propagate more bugs? Yes.
Second, the malfunction occurs when “@grok” is used as a tag. I believe this because the “unauthorized modification” fiddled with the user mappings and jiggled scripts to allow the “white genocide” content to appear. This is definitely not hallucination; it is an “unauthorized modification.” (Did you know that the version of Grok available via x.com cannot return information from X.com (formerly Twitter) content. Strange? Of course not.
Third, I know that Grok, xAI, and the other X entities have “internal policies and core values.” Violating these is improper. The company — like other self regulated entities — “conducted a thorough investigation.” Absolutely. Coders at X are well equipped to perform investigations. That’s why X.com personnel are in such demand as advisors to law enforcement and cyber fraud agencies.
Finally, xAI is going to publish system prompts on Microsoft GitHub. Yes, that will definitely curtail the unauthorized modifications and bugs at X entities. What a bold solution.
The cited write up is definitely not on the same page as this dinobaby. The article reports:
A study by SaferAI, a nonprofit aiming to improve the accountability of AI labs, found xAI ranks poorly on safety among its peers, owing to its “very weak” risk management practices. Earlier this month, xAI missed a self-imposed deadline to publish a finalized AI safety framework.
This negative report may be expanded to make the case that an exploding rocket or a wonky full self driving vehicle is not safe. Everyone must believe X outfits. The company is a paragon of veracity, excellent engineering, and delivering exactly what it says it will provide. That is the way you must respond.
Stephen E Arnold, May 16, 2025
Google Advertises Itself
May 16, 2025
- The signals about declining search traffic warrant attention. SEO wizards, Google’s ad partners, and its own ad wizards depend on what once was limitless search traffic. If that erodes, those infrastructure costs will become a bit of a challenge. Profits and jobs depend on mindless queries.
- Google’s reaction to these signals indicates that the company’s “leadership” knows that there is trouble in paradise. The terse statement that the Cue comment about a decline in Apple to Google search traffic and this itty bitty ad are not accidents of fate. The Google once controlled fate. Now the fabled company is in a sticky spot like Sisyphus.
- The irony of Google’s problem stems from its own Transformer innovation. Released to open source, Google may be learning that its uphill battle is of its own creation. Nice work, “leadership.”
Apple AI Is AImless: Better Than Fire, Ready AIm
May 16, 2025
Apple’s Problems Rebuilding Siri
Apple is a dramatist worthy of reality TV. According to MSN, Apple’s leaders are fighting each other says the article, “New Siri Report Reveals Epic Dysfunction Within Apple — But There’s Hope.” There’s so many issues with Apple’s leaders that Siri 2.0 is delayed until 2026.
Managerial styles and backroom ambitions clashed within Apple’s teams. John Giannandrea heads Siri and has since 2018. He was hired to lead Siri and an AI group. Siri engineers claim they are treated like second class citizens. Their situation worsened when Craig Federighi’s software team released features and updates.
The two leaders are very different:
“Federighi was placed in charge of the Siri overhaul in March, alongside his number two Mike Rockwell — who created the Apple Vision Pro headset— as Apple attempts to revive its Siri revamp. The difference between Giannandrea and Federighi appears to be the difference between the tortoise and the hare. John is allegedly more of a listener and slow mover who lets those underneath him take charge of the work, especially his number two Robby Walker. He reportedly preferred incremental updates and was repeatedly cited as a problem with Siri development. Meanwhile, Federighi is described as brash and quick but very efficient and knowledgeable. Supposedly, Giannandrea’s “relaxed culture” lead to other engineers dubbing his AI team: AIMLess.”
The two teams are at each other’s throats. Projects are getting done but they’re arguing over the means of how to do them. Siri 2.0 is caught in the crossfire like a child of divorce. The teams need to put their egos aside or someone in charge of both needs to make them play nicely.
Whitney Grace, May 16, 2025
Retail Fraud Should Be Spelled RetAIl Fraud
May 16, 2025
As brick-and-mortar stores approach extinction and nearly all shopping migrates to the Web, AI introduces new vulnerabilities to the marketplace. Shocking, we know. Cyber Security Intelligence reports, “ChatGPT’s Image Generation Could Be Driving Retail Fraud.” We learn:
“The latest AI image generators can create images that look like real photographs as well as imagery from simple text prompts with incredible accuracy. It can reproduce documents with precisely matching formatting, official logos, accurate timestamps, and even realistic barcodes or QR codes. In the hands of fraudsters, these tools can be used to commit ‘return fraud’ by creating convincing fake receipts and proof-of-purchase documentation.”
But wait, there is more. The post continues:
“Fake proof of purchase documentation can be used to claim warranty service for products that are out of warranty or purchased through unauthorised channels. Fraudsters could also generate fake receipts showing purchases at higher values than was actually paid for – then requesting refunds to gift cards for the inflated amount. Internal threats also exist too, as employees can create fake expense receipts for reimbursement. This is particularly damaging for businesses with less sophisticated verification processes in place. Perhaps the scenario most concerning of all is that these tools can enable scammers to generate convincing payment confirmations or shipping notices as part of larger social engineering attacks.”
Also of concern is the increased inconvenience to customers as sites beef up their verification processes. After all, the write-up notes, The National Retail Federation found 70% of customers say a positive return experience makes them more likely to revisit a seller.
So what is a retail site to do? Well, author Doriel Abrahams is part of Forter, a company that uses AI to protect online sellers from fraud. Naturally, he suggests using a platform like his firm’s to find suspicious patterns without hindering legit customers too much. Is more AI the solution? We are not certain. If one were to go down that route, though, one should probably compare multiple options.
Cynthia Murrell, May 16, 2025
Complexity: Good Enough Is Now the Best Some Can Do at Google-
May 15, 2025
![dino-orange_thumb_thumb_thumb_thumb_[1]_thumb_thumb](https://www.arnoldit.com/wordpress/wp-content/uploads/2025/05/dino-orange_thumb_thumb_thumb_thumb_1_thumb_thumb-1.gif "dino-orange_thumb_thumb_thumb_thumb_[1]_thumb_thumb")
No AI, just the dinobaby expressing his opinions to Zillennials.
I read a post called “Working on Complex Systems: What I Learned Working at Google.” The write up is a thoughtful checklist of insights, lessons, and Gregorian engineering chants a “coder” learned in the online advertising company. I want to point out that I admire the amount of money and power the Google has amassed from its reinvention of the GoTo-Overture-Yahoo advertising approach.
A Silicon Valley executive looks at past due invoices. The government has ordered the company to be broken up and levied large fines for improper behavior in the marketplace. Thanks, ChatGPT. Definitely good enough.
The essay in The Coder Cafe presents an engineer’s learnings after Google began to develop products and services tangential to search hegemony, selling ads, and shaping information flows.
The approach is to differentiate complexity from complicated systems. What is interesting about the checklists is that one hearkens back to the way Google used to work in the Backrub and early pre-advertising days at Google. Let’s focus on complex because that illuminates where Google wants to direct its business, its professionals, its users, and the pesky thicket of regulators who bedevil the Google 24×7.
Here’s the list of characteristics of complex systems. Keep in mind that “systems” means software, programming, algorithms, and the gizmos required to make the non-fungible work, mostly.
- Emergent behavior
- Delayed consequences
- Optimization (local optimization versus global optimization)
- Hysteresis (I think this is cultural momentum or path dependent actions)
- Nonlinearity
Each of these is a study area for people at the Santa Fe Institute. I have on my desk a copy of The Origins of Order: Self-Organization and Selection in Evolution and the shorter Reinventing the Sacred, both by Stuart A. Kauffman. As a point of reference Origins is 700 pages and Reinventing about 300. Each of the cited articles five topics gets attention.
The context of emergent behavior in human- and probably some machine- created code is that it is capable of producing “complex systems.” Dr. Kauffman does a very good job of demonstrating how quite simple methods yield emergent behavior. Instead of a mess or a nice tidy solution, there is considerable activity at the boundaries of complexity and stability. Emergence seems to be associated with these boundary conditions: A little bit of chaos, a little bit of stability.
The other four items in the list are optimization. Dr. Kauffman points out is a consequence of the simple decisions which take place in the micro and macroscopic world. Non-linearity is a feature of emergent systems. The long-term consequences of certain emergent behavior can be difficult to predict. Finally, the notion of momentum keeps some actions or reactions in place through time units.
What the essay reveals, in my opinion, that:
- Google’s work environment is positioned as a fundamental force. Dr. Kauffman and his colleagues at the Santa Fe Institute may find some similarities between the Google and the mathematical world at the research institute. Google wants to be the prime mover; the Santa Fe Institute wants to understand, explain, and make useful its work.
- The lingo of the cited essay suggests that Google is anchored in the boundary between chaos and order. Thus, Google’s activities are in effect trials and errors intended to allow Google to adapt and survive in its environment. In short, Google is a fundamental force.
- The “leadership” of Google does not lead; leadership is given over to the rules or laws of emergence as described by Dr. Kauffman and his colleagues at the Santa Fe Institute.
Net net: Google cannot produce good products. Google can try to emulate emergence, but it has to find a way to compress time to allow many more variants. Hopefully one of those variants with be good enough for the company to survive. Google understands the probability functions that drive emergence. After two decades of product launches and product failures, the company remains firmly anchored in two chunks of bedrock:
First, the company borrows or buys. Google does not innovate. Whether the CLEVER method, the billion dollar Yahoo inspiration for ads, or YouTube, Bell Labs and Thomas Edison are not part of the Google momentum. Advertising is.
Second, Google’s current management team is betting that emergence will work at Google. The question is, “Will it?”
I am not sure bright people like those who work at Google can identify the winners from an emergent approach and then create the environment for those winners to thrive, grow, and create more winners. Gluing cheese to pizza and ramping up marketing for Google’s leadership in fields ranging from quantum computing to smart software is now just good enough. One final question: “What happens if the advertising money pipeline gets cut off?”
Stephen E Arnold, May 15, 2025
LLM Trade Off Time: Let Us Haggle for Useful AI
May 15, 2025
No AI, just the dinobaby expressing his opinions to Zellenials.
What AI fixation is big tech hyping now? VentureBeat declares, “Bigger Isn’t Always Better: Examining the Business Case for Multi-Million Token LLMs.” The latest AI puffery involves large context models—LLMs that can process and remember more than a million tokens simultaneously. Gemini 1.5 Pro, for example can process 2 million tokens at once. This achievement is dwarfed by MiniMax-Text-01, which can handle 4 million. That sounds impressive, but what are such models good for? Writers Rahul Raja and Advitya Gemawat tell us these tools can enable:
Cross-document compliance checks: A single 256K-token prompt can analyze an entire policy manual against new legislation.
Customer support: Chatbots with longer memory deliver more context-aware interactions.
Financial research: Analysts can analyze full earnings reports and market data in one query.
Medical literature synthesis: Researchers use 128K+ token windows to compare drug trial results across decades of studies.
Software development: Debugging improves when AI can scan millions of lines of code without losing dependencies.
I theory, they may also improve accuracy and reduce hallucinations. We are all for that—if true. But research from early adopter JPMorgan Chase found disappointing results, particularly with complex financial tasks. Not ideal. Perhaps further studies will have better outcomes.
The question for companies is whether to ditch ponderous chunking and RAG systems for models that can seamlessly debug large codebases, analyze entire contracts, or summarize long reports without breaking context. Naturally, there are trade-offs. We learn:
While large context models offer impressive capabilities, there are limits to how much extra context is truly beneficial. As context windows expand, three key factors come into play:
- Latency: The more tokens a model processes, the slower the inference. Larger context windows can lead to significant delays, especially when real-time responses are needed.
- Costs: With every additional token processed, computational costs rise. Scaling up infrastructure to handle these larger models can become prohibitively expensive, especially for enterprises with high-volume workloads.
- Usability: As context grows, the model’s ability to effectively ‘focus’ on the most relevant information diminishes. This can lead to inefficient processing where less relevant data impacts the model’s performance, resulting in diminishing returns for both accuracy and efficiency.”
Is it worth those downsides for simpler workflows? It depends on whom one asks. Some large context models are like a 1958 Oldsmobile Ninety-Eight: lots of useless chrome and lousy mileage.
Stephen E Arnold, May 15, 2025
Germany and Pirate Sites
May 15, 2025
The United States is batting around site-blocking legislation called Foreign Anti-Digital Piracy Act (FADPA) by Representative Zoe Lofgren. The act takes US rights holders site blocking experience from overseas and transforms into a package for US use. What it means, according to TorrentFreak’s article: “Non-Transparency Resumed After Pirate Site Blacklist Publicly Exposed In Error,”
“Should it become law, FAPDA would allow rightsholders to obtain site blocking orders targeted at verified pirate sites, run by foreign or assumed foreign operators. The proposals as they stand today envision blocking orders that would apply to both ISPs and DNS resolvers, the latter an already controversial trend that has only recently shown momentum in Europe.”
In order to be effective, site-blocking tools must always adapt. It appears that FAPDA proposals are the template for US site blocking. Similar legislation called SOPA happened in 2012 but there wasn’t any historical precedence before, but now there is. The US is using Europe’s site-blocking as an example.
Germany has an administrative site that blocks pirate Web sites without direct legal oversight:
“A partnership between rightsholders and local ISPs saw the launch of the “Clearing Body for Copyright on the Internet” (CUII) which is now responsible for handing down blocking instructions against sites that structurally infringe copyright.”
The CUII Web site publishes blocking recommendations and it is supposed to be private. It wasn’t! The Netzpolitik reported that Germany’s secret pirate blocking Web site has been publicly viewable for ten months.
People are also crying free speech violations, especially because there aren’t any transparency. Europe won’t be forthcoming with transparency is ISPs and rights holders aren’t required to have them.
Whitney Grace, May 15, 2025
The Zuck Plays Defense: The Opposing Line Is Huge, Dude
May 15, 2025
The BBC reports that Facebook founder Mark Zuckerberg has been in the news lately for his company being on trial: “Mark Zuckerberg Defends Meta In Social Media Monopoly Trial.” Meta and Zuckerberg are on trail for antitrust allegations that the company has a monopoly on social media. Zuckerberg testified in 2020 when the FTC brought the case to court.
The allegations are that Zuckerberg dominated the social media market when it acquired Instagram in 2012 and WhatsApp in 2014. The FTC wants Meta to split apart by forcing Instagram and WhatsApp into separate entities. Meta argues there’s plenty of competition with X, YouTube, and TikTok. Zuckerberg was the first to testify in the trial expected to last until July 2025.
The FTC says that Meta bought rivals because it was easier to acquire them than compete with them:
“They decided that competition was too hard and it would be easier to buy out their rivals than to compete with them,” said FTC lawyer Daniel Matheson in his opening statement at Monday’s trial. Meta countered that the lawsuit from the FTC, which originally reviewed and approved both those acquisitions, was “misguided”.
Meta ‘acquired Instagram and WhatsApp to improve and grow them alongside Facebook’, the company’s attorney Mark Hansen argued.
The FTC lawyer cited a 2012 memo from Mr Zuckerberg in which he discusses the importance of “neutralising” Instagram.
Mr Matheson called that message “a smoking gun”.”
Meta argues that when they acquired the competing platforms that it made them better for users. Instagram accounts for over half of Meta’s advertising revenue. Meta also donated to Trump’s 2024 presidential campaign. Zuckerberg repeatedly petitions Trump to have the FTC charges dropped. The FTC has a harder case to prove than when Google was sued for monopolizing search. I wonder if the prosecution’s attorneys have read Careless People: A Cautionary Tale of Power, Greed, and Lost Idealism.
Whitney Grace, May 15, 2025
Bing Goes AI: Metacrawler Outfits Are Toast
May 15, 2025
![dino-orange_thumb_thumb_thumb_thumb_[1]_thumb](https://www.arnoldit.com/wordpress/wp-content/uploads/2025/05/dino-orange_thumb_thumb_thumb_thumb_1_thumb-1.gif "dino-orange_thumb_thumb_thumb_thumb_[1]_thumb")
No AI, just the dinobaby expressing his opinions to Zillennials.
The Softies are going to win in the AI-centric search wars. In every war, there will be casualties. One of the casualties will be metasearch companies. What’s metasearch? These are outfits that really don’t crawl the Web. That is expensive and requires constant fiddling to keep pace with the weird technical “innovations” purveyors of Web content present to the user. The metasearch companies provide an interface and then return results from cooperating and cheap primary Web search services. Most users don’t know the difference and have demonstrated over the years total indifference to the distinction. Search means Google. Microsoft wants to win at search and become the one true search service.
The most recent fix? Kill off the Microsoft Bing application programming interface. Those metasearch outfits will have to learn to love Qwant, SwissCows, and their ilk or face some-survive-or-die decisions. Do these outfits use YaCy, OpenSearch, Mwmbl, or some other source of Web indexing?
Bob Softie has just tipped over the metasearch lemonade stand. The metasearch sellers are not happy with Bob. Bob seems quite thrilled with his bold move. Thanks, ChatGPT, although I have not been able to access your wonder 4.1 service, the cartoon is good enough.
The news of this interesting move appears in “Retirement: Bing Search APIs on August 11, 2025.” The Softies say:
Bing Search APIs will be retired on August 11, 2025. Any existing instances of Bing Search APIs will be decommissioned completely, and the product will no longer be available for usage or new customer signup. Note that this retirement will apply to partners who are using the F1 and S1 through S9 resources of Bing Search, or the F0 and S1 through S4 resources of Bing Custom Search. Customers may want to consider Grounding with Bing Search as part of Azure AI Agents. Grounding with Bing Search allows Azure AI Agents to incorporate real-time public web data when generating responses with an LLM. If you have questions, contact support by emailing Bing Search API’s Partner Support. Learn more about service retirements that may impact your resources in the Azure Retirement Workbook. Please note that retirements may not be visible in the workbook for up to two weeks after being announced.
Several observations:
- The DuckDuckGo metasearch system is exempted. I suppose its super secure approach to presenting other outfits’ search results is so darned wonderful
- The feisty Kagi may have to spend to get new access deals or pay low profile crawlers like Dassault Exalead to provide some content (Let’s hope it is timely and comprehensive)
- The beneficiaries may be Web search systems not too popular with some in North America; for example, Yandex.com. I have found that Yandex.com and Yandex.ru are presenting more useful results since the re-juggling of the company’s operations took place.
Why is Microsoft taking this action? My hunch is paranoia. The AI search “thing” is going to have to work if Microsoft hopes to cope with Google’s push into what the Softies have long considered their territory. Those enterprise, cloud, and partnership set ups need to have an advantage. Binging it with AI may be viewed as the winning move at this time.
My view is that Microsoft may be edging close to another Bob moment. This is worth watching because the metasearch disruption will flip over some rocks. Who knows if Yandex or another non-Google or non-Bing search repackager surges to the fore? Web search is getting slightly more interesting and not because of the increasing chaos of AI-infused search results.
Stephen E Arnold, May 15, 2025
An Agreeable Google: Will It Write Checks with a Sad, Wry Systemic Smile?
May 14, 2025
No AI, just the dinobaby expressing his opinions to Zellenials.
Did you see the news about Google’s probable check writing?
“Google Settles Black Employees’ Racial Bias Lawsuit for $50 Million” reports:
According to the complaint, Black employees comprised only 4.4% of Google’s workforce and 3% of its leadership in 2021. The plaintiff April Curley, hired to expand outreach to historically Black colleges, said Google denied her promotions, stereotyped her as an “angry” Black woman, and fired her after six years as she prepared a report on its alleged racial bias. Managers also allegedly denigrated Black employees by declaring they were not “Googley” enough or lacked “Googleyness,” which the plaintiffs called racial dog whistles.
The little news story includes the words “racially biased corporate culture” and “systemic racial bias.” Is this the beloved “do no evil” company with the cheerful kindergarten colored logo? Frankly, this dinobaby is shocked. This must be an anomaly in the management approach of a trusted institution based on advertising.
Well, there is this story from Bloomberg, the terminal folks: “Google to Pay Texas $1.4 Billion to End Privacy Cases.” As I understand it,
Google will pay the state of Texas $1.375 billion to resolve two privacy lawsuits claiming the tech giant tracks Texans’ personal location and maintains their facial recognition data, both without their consent. Google announced the settlement Friday, ending yearslong battles with Texas Attorney General Ken Paxton (R) over the state’s strict laws on user data.
Remarkable.
The Dallas Morning News reports that Google’s position remains firm, resolute, and Googley:
The settlement doesn’t require any new changes to Google’s products, and the company did not admit any wrongdoing or liability. “This settles a raft of old claims, many of which have already been resolved elsewhere, concerning product policies we have long since changed,” said José Castañeda, a Google spokesperson. “We are pleased to put them behind us, and we will continue to build robust privacy controls into our services.”
Absolutely.
Imagine a company with those kindergarten colors in its logos finding itself snared in what seem to me grade school issues. Google must be misunderstood like one of those precocious children who solve math problems without showing their work. It’s just system perhaps?
Stephen E Arnold, May 14, 2025
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