Are Experts Misunderstanding Google Indexing?
April 12, 2024
This essay is the work of a dumb dinobaby. No smart software required.
Google is not perfect. More and more people are learning that the mystics of Mountain View are working hard every day to deliver revenue. In order to produce more money and profit, one must use Rust to become twice as wonderful than a programmer who labors to make C++ sit up, bark, and roll over. This dispersal of the cloud of unknowing obfuscating the magic of the Google can be helpful. What’s puzzling to me is that what Google does catches people by surprise. For example, consider the “real” news presented in “Google Books Is Indexing AI-Generated Garbage.” The main idea strikes me as:
But one unintended outcome of Google Books indexing AI-generated text is its possible future inclusion in Google Ngram viewer. Google Ngram viewer is a search tool that charts the frequencies of words or phrases over the years in published books scanned by Google dating back to 1500 and up to 2019, the most recent update to the Google Books corpora. Google said that none of the AI-generated books I flagged are currently informing Ngram viewer results.
Thanks, Microsoft Copilot. I enjoyed learning that security is a team activity. Good enough again.
Indexing lousy content has been the core function of Google’s Web search system for decades. Search engine optimization generates information almost guaranteed to drag down how higher-value content is handled. If the flagship provides the navigation system to other ships in the fleet, won’t those vessels crash into bridges?
In order to remediate Google’s approach to indexing requires several basic steps. (I have in various ways shared these ideas with the estimable Google over the years. Guess what? No one cared, understood, and if the Googler understood, did not want to increase overhead costs. So what are these steps? I shall share them:
- Establish an editorial policy for content. Yep, this means that a system and method or systems and methods are needed to determine what content gets indexed.
- Explain the editorial policy and what a person or entity must do to get content processed and indexed by the Google, YouTube, Gemini, or whatever the mystics in Mountain View conjure into existence
- Include metadata with each content object so one knows the index date, the content object creation date, and similar information
- Operate in a consistent, professional manner over time. The “gee, we just killed that” is not part of the process. Sorry, mystics.
Let me offer several observations:
- Google, like any alleged monopoly, faces significant management challenges. Moving information within such an enterprise is difficult. For an organization with a Foosball culture, the task may be a bit outside the wheelhouse of most young people and individuals who are engineers, not presidents of fraternities or sororities.
- The organization is under stress. The pressure is financial because controlling the cost of the plumbing is a reasonably difficult undertaking. Second, there is technical pressure. Google itself made clear that it was in Red Alert mode and keeps adding flashing lights with each and every misstep the firm’s wizards make. These range from contentious relationships with mere governments to individual staff member who grumble via internal emails, angry Googler public utterances, or from observed behavior at conferences. Body language does speak sometimes.
- The approach to smart software is remarkable. Individuals in the UK pontificate. The Mountain View crowd reassures and smiles — a lot. (Personally I find those big, happy looks a bit tiresome, but that’s a dinobaby for you.)
Net net: The write up does not address the issue that Google happily exploits. The company lacks the mental rigor setting and applying editorial policies requires. SEO is good enough to index. Therefore, fake books are certainly A-OK for now.
Stephen E Arnold, April 12, 2024
AI Will Take Jobs for Sure: Money Talks, Humans Walk
April 12, 2024
This essay is the work of a dumb dinobaby. No smart software required.
Report Shows Managers Eager to Replace or Devalue Workers with AI Tools
Bosses have had it with the worker-favorable labor market that emerged from the pandemic. Fortunately, there is a new option that is happy to be exploited. We learn from TechSpot that a recent “Survey Reveals Almost Half of All Managers Aim to Replace Workers with AI, Could Use It to Lower Wages.” The report is by beautiful.ai, which did its best to spin the results as a trend toward collaboration, not pink slips. Nevertheless, the numbers seem to back up worker concerns. Writer Rog Thubron summarizes:
“A report by Beautiful.ai, which makes AI-powered presentation software, surveyed over 3,000 managers about AI tools in the workplace, how they’re being implemented, and what impact they believe these technologies will have. The headline takeaway is that 41% of managers said they are hoping that they can replace employees with cheaper AI tools in 2024. … The rest of the survey’s results are just as depressing for worried workers: 48% of managers said their businesses would benefit financially if they could replace a large number of employees with AI tools; 40% said they believe multiple employees could be replaced by AI tools and the team would operate well without them; 45% said they view AI as an opportunity to lower salaries of employees because less human-powered work is needed; and 12% said they are using AI in hopes to downsize and save money on worker salaries. It’s no surprise that 62% of managers said that their employees fear that AI tools will eventually cost them their jobs. Furthermore, 66% of managers said their employees fear that AI tools will make them less valuable at work in 2024.”
Managers themselves are not immune to the threat: Half of them said they worry their pay will decrease, and 64% believe AI tools do their jobs better than experienced humans do. At least they are realistic. Beautiful.ai stresses another statistic: 60% of respondents who are already using AI tools see them as augmenting, not threatening, jobs. The firm also emphasizes the number of managers who hope to replace employees with AI decreased “significantly” since last year’s survey. Progress?
Cynthia Murrell, April 12, 2024
The Only Dataset Search Tool: What Does That Tell Us about Google?
April 11, 2024
This essay is the work of a dumb dinobaby. No smart software required.
If you like semi-jazzy, academic write ups, you will revel in “Discovering Datasets on the Web Scale: Challenges and Recommendations for Google Dataset Search.” The write up appears in a publication associated with Jeffrey Epstein’s favorite university. It may be worth noting that MIT and Google have teamed to offer a free course in Artificial Intelligence. That is the next big thing which does hallucinate at times while creating considerable marketing angst among the techno-giants jousting to emerge as the go-to source of the technology.
Back to the write up. Google created a search tool to allow a user to locate datasets accessible via the Internet. There are more than 700 data brokers in the US. These outfits will sell data to most people who can pony up the cash. Examples range from six figure fees for the Twitter stream to a few hundred bucks for boat license holders in states without much water.
The write up says:
Our team at Google developed Dataset Search, which differs from existing dataset search tools because of its scope and openness: potentially any dataset on the web is in scope.
A very large, money oriented creature enjoins a worker to gather data. If someone asks, “Why?”, the monster says, “Make up something.” Thanks MSFT Copilot. How is your security today? Oh, that’s too bad.
The write up does the academic thing of citing articles which talk about data on the Web. There is even a table which organizes the types of data discovery tools. The categorization of general and specific is brilliant. Who would have thought there were two categories of a vertical search engine focused on Web-accessible data. I thought there was just one category; namely, gettable. The idea is that if the data are exposed, take them. Asking permission just costs time and money. The idea is that one can apologize and keep the data.
The article includes a Googley graphic. The French portal, the Italian “special” portal, and the Harvard “dataverse” are identified. Were there other Web accessible collections? My hunch is that Google’s spiders such down as one famous Googler said, “All” the world’s information. I will leave it to your imagination to fill in other sources for the dataset pages. (I want to point out that Google has some interesting technology related to converting data sets into normalized data structures. If you are curious about the patents, just write benkent2020 at yahoo dot com, and one of my researchers will send along a couple of US patent numbers. Impressive system and method.)
The section “Making Sense of Heterogeneous Datasets” is peculiar. First, the Googlers discovered the basic fact of data from different sources — The data structures vary. Think in terms of grapes and deer droppings. Second, the data cannot be “trusted.” There is no fix to this issue for the team writing the paper. Third, the authors appear to be unaware of the patents I mentioned, particularly the useful example about gathering and normalizing data about digital cameras. The method applies to other types of processed data as well.
I want to jump to the “beyond metadata” idea. This is the mental equivalent of “popping” up a perceptual level. Metadata are quite important and useful. (Isn’t it odd that Google strips high value metadata from its search results; for example, time and data?) The authors of the paper work hard to explain that the Google approach to data set search adds value by grouping, sorting, and tagging with information not in any one data set. This is common sense, but the Googley spin on this is to build “trust.” Remember: This is an alleged monopolist engaged in online advertising and co-opting certain Web services.
Several observations:
- This is another of Google’s high-class PR moves. Hooking up with MIT and delivering razz-ma-tazz about identifying spiderable content collections in the name of greater good is part of the 2024 Code Red playbook it seems. From humble brag about smart software to crazy assertions like quantum supremacy, today’s Google is a remarkable entity
- The work on this “project” is divorced from time. I checked my file of Google-related information, and I found no information about the start date of a vertical search engine project focused on spidering and indexing data sets. My hunch is that it has been in the works for a while, although I can pinpoint 2006 as a year in which Google’s technology wizards began to talk about building master data sets. Why no time specifics?
- I found the absence of AI talk notable. Perhaps Google does not think a reader will ask, “What’s with the use of these data? I can’t use this tool, so why spend the time, effort, and money to index information from a country like France which is not one of Google’s biggest fans. (Paris was, however, the roll out choice for the answer to Microsoft and ChatGPT’s smart software announcement. Plus that presentation featured incorrect information as I recall.)
Net net: I think this write up with its quasi-academic blessing is a bit of advance information to use in the coming wave of litigation about Google’s use of content to train its AI systems. This is just a hunch, but there are too many weirdnesses in the academic write up to write off as intern work or careless research writing which is more difficult in the wake of the stochastic monkey dust up.
Stephen E Arnold, April 11, 2024
Perplexed at Perplexity? It Is Just the Need for Money. Relax.
April 5, 2024
This essay is the work of a dumb dinobaby. No smart software required.
“Gen-AI Search Engine Perplexity Has a Plan to Sell Ads” makes it clear that the dynamic world of wildly over-hyped smart software is somewhat fluid. Pivoting from “No, never” to “Yes, absolutely” might catch some by surprise. But this dinobaby is ready for AI’s morphability. Artificial intelligence means something to the person using the term. There may be zero correlation between the meaning of AI in the mind of any other people. Absent the Vulcan mind meld, people have to adapt. Morphability is important.
The dinobaby analyst is totally confused. First, say one thing. Then, do the opposite. Thanks, MSFT Copilot. Close enough. How’s that AI reorganization going?
I am thinking about AI because Perplexity told Adweek that despite obtaining $73 million in Series B funding, the company will start selling ads. This is no big deal for Google which slips unmarked ads into its short video streams. But Perplexity was not supposed to sell ads. Yeah, well, that’s no longer an operative concept.
The write up says:
Perplexity also links sources in the response while suggesting related questions users might want to ask. These related questions, which account for 40% of Perplexity’s queries, are where the company will start introducing native ads, by letting brands influence these questions,
Sounds rock solid, but I think that the ads will have a bit of morphability; that is, when big bucks are at stake, those ads are going to go many places. With an alleged 10 million monthly active users, some advertisers will want those ads shoved down the throat of anything that looks like a human or bot with buying power.
Advertisers care about “brand safety.” But those selling ads care about selling ads. That’s why exciting ads turn up in quite interesting places.
I have a slight distrust for pivoters. But that’s just an old dinobaby, an easily confused dinobaby at that.
Stephen E Arnold, April 5, 2024
Nah, AI Is for Little People Too. Ho Ho Ho
April 5, 2024
This essay is the work of a dumb dinobaby. No smart software required.
I like the idea that smart software is open. Anyone can download software and fire up that old laptop. Magic just happens. The reality is that smart software is going to involve some big outfits and big bucks when serious applications or use cases are deployed. How do I know this? Well, I read “Microsoft and OpenAI Reportedly Building $100 Billion Secret Supercomputer to Train Advanced AI.” The number $100 billion in not $6 trillion bandied about by Sam AI-Man a few weeks ago. It does, however, make Amazon’s paltry $3 billion look like chump change. And where does that leave the AI start ups, the AI open source champions, and the plain vanilla big-smile venture folks? The answer is, “Ponying up some bucks to get that AI to take flight.”
Thanks, MSFT Copilot. Stick to your policies.
The write up states:
… the dynamic duo are working on a $100 billion — that’s "billion" with a "b," meaning a sum exceeding many countries’ gross domestic products — on a hush-hush supercomputer designed to train powerful new AI.
The write up asks a question some folks with AI sparkling in their eyes cannot answer; to wit:
Needless to say, that’s a mammoth investment. As such, it shines an even brighter spotlight on a looming question for the still-nascent AI industry: how’s the whole thing going to pay for itself?
But I know the answer: With other people’s money and possibly costs distributed across many customers.
Observations are warranted:
- The cost of smart software is likely to be an issue for everyone. I don’t think “free” is the same as forever
- Mistral wants to do smaller language models, but Microsoft has “invested” in that outfit as well. If necessary, some creative end runs around an acquisition may be needed because MSFT may want to take Mistral off the AI chess board
- What’s the cost of the electricity to operate what $100 billion can purchase? How about a nifty thorium reactor?
Net net: Okay, Google, what is your move now that MSFT has again captured the headlines?
Stephen E Arnold, April 5, 2024
McKinsey & Co. Emits the Message “You Are No Longer the Best of the Best”
April 4, 2024
This essay is the work of a dumb dinobaby. No smart software required.
I love blue chip consulting firms’ management tactics. I will not mention the private outfits which go public and then go private. Then the firms’ “best of the best” partners decide to split the firm. Wow. Financial fancy dancing or just evidence that “best of the best” is like those plastic bottles killing off marine life?
I read “McKinsey Is so Eager to Trim Staff That It’s Offering Some Employees 9 Months’ Pay to Go and Do Something Else. I immediately asked myself, “What’s some mean?” I am guessing based on my experience that “all” of the RIF’ed staff are not getting the same deal. Well, that’s life in the exciting world of the best and the brightest. Some have to accept that there are blue chippers better and, therefore, able to labor enthusiastically at a company known as the Big Dog in the consulting world.
Thanks MSFT Copilot. (How’s your security today?)
The write up reports as “real” NY news:
McKinsey is attempting to slim the company down in a caring and supporting way by paying its workers to quit.
Hmmm. “Attempting” seems an odd word for a consulting firm focused on results. One slims down or one remains fat and prone to assorted diseases if I understood my medical professional. Is McKinsey signaling that its profit margin is slipping like the trust level for certain social media companies? Or is artificial intelligence the next big profit making thing; therefore, let’s clear out the deadwood and harvest the benefits of smart software unencumbered by less smart humans?
Plus, the formerly “best and brightest” will get help writing their résumés. My goodness, imagine a less good Type A super achiever unable to write a résumé. But just yesterday those professionals were able to advise executives often with decades more experience, craft reports with asterisk dot points, and work seven days a week. These outstanding professionals need help writing their résumés. This strikes me as paternalistic and a way to sidestep legal action for questionable termination.
Plus, the folks given the chance to find their future elsewhere (as long as the formerly employed wizard conforms to McKinsey’s policies about client poaching) can allegedly use their McKinsey email accounts. What might a person who learns he or she is no longer the best of the best might do with a live McKinsey email account? I have a couple of people on my research team who have studied mischief with emails. I assume McKinsey’s leadership knows a lot more than my staff. We don’t pontificate about pharmaceutical surfing; we do give lectures to law enforcement and intelligence professionals. Therefore, my team knows much, much less about the email usage that McKinsey management.
Deloitte, another blue chip outfit, is moving quickly into the AI space. I have heard that it wants to use AI and simultaneously advise its clients about AI. I wonder if Deloitte has considered that smart software might be marginally less expensive than paying some of the “best of the best” to do manual work for clients? I don’t know.
The blue chip outfit at which I worked long ago was a really humane place. Those rumors that an executive drowned a loved one were just rumors. The person was a kind and loving individual with a raised dais in his office. I recall I hard to look up at him when seated in front of his desk. Maybe that’s just an AI type hallucination from a dinobaby. I do remember the nurturing approach he took when pointing at a number and demanding the VP presenting the document, “I want to know where that came from now.” Yes, that blue chip professional was patient and easy going as well.
I noted this passage in the Fortune “real” NY news:
A McKinsey spokesperson told Fortune that its unusual approach to layoffs is all part of the company’s core mission to help people ‘learn and grow into leaders, whether they stay at McKinsey or continue their careers elsewhere.’
I loved the sentence including the “learn and grow into leaders” verbiage. I am imagining a McKinsey HR professional saying, “Remember when we recruited you? We told you that you were among the top one percent of the top one percent. Come on. I know you remember? Oh, you don’t remember my assurances of great pay, travel, wonderful colleagues, tremendous opportunities to learn, and build your interpersonal skills. Well, that’s why you have been fired. But you can use your McKinsey email. Please, leave now. I have billable work to do that you obviously were not able to undertake and complete in a satisfactory manner. Oh, here’s your going away gift. It is a T shirt which says, ‘Loser@mckinsey.com.’”
Stephen E Arnold, April 4, 2024
Publishers and Libraries: Tensions Escalate
April 4, 2024
This essay is the work of a dumb dinobaby. No smart software required.
We doubt this is what Ben Franklin had in mind. With more and more readers turning to digital editions, ABC News reports, “Libraries Struggle to Afford the Demand for E-Books, Seek New State Laws in Fight with Publishers.” With physical books, the process of building a library collection is simple: a volume is purchased (or donated) then loaned out repeatedly until it is lost or disintegrates. But publishers have made the process for ebooks much more complicated. And costly. Journalist Susan Haigh writes:
“The digital titles often come with a price tag that’s far higher than what consumers pay. While one hardcover copy of [Robin] Cook’s latest novel costs the library $18, it costs $55 to lease a digital copy — a price that can’t be haggled with publishers. And for that, the e-book expires after a limited time, usually after one or two years, or after 26 checkouts, whichever comes first. While e-books purchased by consumers can last into perpetuity, libraries need to renew their leased e-material. The modestly funded West Haven Library has spent more than $12,000 over the last three years to lease just 276 additional digital titles beyond what patrons can access through a consortium of public libraries. Eighty-four of those books are no longer available. If that same amount had been spent on paper books, it would have covered about 800 titles. … Publishers, however, argue the arrangement is fair considering e-book licenses for libraries allow numerous patrons to ‘borrow’ them and the per-reader cost is much less expensive than the per-reader rate.”
Well,yes, that is how public libraries work. Or it used to be. Will publishers come for hard copies next? Librarians across the US are pushing for legislation to counter these trends, and bills have been proposed in several states. Any that get passed, though, will have to make it through Big Publishing’s legal challenges. See the write-up for some lawmakers’ strategies to do so. Will libraries, and the taxpayers that fund them, prevail over these corporations? Stay tuned.
Cynthia Murrell, April 4, 2024
Angling to Land the Big Google Fish: A Humblebrag Quest to Be CEO?
April 3, 2024
This essay is the work of a dumb dinobaby. No smart software required.
My goodness, the staff and alums of DeepMind have been in the news. Wherever there are big bucks or big buzz opportunities, one will find the DeepMind marketing machinery. Consider “Can Demis Hassabis Save Google?” The headline has two messages for me. The first is that a “real” journalist things that Google is in big trouble. Big trouble translates to stakeholder discontent. That discontent means it is time to roll in a new Top Dog. I love poohbahing. But opining that the Google is in trouble. Sure, it was aced by the Microsoft-OpenAI play not too long ago. But the Softies have moved forward with the Mistral deal and the mysterious Inflection deal . But the Google has money, market share, and might. Jake Paul can say he wants the Mike Tyson death stare. But that’s an opinion until Mr. Tyson hits Mr. Paul in the face.
The second message in the headline that one of the DeepMind tribe can take over Google, defeat Microsoft, generate new revenues, avoid regulatory purgatory, and dodge the pain of its swinging door approach to online advertising revenue generation; that is, people pay to get in, people pay to get out, and soon will have to subscribe to watch those entering and exiting the company’s advertising machine.
Thanks, MSFT Copilot. Nice fish.
What are the points of the essay which caught my attention other than the headline for those clued in to the Silicon Valley approach to “real” news? Let me highlight a few points.
First, here’s a quote from the write up:
Late on chatbots, rife with naming confusing, and with an embarrassing image generation fiasco just in the rearview mirror, the path forward won’t be simple. But Hassabis has a chance to fix it. To those who known him, have worked alongside him, and still do — all of whom I’ve spoken with for this story — Hassabis just might be the perfect person for the job. “We’re very good at inventing new breakthroughs,” Hassabis tells me. “I think we’ll be the ones at the forefront of doing that again in the future.”
Is the past a predictor of future success? More than lab-to-Android is going to be required. But the evaluation of the “good at inventing new breakthroughs” is an assertion. Google has been in the me-too business for a long time. The company sees itself as a modern Bell Labs and PARC. I think that the company’s perception of itself, its culture, and the comments of its senior executives suggest that the derivative nature of Google is neither remembered nor considered. It’s just “we’re very good.” Sure “we” are.
Second, I noted this statement:
Ironically, a breakthrough within Google — called the transformer model — led to the real leap. OpenAI used transformers to build its GPT models, which eventually powered ChatGPT. Its generative ‘large language’ models employed a form of training called “self-supervised learning,” focused on predicting patterns, and not understanding their environments, as AlphaGo did. OpenAI’s generative models were clueless about the physical world they inhabited, making them a dubious path toward human level intelligence, but would still become extremely powerful. Within DeepMind, generative models weren’t taken seriously enough, according to those inside, perhaps because they didn’t align with Hassabis’s AGI priority, and weren’t close to reinforcement learning. Whatever the rationale, DeepMind fell behind in a key area.
Google figured something out and then did nothing with the “insight.” There were research papers and chatter. But OpenAI (powered in part by Sam AI-Man) used the Google invention and used it to carpet bomb, mine, and set on fire Google’s presumed lead in anything related to search, retrieval, and smart software. The aftermath of the Microsoft OpenAI PR coup is a continuing story of rehabilitation. From what I have seen, Google needs more time getting its ageingbody parts working again. The ad machine produces money, but the company reels from management issue to management issue with alarming frequency. Biased models complement spats with employees. Silicon Valley chutzpah causes neurological spasms among US and EU regulators. Something is broken, and I am not sure a person from inside the company has the perspective, knowledge, and management skills to fix an increasingly peculiar outfit. (Yes, I am thinking of ethnically-incorrect German soldiers loyal to a certain entity on Google’s list of questionable words and phrases.)
And, lastly, let’s look at this statement in the essay:
Many of those who know Hassabis pine for him to become the next CEO, saying so in their conversations with me. But they may have to hold their breath. “I haven’t heard that myself,” Hassabis says after I bring up the CEO talk. He instantly points to how busy he is with research, how much invention is just ahead, and how much he wants to be part of it. Perhaps, given the stakes, that’s right where Google needs him. “I can do management,” he says, ”but it’s not my passion. Put it that way. I always try to optimize for the research and the science.”
I wonder why the author of the essay does not query Jeff Dean, the former head of a big AI unit in Mother Google’s inner sanctum about Mr. Hassabis? How about querying Mr. Hassabis’ co-founder of DeepMind about Mr. Hassabis’ temperament and decision-making method? What about chasing down former employees of DeepMind and getting those wizards’ perspective on what DeepMind can and cannot accomplish.
Net net: Somewhere in the little-understood universe of big technology, there is an invisible hand pointing at DeepMind and making sure the company appears in scientific publications, the trade press, peer reviewed journals, and LinkedIn funded content. Determining what’s self-delusion, fact, and PR wordsmithing is quite difficult.
Google may need some help. To be frank, I am not sure anyone in the Google starting line up can do the job. I am also not certain that a blue chip consulting firm can do much either. Google, after a quarter century of zero effective regulation, has become larger than most government agencies. Its institutional mythos creates dozens of delusional Ulysses who cannot separate fantasies of the lotus eaters from the gritty reality of the company as one of the contributors to the problems facing youth, smaller businesses, governments, and cultural norms.
Google is Googley. It will resist change.
Stephen E Arnold, April 3, 2024
Open Source Software: Fool Me Once, Fool Me Twice, Fool Me Once Again
April 1, 2024
This essay is the work of a dumb dinobaby. No smart software required.
Open source is shoved in my face each and every day. I nod and say, “Sure” or “Sounds on point”. But in the back of my mind, I ask myself, “Am I the only one who sees open source as a way to demonstrate certain skills, a Hail, Mary, in a dicey job market, or a bit of MBA fancy dancing. I am not alone. Navigate to “Software Vendors Dump Open Source, Go for Cash Grab.” The write up does a reasonable job of explaining the open source “playbook.”
The write up asserts:
A company will make its program using open source, make millions from it, and then — and only then — switch licenses, leaving their contributors, customers, and partners in the lurch as they try to grab billions.
Yep, billions with a “B”. I think that the goal may be big numbers, but some open source outfits chug along ingesting venture funding and surfing on assorted methods of raising cash and never really get into “B” territory. I don’t want to name names because as a dinobaby, the only thing I dislike more than doctors is a legal eagle. Want proper nouns? Sorry, not in this blog post.
Thanks, MSFT Copilot. Where are you in the open source game?
The write up focuses on Redis, which is a database that strikes me as quite similar to the now-forgotten Pinpoint approach or the clever Inktomi method to speed up certain retrieval functions. Well, Redis, unlike Pinpoint or Inktomi is into the “B” numbers. Two billion to be semi-exact in this era of specious valuations.
The write up says that Redis changed its license terms. This is nothing new. 23andMe made headlines with some term modifications as the company slowly settled to earth and landed in a genetically rich river bank in Silicon Valley.
The article quotes Redis Big Dogs as saying:
“Beginning today, all future versions of Redis will be released with source-available licenses. Starting with Redis 7.4, Redis will be dual-licensed under the Redis Source Available License (RSALv2) and Server Side Public License (SSPLv1). Consequently, Redis will no longer be distributed under the three-clause Berkeley Software Distribution (BSD).”
I think this means, “Pay up.”
The author of the essay (Steven J. Vaughan-Nichols) identifies three reasons for the bait-and-switch play. I think there is just one — money.
The big question is, “What’s going to happen now?”
The essay does not provide an answer. Let me fill the void:
- Open source will chug along until there is a break out program. Then whoever has the rights to the open source (that is, the one or handful of people who created it) will look for ways to make money. The software is free, but modules to make it useful cost money.
- Open source will rot from within because “open” makes it possible for bad actors to poison widely used libraries. Once a big outfit suffers big losses, it will be hasta la vista open source and “Hello, Microsoft” or whoever the accountants and lawyers running the company believe care about their software.
- Open source becomes quasi-commercial. Options range from Microsoft charging for GitHub access to an open source repository becoming a membership operation like a digital Mar-A-Lago. The “hosting” service becomes the equivalent of a golf course, and the people who use the facilities paying fees which can vary widely and without any logic whatsoever.
Which of these three predictions will come true? Answer: The one that affords the breakout open source stakeholders to generate the maximum amount of money.
Stephen E Arnold, April 1, 2024
Commercial Open Source: Fantastic Pipe Dream or Revenue Pipe Line?
March 26, 2024
This essay is the work of a dumb dinobaby. No smart software required.
Open source is a term which strikes me as au courant. Artificial intelligence software is often described as “open source.” The idea has a bit of “do good” mixed with the idea that commercial software puts customers in handcuffs. (I think I hear Kumbaya playing faintly in the background.) Is it possible to blend the idea of free and open software with the principles of commercial software lock in? Notable open source entrepreneurs have become difficult to differentiate from a run-of-the-mill technology company. Examples include RedHat, Elastic, and OpenAI. Ooops. Sorry. OpenAI is a different type of company. I think.
Will open source software, particularly open source AI components, end up like this private playground? Thanks, MSFT Copilot. You are into open source, aren’t you? I hope your commitment is stronger than for server and cloud security.
I had these open source thoughts when I read “AI and Data Infrastructure Drives Demand for Open Source Startups.” The source of the information is Runa Capital, now located in Luxembourg. The firm publishes a report called the Runa Open Source Start Up Index, and it is a “rosy” document. The point of the article is that Runa sees open source as a financial opportunity. You can start your exploration of the tables and charts at this link on the Runa Capital Web site.
I want to focus on some information tucked into the article, just not presented in bold face or with a snappy chart. Here’s the passage I noted:
Defining what constitutes “open source” has its own inherent challenges too, as there is a spectrum of how “open source” a startup is — some are more akin to “open core,” where most of their major features are locked behind a premium paywall, and some have licenses which are more restrictive than others. So for this, the curators at Runa decided that the startup must simply have a product that is “reasonably connected to its open-source repositories,” which obviously involves a degree of subjectivity when deciding which ones make the cut.
The word “reasonably” invokes an image of lawyers negotiating on behalf of their clients. Nothing is quite so far from the kumbaya of the “real” open source software initiative as lawyers. Just look at the licenses for open source software.
I also noted this statement:
Thus, according to Runa’s methodology, it uses what it calls the “commercial perception of open-source” for its report, rather than the actual license the company attaches to its project.
What is “open source”? My hunch it is whatever the lawyers and courts conclude.
Why is this important?
The talk about “open source” is relevant to the “next big thing” in technology. And what is that? ANSWER: A fresh set of money making plays.
I know that there are true believers in open source. I wish them financial and kumbaya-type success.
My take is different: Open source, as the term is used today, is one of the phrases repurposed to breathe life in what some critics call a techno-feudal world. I don’t have a dog in the race. I don’t want a dog in any race. I am a dinobaby. I find amusement in how language becomes the Teflon on which money (one hopes) glides effortlessly.
And the kumbaya? Hmm.
Stephen E Arnold, March 26, 2024
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