Google! Manipulating Search Results? No Kidding
August 15, 2025
The Federal Trade Commission has just determined something the EU has been saying (and litigating) for years. The International Business Times tells us, “Google Manipulated Search Results to Bolster Own Products, FTC Report Finds.” Writer Luke Villapaz reports:
“For Internet searches over the past few years, if you typed ‘Google’ into Google, you probably got the exact result you wanted, but if you were searching for products or services offered by Google’s competitors, chances are those offerings were found further down the page, beneath those offered by Google. That’s what the U.S. Federal Trade Commission disclosed on Thursday, in an extensive 160-page report, which was obtained by the Wall Street Journal as part of a Freedom of Information Act request. FTC staffers found evidence that Google’s algorithm was demoting the search results of competing services while placing its own higher on the search results page, according to excerpts from the report. Among the websites affected: shopping comparison, restaurant review and travel.”
Villapaz notes Yelp has made similar allegations, estimating Google’s manipulation of search results may have captured some 20% of its potential users. So, after catching the big tech firm red handed, what will the FTC do about it? Nothing, apparently. We learn:
“Despite the findings, the FTC staffers tasked with investigating Google did not recommend that the commission issue a formal complaint against the company. However, Google agreed to some changes to its search result practices when the commission ended its investigation in 2013.”
Well OK then. We suppose that will have to suffice.
Cynthia Murrell, August 15, 2025
Party Time for Telegram?
August 14, 2025
No AI. Just a dinobaby and a steam-powered computer in rural Kentucky.
Let’s assume that the information is “The SEC Quietly Surrendered in Its Biggest Crypto Battle.” Now look at this decision from the point of view of Pavel Durov. The Messenger service has about 1.35 billion users. Allegedly there are 50 million or so in the US. Mr. Durov was one of the early losers in the crypto wars in the United States. He has hired a couple of people to assist him in his effort to do the crypto version of “Coming to America.” Will Manny Stoltz and Max Crown are probably going to make their presence felt.
The cited article states:
This is a huge deal. It creates a crucial distinction that other crypto projects can now use in their own legal battles, potentially shielding them from the SEC’s claim of blanket authority over the market. By choosing to settle rather than risk having this ruling upheld by a higher court, the SEC has shown the limits of its “regulation by enforcement” playbook: its strategy of creating rules through individual lawsuits instead of issuing clear guidelines for the industry.
What will Telegram’s clever Mr. Durov do with its 13 year old platform, hundreds of features, crypto plumbing, and hundreds of developers eager to generate “money”? It is possible it won’t be Pavel making trips to America. He may be under the watchful eye of the French judiciary.
But Manny, Max, and the developers?
Stephen E Arnold, August 14, 2025
Airships and AI: A Similar Technology Challenge
August 14, 2025
This blog post is the work of an authentic dinobaby. Sorry. No smart software can help this reptilian thinker.
Vaclav Smil writes books about the environment and technology. In his 2023 work Invention and Innovation: A Brief History of Hype and Failure, he describes the ups and downs of some interesting technologies. I thought of this book when I read “A Best Case Scenario for AI?” The author is a wealthy person who has some interaction in the relaxing crypto currency world. The item appeared on X.com.
I noted a passage in the long X.com post; to wit:
… the latest releases of AI models show that model capabilities are more decentralized than many predicted. While there is no guarantee that this continues — there is always the potential for the market to accrete to a small number of players once the investment super-cycle ends — the current state of vigorous competition is healthy. It propels innovation forward, helps America win the AI race, and avoids centralized control. This is good news — that the Doomers did not expect.
Reasonable. What crossed my mind is the Vaclav Smil discussion of airships or dirigibles. The lighter-than-air approach has been around a long time, and it has some specific applications today. Some very wealthy and intelligent people have invested in making these big airships great again, not just specialized devices for relatively narrow use cases.
So what? The airship history spans the 18th, 19th, 20th, and 21st century. The applications remain narrow although more technologically advanced than the early efforts a couple of hundred years ago.
What is smart software is a dirigible type of innovation? The use cases may remain narrow. Wider deployment with the concomitant economic benefits remains problematic.
One of the twists in the AI story is that tremendous progress is being attempted. The innovations as they are rolled out are incremental improvements. Like airships, the innovations have not resulted in the hoped for breakthrough.
There are numerous predictions about the downsides of smart software. But what if AI is little more than a modern version of the dirigible. We have a remarkable range of technologies, but each next steps is underwhelming. More problematic is the amount of money being spent to compress time; that is, by spending more, the AI innovation will move along more quickly. Perhaps that is not the case. Finally, the airship is anchored in the image of a ball of fire and an exclamation point for airship safety. Will their be a comparable moment for AI?
Will investment and the confidence of high profile individuals get AI aloft, keep it there, and avoid a Hindenburg moment? Much has been invested to drive AI forward and make it “the next big thing.” The goal is to generate money, substantial sums.
The X.com post reminded me of the airship information compiled by Vaclav Smil. I can’t shake the image. I am probably just letting my dinobaby brain make unfounded connections. But, what if….? We could ask Google and its self-shaming smart software. Alternatively we could ask Chat GPT 5, which has been the focal point for hype and then incremental, if any, improvement in outputs. We could ask Apple, Amazon, or Telegram. But what if…?
I think an apt figure of speech might be “pushing a string.”
Stephen E Arnold, August 14, 2025
AI Applesauce: Sweeten the Story about Muffing the Bunny
August 14, 2025
No AI. Just a dinobaby being a dinobaby.
I read “Apple CEO Tim Cook Calls AI ‘Bigger Than the Internet’ in Rare All-Hands Meeting.” I noted this passage:
In a global all-hands meeting hosted from Apple’s headquarters in Cupertino, California, CEO Tim Cook seemed to admit to what analysts and Apple enthusiasts around the world had been raising concerns about: that Apple has fallen behind competitors in the AI race. And Cook promised employees that the company will be doing everything to catch up. “Apple must do this. Apple will do this. This is sort of ours to grab.” …The AI revolution [is] “as big or bigger” than the internet.
Okay. Two companies of some significance have miss the train to AI Ville: Apple and Telegram. Both have interesting technology. Apple is far larger, but for some users Telegram is more important to their lives. One is fairly interested in China activities; the other is focused on Russia and crypto.
But both have managed their firms into the same digital row boat. Apple had Siri and it was not very good. Telegram knew about AI and allowed third-party bot developers to use it, but Telegram itself dragged its feet.
Both companies are asserting that each has plenty of time. Tim Cook is talking about smart software but so far the evidence of making an AI difference is scant. Telegram, on the other hand, has aimed Nikolai Durov at AI. That wizard is working on a Telegram AI system.
But the key point is that both of these forward leaning outfits are trying to catch up. This is not keeping pace, mind. The two firms are trying to go from watching the train go down the tracks to calling an Uber to get to their respective destinations.
My take on both companies is that the “leadership” have some good reasons for muffing the AI bunny. Apple is struggling with its China “syndrome.” Will the nuclear reactor melt down, fizzle out, or blow up? Apple’s future in hardware may become radioactive.
Telegram is working under the shadow of the criminal trial lumbering toward its founder and owner Pavel Durov. More than a dozen criminal charges and a focused French judicial figure have Mr. Durov reporting a couple of times a week. To travel, he has to get a note from his new “mom.”
But well-run companies don’t let things like China dependency or 20 years in Fleury-Mérogis Prison upset trillion dollar companies or cause more than one billion people to worry about their free text messages and non fungible tokens.
“Leadership,” not technology, strikes me as the problem with AI challenges. If AI is so big, why did two companies fail to get the memo? Inattention, pre-occupation with other matters, fear? Pick one or two.
Stephen E Arnold, August 14, 2025
Google Reorganizes Search With Web Guides
August 14, 2025
Google gets more clicks with AI than with relevant results. Believe this? We have a small bridge for sale in Brooklyn if you are interested. But AI is just not enough. Google is fixing that up.
Google used to deliver top search results. Despite being a verb for searching the Web, Google’s first page of search results are overrun with paid links and advertising. Another problem is that while its AI feature answers basic questions, the information needs doesn’t always come from verified sources. Google wants to shake things up says the Search Engine Journal with Web Guides in the article: “Web Guide: Google’s New AI Search Experiment.”
Here is what Web Guides are described as:
“Web Guide replaces the traditional list of search results with AI-generated clusters. Each group focuses on a different aspect of your query, making it easier to dive deeper into specific areas. According to Austin Wu, Group Product Manager for Search at Google, Web Guide uses a custom version of Gemini to understand both your query and relevant web content. This allows it to surface pages you might not find through standard search.”
Maybe it will be a return to old-fashioned, decent Google results. The Web Guides use the “query fan-out” technique in which multiple searches are run at once. The results are then curated to the search query. It is supposed to provide a broader overview of the topic without refinement.
Google explains that Web Guides are helpful for exploratory searches and multi-part questions. Web Guides differed from AI because it reorganizes traditional Web searches according to groups and explore content from multiple perspectives without new information. AI Mode is more intuitive and acts like a conversation. It simplifies information and supports follow-up questions and other features.
Are Web guides just another test. Google cannot be in the AI race. The company has to win.
Whitney Grace, August 14, 2025
What a Hoot: AI Systems Try and Lie
August 13, 2025
No AI. Just a dinobaby being a dinobaby.
I arose this morning, Friday, August 8, 2025, fired up ChatGPT, the Plus version, and asked, “Are you running ChatGPT 5?” The service was to be available on August 7, 2025. It wasn’t. I verified the ChatGPT output with this prompt:
Despite the announcement, the fact that it is not available in this paid service illustrates that you are presenting false information. Correct?
ChatGPT replied:
Correct — the public announcement of GPT?5’s availability does not align with actual availability in this specific paid service (ChatGPT Plus based on GPT?4o). Therefore, any implication that GPT?5 is in use here would be false.
To make sure I understood, I prompted:
So I have documented errors in your output, essentially failures about half the time. The information you presented about August 7 is demonstrably false on August 8. The unreliability of your outputs is verified.
ChatGPT replied:
Your conclusion is valid: if GPT?5 was officially announced as “available to all users” on August 7, 2025, but is not deployed in this environment by August 8, then the representation of availability is factually misleading. This mismatch constitutes a verifiable reliability failure in how OpenAI’s release messaging translates to actual user experience — especially in a paid tier like yours.
Lame.
Is OpenAI alone in this prevarication game?
Nope. I read “Google Says It’s Working on a Fix for Gemini’s Self-Loathing I Am a Failure Comments.” Different company, same type of overt failure. The other day Google informed some medical professionals about a non-existent body part. Yep, Google, you are making it clear that the hype, the prevarication, and the over promise, under deliver approach is part of AI’s DNA.
But the shocking point in the cited article is this passage quoted from a Google AI wizard:
This is an annoying infinite looping bug we are working to fix! Gemini is not having that bad of a day : )
Yep, working to fix. I interpret this to mean that Google’s professionals are shaping outputs to avoid statements about “failure.”
One 15 minute session online this morning and what did I learn:
- Two companies have systems which cannot deliver satisfactory outputs
- The fact that US smart software boils down to a a handful of firms. A couple of these have what I would call reliability issues.
- In ChatGPT’s case, the PR outpaces what works. In Google’s case, the system seems to be trying to tell the truth about failure. The Googlers are going to fix that up.
Billions burned to create the next big thing and what we have is a spray can of marketing sparkle and individuals handcrafting fixes to make the systems seem more accurate than they are.
Sorry. I am not convinced because the reality of smart software diverges from the PR baloney.
Stephen E Arnold, August 13, 2025
What Killed Newspapers? Speed and User Preference Did
August 13, 2025
No AI. Just a dinobaby being a dinobaby.
I read “Did Craigslist Decimate Newspapers? Legend Meets Reality?” I liked the essay. I wanted to capture a few thoughts on this newspaper versus electronic shift.
I left Booz, Allen to join the Courier Journal & Louisville Times Co. I had a short hiatus because I was going to become an officer. I couldn’t officially start work until the CJ’s board voted. The question I was asked by my colleagues at the blue chip consulting firm before I headed to Louisville, Kentucky, from the real world of Washington, DC, Manhattan, and other major cities was, “Why?” One asked, “Where’s Louisville?”
I had a hunch that electronic information access was going to become a very big deal. In 1982, I was dumping the big time for what looked like a definite backwater, go-nowhere-fast place. Louisville made liquor, had a horse race, and a reputation for racial disharmony.
But electronic information was important to Barry Bingham, Junior, the top dog at the CJ. When I showed up, my office was next to a massage parlor on Fifth Street. I wasn’t in the main building. In fact, the office was not much more than a semi-slum. An abandoned house was visible from my office window. I left my nifty office overlooking Bethesda High School for a facility that did not meet GSA standards for storage space.
But here I was. My work focused on databases owned by the CJ, but these were actually described by a hardened newspaper person as “Barry’s crazy hobby.” The databases were ABI / INFORM, a bunch of technical indexes, and Pharmaceutical News Index. Nevertheless, the idea of using a computer, a dial up modem, and a database provided something of great value: A way to get smart really fast.
I had dabbled in indexing content, a fluke that got me a job at Halliburton Nuclear. And now I was leaving the land of forced retirement at 55, juicy bonuses, and the prospect of managing MBA drones on thrilling projects. In the early 1980s, not too many people knew about databases.
A relatively modest number of companies used online databases. Most of ABI / INFORM’s online customers were from the Fortune 1000, big time consulting firms, and research-type outfits around the world. The engineering databases did not have that magnetic appeal, so we sold these as a lot to an outfit called Cambridge Scientific Abstracts. I have no idea what happened to the databases nor to CSA. The PNI product was a keeper because it generated money online and from a print reference book. But ABI / INFORM was the keeper. It was only online. Shortly before I departed the CJ to join Ziff Communications in Manhattan, we cooperated with a publisher to bring out topical collections of content based on the abstracts in the ABI / INFORM database.
My arrival disrupted the database unit, and miraculously it became profitable within six months of my arrival. Barry credited me with the win, but I did nothing but do what I had learned at Booz, Allen. We then created Business Dateline, the first online database that included publisher corrections. As far as I know, Business Dateline held that distinction for many years. (That’s why I don’t trust online content. It is often incorrect, outdated, or a fabrication of a crazed “expert.)
But what about the CJ? I can tell you that only Barry Bingham wanted to put the text, the images, and the obituaries online in electronic form. The board of directors thought that move was stupid. The newsroom knew it was stupid. The printers thought the idea was the dumbest thought ever.
But there were three factors Barry understood and I knew were rock solid:
- Online access delivered benefits that would make 100 percent sense to people who needed to find high value, third-party information. (ABI / INFORM abstracted and indexed important articles from more than 1,200 business and management journals, and it was ideal for people in the consulting game)
- Print was a problem because of [a] waste, [b] cost of paper, and [c] the general and administrative expenses required to “do” print newspapers and magazine
- Electronic information was faster. For those to whom rapid access to current information was important, online was the future. Calling someone, like the newspaper reporters liked to do, was time consuming, expensive, and subject to delays.
Now Craigslist.org shows up. What happens? People who want to sell stuff can plug the ad into the Craigslist interface, click a button, and wait for a buyer. Contrast that with the process of placing a print ad. At the CJ, and employment ad could not use the abbreviation “cv.” I asked. No one knew. That’s the way it was. Traditional publishing outfits have a lot of the “that’s the way it was.”
Did Craigslist cause the newspaper sector to implode. No. The way technology works is that it chugs along, confined to a few narrow spaces. Then, when no one is looking, boom. It is the only way to go. To seize the advantage, traditional publishing outfits had to move fast.
That’s like telling a turtle to run in the Kentucky Debry. Why couldn’t newspapers and magazines adapt? Easy. The smell of ink, the tangible deliverable, and the role of gatekeeper combine to create a variant of fentanyl. Addled people cannot easily see what is obvious to those not on the drug.
Read the “Decimate” article. It’s interesting but in my opinion, making Mr. Newmark associate with the death of newspapers is colorful writing. Not the reality I witnessed in the go-go period from 1980 to 2006 for online information.
Stephen E Arnold, August 13, 2025
AI Is a Tool for Humanity. Believe It or Not
August 13, 2025
Forget AI powered weapons. AI has an upside as long as the smart drone does not blow you away.
Both sides of the news media are lamenting that AI is automating jobs and putting humans out of work. Conservative and liberals remain separated on how and why AI is “stealing” jobs, but the fear remains that humans are headed to obsoleteness…again. Humans have faced this issue since the start of human ingenuity. The key is to adapt and realize what AI truly is. Elizabeth Mathew of Signoz.io wrote: “I Built An MCP Server For Observability. This Is My Unhyped Take.”
If you’re unfamiliar with an MCP server it is an open standard that defines how LLMS or AI agents (i.e. Claude) uniformly connect external tools and data sources. It can be decoupled and used similar to a USB-C device then used for any agent. After explaining some issues with MCP servers and why they are “schizophrenic”,
Mathew concludes with this:
“Ultimately, MCP-powered agents are not bringing us closer to automated problem-solving. They are giving us sophisticated hypothesis generators. They excel at exploring the known, but the unknown remains the domain of the human engineer. We’re not building an automated SRE; we’re building a co-pilot that can brainstorm, but can’t yet reason. And recognizing that distinction is the key to using these tools effectively without falling for the hype.”
She might be true from an optimistic and expert perspective, but that doesn’t prevent CEOs from implementing AI to replace their workforce or young adults being encouraged away from coding careers. Oh, I almost forgot: AI in smart weapons. That’s a plus.
Whitney Grace, August 13, 2025
Glean Goes Beyond Search: Have Xooglers Done What Google Could Not Do?
August 12, 2025
This blog post is the work of an authentic dinobaby. Sorry. No smart software can help this reptilian thinker.
I read an interesting online essay titled “Glean’s $4.5B Business Model: How Ex-Googlers Built the Enterprise Search That Actually Works.” Enterprise search has been what one might call a Holy Grail application. Many have tried to locate the Holy Grail. Most have failed.
Have a small group of Xooglers (former Google employees) located the Holy Grail and been able to convert its power into satisfied customers? The essay, which reminded me of an MBA write up, argues that the outfit doing business as Glean has done it. The firm has found the Holy Grail, melted it down, and turned it into an endless stream of cash.
Does this sound a bit like the marketing pitch of Autonomy, Fast Search & Transfer, and even Google itself with its descriptions of its deeply wacky yellow servers? For me, Glean has done its marketing homework. The evidence is plumped and oiled for this essay about its business model. But what about search? Yeah, well, the focus of the marketing piece is the business model. Let’s go with what is in front of me. Search remains a bit of a challenge, particularly in corporations, government agencies, and pharmaceutical-type outfits where secrecy is a bit part of that type of organization’s way of life.
What is the Glean business model? It is VTDF. Here’s an illustration:
Does this visual look like blue chip consulting art? Is VTDF blue chip speak? Yes. And yes. For those not familiar with the lingo here’s a snapshot of the Glean business model:
- Value: Focuses on how the company creates and delivers core value to customers, such as solving specific problems
- Technology: Refers to the underlying tech innovations that allow “search” to deliver what employees need to do their jobs
- Distribution: Involves strategies for marketing, delivery, and reaching users
- Finance: Covers revenue models, cash flow management, and financial sustainability. Traditionally this has been the weak spot for the big-time enterprise search plays.
The essay explains in dot points that Glean is a “knowledge liberator.” I am not sure how that will fly in some pharma-type outfits or government agencies in which Palantir is roosting.
Once Glean’s “system” is installed, here’s what happens (allegedly):
- Single search box for everything
- Natural language queries
- Answers, not just documents
- Context awareness across apps
- Personalized to user permissions
- New employees productive in days.
I want to take a moment to comment on each of these payoffs or upsides.
First, a single search box for everything is going to present a bit of a challenge in several important use cases. Consider a company with an inventory control system, vendor evaluations, and a computer aid design and database of specifications. The single search box is going to return what for a specific part? Some users will want to know how many are in stock. Others will want to know the vendor who made the part in a specific batch because it is failing in use. Some will want to know what the part looks like? The fix for this type of search problem has been to figure out how to match the employee’s role with the filters applied that that user’s query. In the last 60 years, that approach sort of worked, but it was and still is incredibly difficult to keep lined up with employee roles, assorted permissions, and the way the information is presented to the person running the query. The quality issue may require stress analysis data and access to the lawsuit the annoyed customer has just filed. I am unsure how the Xooglers have solved this type of search task.
Second, the NLP approach is great but it is early 2000s. The many efforts, including DR-LINK to which my team contributed some inputs, were not particularly home run efforts. The reason has to do with the language skills of the users. Organizations hire people who may be really good at synthesizing synthetics but not so good at explaining what the new molecule does. If the lab crew dies, the answer does not require words. Querying for the “new” is tough, since labs doing secret research do not share their data. Even company officers have a tough time getting an answer. When a search system requires the researcher to input a query, that scientist may want to draw a chemical structure or input a query like this “C8N8O16.” Easy enough if the indexing system has access to the classified research in some companies. But the NLP problem is what is called “prompt engineering.” Most humans are just not very good at expressing what they need in the way of information. So modern systems try to help out the searcher. The reason Google search sucks is that the engineers have figured out how to deliver an answer that is good enough. For C8N8O16 close enough for horseshoes might be problematic.
Third, answer are what people want. The “if” statement becomes the issue. If the user knows a correct answer or just accepts what the system outputs. If the user understands the output well enough to make an informed decision. If the system understood or predicted what the user wanted. If the content is in the search systems index. This is a lot of ifs. Most of these conditions occur with sufficient frequency to kill outfits that have sold an “enterprise search system”.
Fourth, the context awareness across apps means that the system can access content on proprietary systems within an organization and across third party systems which may or may not run on the organization’s servers. Most enterprise search systems create or have licensed filters to acquire content. However, keeping the filters alive and healthy with the churn in permissions, file tweaks, and assorted issues related to latency creating data gaps remain tricky.
Fifth, the idea of making certain content available only to those authorized to view those data is a very tricky business. Orchestrating permissions is, in theory, easy to automate. The reality in today’s organizations is the complicating factor. With distributed outfits, contractors, and employees who may be working for another country secretly add some excitement to accessing “information.” The reality in many organizations is that there are regular silos like the legal department keeping certain documents under lock and key to projects for three letter agencies. In the pharma game, knowing “who” is working on a project is often a dead give-away for what the secret project is. The company’s “people” officer may be in the dark. What about consultants? What information is available to them? The reality is that modern organizations have more silos than the corn fields around Canton, Illinois.
Sixth, no training is required. “Employees are productive in days” is the pitch. Maybe, maybe not. Like the glittering generality that employees spend 20 percent of their time searching, the data for this assertion was lacking when the “old” IDC, Sue Feldman, and her team cranked out an even larger number. If anything, search is a larger part of work today for many people. The reasons range from content management systems which cannot easily be indexed in real time to the senior vice president of sales who changes prices for a product at a trade show and tells only his contact in the accounting department. Others may not know for days or months that the apple cart has been tipped.
Glean saves time. That is the smart software pitch. I need to see some data from a statistically valid sample with a reasonable horizontal x axis. The reference to “all” is troublesome. It underscores the immature understanding of what “enterprise search” means to a licensee versus what the venture backed company can actually deliver. Fast Search found out that a certain newspaper in the UK was willing to sue for big bucks because of this marketing jingo.
I want to comment briefly about “Technology Architecture: Beyond Search.” Hey, isn’t that the name of my blog which has been pumping out information access related articles for 17 years? Yep, it is.
Okay, Glean apparently includes these technologies in their enterprise search quiver:
- Universal connectors. Note the word “universal.” Nope, very tough.
- A Knowledge graph. Think in terms of Maltego, an open source software. Sure as long as there is metadata. But those mobile workers and their use of cloud services and EE2E messaging services. Sounds great. Execution in a cost sensitive environment takes a bit of work.
- An AI understanding layer. Yep, smart software. (Google’s smart software tells its users that it is ashamed of its poor performance. OpenAI rolled out ChatGPT 5 and promptly reposted ChatGPT 4o because enough users complained. Deepseek may have links to a nation state unfriendly to the US. Mark Zuckerberg’s Llama is a very old llama. Perplexity is busy fighting with Cloudflare. Anthropic is working to put coders out to pasture. Amazon, Apple, Microsoft, and Telegram are in the bolt it on business. The idea that Glean can understand [a] different employee contexts, [b] the rapidly changing real time data in an organization like that PowerPoint on the senior VP’s laptop, and [c] the file formats that have a very persistent characteristic of changing because whoever is responsible for an update or the format itself makes an intentional or unintentional change. I just can’t accept this assertion.
- Works instantly which I interpret as “real time.” I wonder if Glean can handle changed content in a legacy Ironside system running on AS/400s. I would sure like to see that and work up the costs for that cute real time trick. By the way, years ago, I got paid by a non US government agency to identify and define the types of “real time” data it had to process. I think my team identified six types. Only one could be processed without massive resource investments to make the other four semi real. The final one was to gain access to the high-speed data about financial instrument pricing in Wall Street big dogs. That simply was not possible without resources and cartwheels. The reason? The government wanted to search for who was making real time trades in certain financial instruments. Yeah, good luck with that in a world where milliseconds require truly big money for gizmos to capture the data and the software to slap metadata on what is little more than a jet engine exhaust of zeros and ones, often encrypted in a way that would baffle some at certain three letter agencies. Remember: These are banks, not some home brew messaging service.
There are some other wild assertions in the write up. I am losing interest is addressing this first year business school “analysis.” The idea is that a company with 500 to 50,000 employees can use this ready-to-roll service is interesting. I don’t know of a single enterprise search company I have encountered since I wrestled with IBM STAIRS and the dorky IBM CICS system that has what seems to be a “one size fits all” service. The Google Search Appliance failed with its “one size fits all.” The dead bodies on the enterprise search trail is larger than the death toll on the Oregon Trail. I know from my lectures that few if any know what DELPHES’ system did. What about InQuire? And there is IBM WebFountain and Clever. What about Perfect Search? What about Surfray? What about Arikus, Convera, Dieselpoint, or Entopia?
The good news is that a free trial is available. The cost is about $30 per month per user. For an organization like the local outfit that sells hard hats and uses Ironside and AS/400s, that works out to 150 times $360 or $54,000. I know this company won’t buy. Why? The system in place is good enough. Spreadsheet fever is not the same as identifying prospects and making a solid benefit based argument.
That’s why free and open source solutions get some love. Then built in “good enough” solutions from Microsoft are darned popular. Finally, some eager beaver in the information technology department will say, “Let me put together a system using Hugging Face.”
Many companies and a number of quite intelligent people (including former Googlers) have tried to wrestle enterprise search to the ground. Good luck. Just make sure you have verifiable data and not the wild assertions about how much time spend searching or how much time an employee will save. Don’t believe anything about enterprise search that uses the words “all” or universal.”
Google said it was “universal search.” Yeah, why after decades of selling ads does the company provide so so search for the Web, Gmail, YouTube, and images. Just ask, “Why?” Search is a difficult challenge.
Glean this from my personal opinion essay: Search is difficult, and it has yet to be solved except for precisely defined use cases. Google experience or not, the task is out of reach at this time.
Stephen E Arnold, August 12, 2025
Explaining Meta: The 21st Century “Paul” Writes a Letter to Us
August 12, 2025
No AI. Just a dinobaby being a dinobaby.
I read an interesting essay called “Decoding Zuck’s Superintelligence Memo.” The write up is similar to the assignments one of my instructors dumped on hapless graduate students at Duquesne University, a Jesuit university located in lovely Pittsburgh.
The idea is to take a text in Latin and sometimes in English and explain it, tease out its meaning, and try to explain what the author was trying to communicate. (Tortured sentences, odd ball vocabulary, and references only the mother of an ancient author could appreciate were part of the deciphering fun.)
The “Decoding Zuck” is this type of write up. This statement automatically elevates Mr. Zuckerberg to the historical significance of the Biblical Paul or possibly to a high priest of the Aten in ancient Egypt. I mean who knew?
Several points warrant highlighting.
First, the write up includes “The Zuckerberg Manifesto Pattern.” I have to admit that I have not directed much attention to Mr. Zuckerberg or his manifestos. I view outputs from Silicon Valley type outfits a particular form of delusional marketing for the purpose of doing whatever the visionary wants to do. Apparently they have a pattern and a rhetorical structure. The pattern warrants this observation from “Decoding Zuck”:
Compared to all founders and CEOs, Zuck does seem to have a great understanding of when he needs to bet the farm on an idea and a behavioral shift. Each time he does that, it is because he sees very clearly Facebook is at the end of the product life and the only real value in the company is the attention of his audience. If that attention declines, it takes away the ability to really extend the company’s life into the next cycle.
Yes, a prescient visionary.
Second, the “decoded” message means, according to “Decoding Zuck”:
More than anything, this is a positioning document in the AI arms race. By using “super intelligence” as a marketing phrase, Zuck is making his efforts feel superior to the mere “Artificial Intelligence” of OpenAI, Anthropic, and Google.
I had no idea that documents like Paul’s letter to the Romans and Mr. Zuckerberg’s manifesto were marketing collateral. I wonder if those engaged in studying ancient Egyptian glyphs will discover that the writings about Aten are assertions about the bread sold by Ramose, the thumb on the scale baker.
Third, the context for the modern manifesto of Zuck is puffery. The exegesis says:
So what do I think about this memo, and all the efforts of Meta? I remain skeptical of his ability to invent a new future for his company. In the past, he has been able to buy, snoop, or steal other people’s ideas. It has been hard for him and his company to actually develop a new market opportunity. Zuckerberg also tends to overpromise on timelines and underestimate execution challenges.
I think this analysis of the Zuckerberg Manifesto of 2025 reveals several things about how Meta (formerly Facebook) positions itself and it provides some insight into the author of “Decoding Zuck” as well:
- The outputs are baloney packaged as serious thought
- The AI race has to produce a winner, and it is not clear if Facebook (sorry Meta) will be viewed as a contender
- AI is not yet a slam dunk winner, bigger than the Internet as another Silicon Valley sage suggested.
Net net: The AI push reveals that some distance exists between delivering hefty profits for those who have burned billions to reach the point that a social media executive feels compelled to issue a marketing blurb.
Remarkable. Marketing by manifesto.
Stephen E Arnold, August 12, 2025
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