What a shit concert LOL but I’m just glad E was with me.

Before starting Day 5, I noticed that I forgot to add ESLint, Prettier, and proper typechecking on project init.

So I've added it and also run into an issue in my Neovim config. Where I was unable to use some LSP methods. The solution was that I tried to use a tool that was not installed, and after the typescript-tools migration for Neovim v0.11, this tool initialization was failing silently and causing some problems. Strange that this is only recently an issue. But ok, I found a fix, and now my Neovim is back working again with TypeScript. :)

After adding ESLint, Prettier, and proper typechecking with my now working Neovim, I resolved some issues, and the project is now “clean.”

---

63 of #100DaysToOffload
#log #AdventOfProgress
Thoughts?

The Advent of code started a few days ago, and this year I decided to implement my solutions in Clojure.

My solutions in this repo: https://github.com/dimiro1/adventofcode2025-clj

Later I will update this post with my overall impressions on the challenges of this year.

para qué más si cada palabra nos encierra

o sigue para que las palabras nos liberen

Fight On! issue 17 now available on DTRPG and Lulu (POD and PDF)!

Massive issue counting 164 pages (!)—twelve pages more than the titanic third issue—featuring adventures, monsters, classes, artwork, and essays from over thirty contributors. Scroll down for full table of contents.

I contributed 7 Contrarian Practices for Running Online Games essay, outlining practices from our long-running sandbox game. This is a continuation of the 21 Lessons Learned After Running 100 Sessions essay published in the previous issue, which resonated with many readers. Several wrote to me and asked if I could write more about how we play online.

Bigger than a bull baluchitherium barreling through Bucklebury, Fight On! is BACK! Writers and artists old and new proudly present a whopping 166 PAGES of men, magic, monsters, treasures, underworlds, and wilderness adventures for your dreamworld delectation! It’s never been a better day to Fight On!

Discerning dungeoneers and daring dilettantes alike will be DAZZLED with articles, adventures, and art by Toren Atkinson, Attronarch, Zhu Baijee, Rick Base, J. Blasso-Gieseke, Calithena, Paul Carrick, Dr. John Cichowski, Jasmine Collins, Geoffrey O. Dale, Patrick Farley, Graphite Prime, Idle Doodler, Kelvin Green, Allan Grohe, Philipp H., Dave Hargrave, Cameron Hawkey, Kesher, Gabor Lux, Ripley Matthews, James Maliszewski, James Mishler, Michael Mornard, Peter Mullen, Prince of Nothing, Steve Queen, Glenn Robinson, DeWayne Rogers, Frank Scacalossi, Daniel Scherrey, Robert Scudder, Settembrini, Dan Sousa, Oakes Spalding, Anthony Stiller, Paul Swanlund, Del Teigeler, Andrew Walter, Bill Webb, Jennifer Weigel, Alex Zisch, and many more! Don’t delay – score your copy today!

Here is the table of contents:

Article	Author(s)	Page
Reptiles and Samurai	Calithena	5
Martial Stances	Jeff Hollifield	12
Grognard’s Grimoire: Codex of Droon	Matt the Bastard DM	14
Knights & Knaves: Stumble	Paul Swanlund	18
New Kindred for Tunnels & Trolls!	Kesher	20
Return of the Ancients	Prince of Nothing	22
Creepies & Crawlies: The Thoul	Allan Grohe	42
Spiders, Spiders, Spiders!	James Mishler	50
Lobogolem “Laster”	Del L. Beaudry	61
Gems of Zylarthen, Part II	Oakes Spalding	62
Black Powder Firearms	Jack Griffis	68
Artifacts, Adjuncts, & Oddments	Various	72
The Eshkom District	James Maliszewski	75
Under Samora: Al’Murtok’s Refuge	Philipp H.	85
Contrarian Practices Online	Attronarch	101
Running for Large Groups	Bill Web	103
Portal Fantasy Protagonists	Will Mistretta	105
Saint Cuthbert of Lindisfarne	H. Kazantzakis	108
The Charioteer’s Shrine	Gabor Lux	111
Tables for Fables	Reilly, Koed & Blasso-Gieseke	116
Lady Omen’s Island	Glenn Robinson	122
Memories of Dave Sutherland	Michael Mornard	143
Demonweb Savanna	Alex Zisch	145
Rose Bush Hedge Maze	Geoffrey O. Dale	151
Chainmail / Sarissa: Fomalhaut	Settembrini / Gabor Lux	155
Doxy, Urgent Care Cleric	Linneman / Green	162
Humor & Art	J. B-G, Cal, Queen, and Scherrey	163

Back issues are available via DTRPG and Lulu.

#News #OSR #FightOn

I shall apply Chatham House Rules, where no names nor affiliations may be revealed, though discussions may be reproduced outside of the discussion room.

---

Q: How do you handle fame? It's so easy to get lost in ego and fame. Bon Jovi said: “Fame is a liar and a thief. I've seen it ruin people. It is what I do, and I do it well, but it does not define me. I have a family, a business, and tennis.” Fame can be so destructive.

A: Don't define your worth based on who takes a photo with you after red-carpet events, or how many followers you have on social media. Find the people you look up to, such as directors or other actors, and ask them for their feedback on your craftsmanship as an actor. If you believe your own publicity, then you will also believe the negative comments.

Q: do you think your roles represent you as the person you want to be? You have worn many hats – you have been an actor, a producer, and a director.

A: [chuckles.] That's quite a meta- kind of question. [pause] I bring my best self to work. I show up on time. On set, I give everyone the time of day: the AD (Assistant Director), the ADPA (Assistant Director Production Assistant), and the caterer. There are so many people on set. And, I like tequila, [audience laughs] but 48 hours before a shoot, I avoid drinking. If you can hold your liquor, that's fine, but that's how I conduct myself. I don't know if this behaviour represents my race, my ethnicity, and my nationality, but that's what I do.

Q: how did it happen? How did you get inside the world of [redacted]?

A: Well, I met this guy, [redacted], in [redacted]. I don't know what possessed me, but I gave him a bunch of cards, and said, “Here are my head shots”. One year later, he called me up on a Thursday, and said, “The casting director wants to see you on Saturday, in [redacted].” Now, there was no way I could get from [redacted] to [redacted] on such short notice. And you know how casting calls work in [redacted], you have a specific time that you show up, say, 5.27 PM, and if you are not there, you're out. But, you know, my niece – she's here today, in the audience – and my mother, they went with me to the airport. They said, “It doesn't matter, the size [of your travel expenses]. This is your dream, right?”

So I flew over, I rented a car, and I went to [redacted]. And I was very jet-lagged, and I entered the room, and I saw ten other people, who all looked just like me. [audience laughs.] And, I have been directing for years, I haven't auditioned in a while, and my nerves were starting to get to me. And then I went into the room – there is a Flow state that musicians have, you know, where you just get lost in the music – well, I went into the room, and I said my lines, and then I left the room, and after that, I realised I couldn't recall what I did in that room. Not a thing.

And then I waited six weeks, paying for my lodging, out of my own pocket, and then they called me in for a second audition. And it gets even more nerve-racking, because you're closer now, but there's also a chance that everything could end for you, just like that [snaps fingers]. Behind actors' huge confidence is a huge sense of insecurity and fear. [audience giggles.]

And you think the Casting Director can get you in, but the Casting Director is just the beginning. You have to talk to the Studios, to see if they want you, and then you have to talk to the director. This director, [redacted], he meets people in person, for the smallest role. There was this character who has only one line in the whole movie – he says: [redacted] – and the director went to have coffee with him, just to hear him say that one line.

So, some time later, I was driving, and I got a call. And [redacted] said, “are you sitting down?” I said, “I'm not, I'm driving! But I will try to stop driving.” So I pulled into a gas station, and then she said, “You got it.”

And I don't have enough time to tell you everything that I have seen on set, the lovely actors I've met.

Sometimes I look at the sound stage, I look at the stunt crew, and I just let it all sink in. The night before, I'm rehearsing my lines in my head, and saying them out loud, over and over – so that it comes out as naturally as possible – but when I arrive on set, and see everything moving, I just have to let it sink in: “This is really happening.”

#acting

moon drenched night of softly sung velvet near the fragrant edge — what thicket of leaves!

sway, windswept boughs of gold into quiet spears spindled

04.12.2025, fragment

In the late 90s and early 00s, a casual stroll through the internet could spawn dozens or more pop-over and pop-under ads. Browsers helped us fight against intrusive pop-up ads.

Today, we're in a similar situation to what we faced in the early 00s except this time, our browsers have betrayed our trust.

Simple to complex

In the earlier days of the web, websites were relatively simple. You could scroll and read. You could click on links that took you to other places. By the time I was using a web browser, graphics were displayed on the websites directly. That's an innovation that didn't exist in the earliest browsers. Adding images? An improvement. I suspect that's where ads really kicked off, but we'll get there.

Eventually, people and companies wanted to do more with their browsers than just read, scroll, click, and look at images. Eventually, we'd want to do everything in our browser that we could do in our computers. That's a story for another day but it's not just a bunny trail. Nope, we're stopping at this sight seeing spot for a reason. In the mid-90s, Javascript was invented.

The Pop-up War

HTML isn't a programming language in the same way that Basic, C, Perl, etc. are. It's a markup language, designed to format and display hypertext. Javascript let you run programs in your browser. At first, they were simple. But not too simple to avoid the creation of one of the first great menaces of the internet: the pop-up ad.

You're browsing a site — perhaps several — and suddenly a new window pops up. It's got an ad in it. Extremely annoying. You close it. Maybe it opens another. Soon, you're playing whack-a-mole with pop-ups.

Eventually, the pop-up ad was replaced by something even more nefarious: the pop-under. Unless you're watching your taskbar closely, you don't even realize that a casual stroll through the internet is spawning dozens of ad windows you'll have to deal with once you've stopped your session. It was a menace that users couldn't effectively control themselves. Outside intervention was needed.

That intervention came from the browsers themselves. According to Wikipedia, by 2004, even Internet Explorer had pop-up blocking.

Like the flu, pop-overs and pop-unders haven't really gone away. Nefarious advertisers on the seedier parts of the internet use all sorts of tricks to get around the protection that every browser offers today.

The war is over, though. With browsers as our champions, users won.

All Your Data

Our current battle has been going on for a while. Ads are a vital part of revenue for the web but they're out of control.

The advertisers have fancy new tools to ensure that they can tie everything you do on the internet to a profile they can use to advertise to you. It's a surveillance state that would make Jeremy Bentham blush. But don't worry! The only thing they want is to sell us things! And sell our data to others. And manipulate our vote. But that's the absolute limit, we swear!

What else is there?

As if those things weren't reprehensible enough, they've also made most news sites unusable. Try reading an article while the page moves around underneath you as ads load in and out. Random videos play without any interaction. Trying to select some text to highlight it takes you to new pages.

The most popular browser, Chrome, is owned by one of the largest advertising companies in the world. Chrome doesn't want you running a real, effective ad blocker so they've shut down the interfaces that allow a plug-in to be effective at ad-blocking.

Safari at least gives you an option to use Reader Mode so the page doesn't move around on you while you read. It's also pretty far behind and incompatible with much of the more recent web developments.

Peanut Butter Jelly Time

It's time for browsers to stop betraying their users.

You can have ads. They can't be abusive, though. They can't continue to J. Edgar Hoover our private data and track us. They can't bog down our browsers so much that we have to close them to get our computers' fans to stop blasting hot air continuously. They can't render websites unusable by loading in and out or click hijacking.

Browsers, it's time to implement ad-blocking. Not for ads that respect the privacy of readers and behave themselves in the browser. Pop-up blocking was never about blocking ads. It was about the bad behavior.

Until browsers turn things around, get yourself a browser that will work with an ad blocker. I like Ad Nauseam. Among other things, it lets me see ads on sites that don't use trackers, rewarding sites that are behaving themselves.

Shameless self-promotion

This 'ad' won't track you. It doesn't know who you are. It won't even know if you clicked on it. 😹 If you enjoyed my rant disguised as part history and part advocacy, please consider checking out my first book.

The passengers of the Scampering Pete are on their way to Oshang Daro. If they had more money, they probably would have taken another transit. When the captain of the ship takes ill, five passengers rise to the occasion. Each were looking for a new start and the opportunity presented may be just what they were looking for. Assuming they can survive it!

Death In Transit is now available across ebook stores including Amazon, Apple, Barnes & Noble, Kobo, Everand, Thalia, Smashwords, Vivlio, and Fable.

#Technology

Existence is not a choice, feeding a hunger is.

The ancient sea turtle does not ask for the wet into which it slips,

Nor the cephalopod for the dark that winds around it like a slow, deliberate hand.

The humble flower never chooses the sun that coaxes it open— petal by trembling petal— as if undressing it.

Nor does the gentle butterfly petition the garden where it lands; wings and proboscis quivering at the first shy contact.

But he—

Just a foolish boy with a body too alive for sleep— chose the night instead of rest.

He claimed a patch of earth, bare and waiting, breath shallow in his throat, heart beating hard enough to heat his own skin.

There he made the one choice that undid him— to open himself fully, ribs loosened, defenses stripped away like clothing left behind.

And when her star fell, it did not simply touch him; it pressed against him, sliding into every place he had left unguarded— and in that slow, luminous descent, it melted him from within, leaving heat where longing had once lived alone.

---

In Summary: * No complaints about this Thursday at all. Gregorian Chant is playing in my room now, and I still have some night prayers to get to, then a bit of reading, then to bed. That is my plan for the remainder of this night.

Prayers, etc.: * My daily prayers

Health Metrics: * bw= 220.02 lbs. * bp= 147/91 (62)

Exercise: * kegel pelvic floor exercise, half squats, calf raises, wall push-ups

Diet: * 05:50 – 1 peanut butter sandwich * 07:10 – sausage, pancakes, biscuit & jam, 1 breakfast taco * 11:30 – fried chicken, white bread and butter * 16:45 – 1 fresh orange

Activities, Chores, etc.: * 04:30 – listen to local news talk radio * 05:50 – bank accounts activity monitored * 05:55 – read, pray, listen to news reports from various sources * 13:30 to 14:30 – watch old game shows with Sylvia * 14:45 – follow news reports from various sources * 17:00 – listening to The Joe Pags Show * 18:00 – tuning into an NCAA women's basketball game, Arkansas Razorbacks vs. SMU Mustangs * 20:00 – Congrats to the SMU Lady Mustangs who defeated Arkansas 78-63. Now I'll finish my night prayers, put on some relaxing music, and read for a bit before bedtime.

Chess: * 11:15 – moved in all pending CC games

The smartphone in your pocket contains a curious paradox. Apple, one of the world's most valuable companies, builds its own chips, designs its own operating system, and controls every aspect of its ecosystem with obsessive precision. Yet when you tap Safari's search bar, you're not using an Apple search engine. You're using Google. And Google pays Apple a staggering $20 billion every year to keep it that way.

This colossal payment, revealed during the US Department of Justice's antitrust trial against Google, represents far more than a simple business arrangement. It's the visible tip of a fundamental transformation in how digital platforms compete, collaborate, and ultimately extract value from the billions of searches and queries humans perform daily. As artificial intelligence reshapes the search landscape and digital assistants become genuine conversational partners rather than glorified keyword matchers, these backend licensing deals are quietly redrawing the competitive map of the digital economy.

The stakes have never been higher. Search advertising generated $102.9 billion in revenue in the United States alone during 2024, accounting for nearly 40 per cent of all digital advertising spending. But the ground is shifting beneath the industry's feet. AI-powered search experiences from OpenAI's ChatGPT, Microsoft's Copilot, and Google's own AI Overviews are fundamentally changing how people find information, and these changes threaten to upend decades of established business models. Into this volatile mix come a new wave of licensing deals, platform partnerships, and strategic alliances that could determine which companies dominate the next generation of digital interaction.

When Search Was Simple

To understand where we're heading, it helps to grasp how we got here. Google's dominance in search wasn't accidental. The company built the best search engine, captured roughly 90 per cent of the market, and then methodically paid billions to ensure its search bar appeared by default on every device that mattered. Apple, Samsung, Mozilla, and countless other device manufacturers and browser makers accepted these payments, making Google the path of least resistance for billions of users worldwide.

The economics were brutally simple. Google paid Apple $20 billion annually, representing roughly 21 per cent of Apple's entire services revenue in 2024. In exchange, Google maintained its dominant position in mobile search, where it captured nearly 95 per cent of smartphone searches. For Apple, this represented essentially free money, high-margin revenue that required no product development, no customer support, no operational complexity. The company simply collected a 36 per cent commission on advertising revenue generated from Safari searches.

Judge Amit Mehta, in his landmark August 2024 ruling in United States v. Google LLC, described this arrangement with clinical precision: “Google is a monopolist, and it has acted as one to maintain its monopoly.” The 277-page opinion found that Google's exclusive contracts violated Section 2 of the Sherman Act, maintaining illegal monopoly power in general search services and text advertising markets.

Yet even as the legal system caught up with Google's practices, a more profound transformation was already underway. The rise of large language models and generative AI was creating an entirely new category of digital interaction, one where traditional search might become just one option among many. And the companies positioning themselves for this future weren't waiting for courts to dictate the terms.

When Assistants Get Smart

Apple's June 2024 partnership announcement with OpenAI marked a watershed moment. The integration of ChatGPT, powered by GPT-4o, into iOS, iPadOS, and macOS represented something fundamentally different from the Google search deal. This wasn't about directing queries to an existing search engine; it was about embedding advanced AI capabilities directly into the operating system's fabric.

The deal's structure reveals the shifting economics of the AI era. Unlike the Google arrangement, where billions of dollars changed hands annually, the OpenAI partnership reportedly involves no direct payment from Apple to OpenAI. Instead, OpenAI gains exposure to over one billion potential users across Apple's device ecosystem. Users can access ChatGPT for free without creating an account, and premium ChatGPT subscribers can connect their accounts to access advanced features. For OpenAI, the deal represents a potential path to reaching one billion users, a scale that could transform the company's trajectory.

But here's where it gets interesting. Apple didn't abandon Google when it partnered with OpenAI. The Google search deal continues, meaning Apple now has two horses in the race: traditional search through Google and conversational AI through OpenAI. Siri, Apple's long-struggling digital assistant, can now call upon ChatGPT when it encounters queries beyond its capabilities, whilst maintaining Google as the default search engine for web searches.

This dual-track strategy reflects a crucial truth about the current moment: nobody knows exactly how the search and assistant markets will evolve. Will users prefer traditional search results with AI-generated summaries, as Google is betting with its AI Overviews feature? Or will they migrate to conversational AI interfaces that provide direct answers without traditional web links? Apple's strategy is to cover both scenarios whilst maintaining optionality.

Microsoft, meanwhile, had moved earlier and more aggressively. The company's multi-billion dollar investment in OpenAI, first disclosed in January 2023, gave it exclusive rights to integrate OpenAI's technology into its products. Bing, Microsoft's perennial search underdog, became the first major search engine to integrate GPT-4 directly into search results. The new Bing, announced in February 2023, promised to “reinvent search” by combining traditional web results with AI-generated summaries and conversational interactions.

The Microsoft-OpenAI arrangement differs fundamentally from the Apple-Google model. Rather than simply paying for default placement, Microsoft invested billions directly in OpenAI, reportedly securing 49 per cent of the company's profits until Microsoft recoups its investment. This structure aligns incentives more closely: Microsoft succeeds if OpenAI succeeds, and vice versa. The partnership granted Microsoft exclusive access to OpenAI's models for integration into commercial products, including not just Bing but also Office applications, Windows, and Azure cloud services.

Yet despite the technological leap, Bing's market share remains stubbornly low. Even with AI superpowers, Google's dominance barely budged. Google's search market share dipped below 90 per cent for the first time since 2015 in October 2024, but the company still controlled the vast majority of queries. This stubborn reality underscores a crucial lesson: technological superiority alone doesn't break entrenched defaults and user habits.

The Economics of Digital Gatekeeping

The financial mechanics behind these deals reveal the extraordinary value of controlling access points to digital information. Google paid a total of $26.3 billion in 2021 across all its default search placements, with $20 billion going to Apple alone. To put this in perspective, that's more than the entire annual revenue of many Fortune 500 companies, paid simply to remain the default choice.

These payments work because defaults matter enormously. Research on user behaviour consistently shows that overwhelming majorities never change default settings. When Google is the default search engine, around 95 per cent of users never switch. This makes default placement extraordinarily valuable, justifying multi-billion dollar payments that would seem absurd in a genuinely competitive market.

The business model creates what economists call a two-sided market with network effects. On one side, users generate queries. On the other, advertisers pay for access to those users. Google's dominance in search made it the essential platform for digital advertising, and that dominance was maintained partly through ensuring its search bar appeared everywhere users might look for information.

US search advertising revenues surged 15.9 per cent to reach $102.9 billion in 2024, according to the Interactive Advertising Bureau and PwC annual Internet Advertising Revenue Report. Google captured the lion's share, with search spending on Google rising 10 per cent year-over-year in the fourth quarter of 2024 alone. The average cost per click increased 7 per cent, demonstrating that even as queries grew, the value of each search remained robust.

But the AI revolution threatens to disrupt these economics fundamentally. Generative AI search tools experienced an astonishing 525 per cent revenue growth in 2024, albeit from a small base. More concerning for traditional search, studies found that Google search results featuring AI Overviews saw 34.5 per cent lower clickthrough rates compared to traditional results. When users get their answers directly from AI-generated summaries, they don't click through to websites, which undermines the entire advertising model built on those clicks.

Research firm SparkToro found that roughly 60 per cent of Google searches now end without a click to any website. Gartner predicted that traditional search engine volume will decline by 25 per cent by 2026 due to AI chatbot applications. If these trends continue, the entire economic foundation of search advertising could crumble, making those multi-billion dollar default placement deals look like investments in a declining asset.

This creates a fascinating strategic dilemma for companies like Google. The company must integrate AI features to remain competitive and meet user expectations for more sophisticated answers. Yet every AI-generated summary that satisfies a user's query without requiring a click potentially destroys a small amount of advertising value. Google is essentially forced to cannibalise its own business model to prevent competitors from doing it first.

New Street Research estimated that AI Overviews advertising would account for just 1 per cent of Google's search advertising revenues in 2025, growing to 3 per cent in 2026. But this gradual integration masked deeper uncertainties about long-term monetisation. How do you sell advertising against conversational AI interactions that don't involve clicking on links? Google's experiments with embedding ads directly in AI-generated summaries provided one answer, but it remained unclear whether users would accept this model or whether advertisers would pay comparable rates for these new formats.

The Regulatory Hammer Falls

Into this already complex landscape came regulators, wielding antitrust law with renewed vigour. Judge Mehta's August 2024 ruling that Google maintained an illegal monopoly in search triggered a lengthy remedies process, culminating in a May 2025 trial to determine how to restore competition.

The Department of Justice initially proposed aggressive remedies. The DOJ called for Google to divest Chrome, its web browser, and to end exclusive distribution agreements with device makers like Apple and Samsung. The department argued that only structural separation could prevent Google from using its control over key distribution channels to maintain its search monopoly.

Apple moved to intervene in the case, filing motions to defend its “contractual interests” in the Google relationship. The company argued that the Justice Department's efforts would harm consumers and stifle innovation, particularly in artificial intelligence. The filing revealed Apple's dependence on this revenue stream; analysts at J.P. Morgan estimated Apple faced a potential $12.5 billion annual revenue hit if courts forced Google to stop making payments.

The eventual ruling, delivered in September 2025, split the difference. Judge Mehta prohibited Google from entering or maintaining exclusive contracts relating to search distribution but stopped short of requiring Chrome's divestiture. Critically, the ruling allowed Google to continue making payments to partners, just not under exclusive terms. Apple and other partners would need to offer users genuine choices, but they could still receive payments for making Google one available option.

The ruling represented a partial victory for Apple and Google's business relationship whilst establishing important guardrails. As Judge Mehta noted, “Cutting off payments from Google almost certainly will impose substantial, in some cases, crippling, downstream harms to distribution partners.” Mozilla, maker of the Firefox browser, had revealed that search engine royalties totalled $510 million against total revenue of just $594 million in 2022, illustrating the existential dependence some companies had developed on these payments.

Across the Atlantic, European regulators took a different approach. The Digital Markets Act, which came into force in March 2024, designated six companies as “gatekeepers”: Alphabet, Amazon, Apple, ByteDance, Meta, and Microsoft. These companies faced strict obligations to enable interoperability, prohibit self-preferencing, and provide fair access to their platforms.

The European Commission opened non-compliance investigations against Alphabet, Apple, and Meta in March 2024. The Commission expressed concern that Alphabet's search preferenced its own vertical services, such as Google Shopping and Google Hotels, over rival offerings. By March 2025, the Commission had informed Alphabet that Google search treated the company's services more favourably than competitors, a violation of DMA provisions.

The DMA's approach differed from US antitrust enforcement in important ways. Rather than requiring proof of market harm through lengthy litigation, the DMA imposed ex ante obligations on designated gatekeepers, shifting the burden to these platforms to demonstrate compliance. Penalties could reach 10 per cent of global annual revenue for violations, or 20 per cent for repeated infringements. The Commission fined Apple €500 million and Meta €200 million in April 2025 for non-compliance.

Critically, the DMA required gatekeepers like Google to share data useful for training search models, potentially lowering barriers for alternative search engines. This provision acknowledged that in the AI era, access to training data mattered as much as access to users. A search engine couldn't compete effectively without both the scale to attract users and the data to train increasingly sophisticated AI models.

The Small Players' Dilemma

For smaller search engines and AI model providers, these backend deals and regulatory interventions created a complex and often contradictory landscape. Companies like DuckDuckGo and Ecosia had built businesses around privacy-focused search, capturing small but loyal user bases. DuckDuckGo held a 0.63 per cent worldwide market share, whilst Ecosia claimed 0.11 per cent.

But these alternative search engines faced a fundamental problem: they didn't actually operate their own search infrastructure. DuckDuckGo sourced its main search results from Bing and Yahoo. Ecosia's search content and advertisements came from Bing. This dependence on larger tech companies for backend infrastructure limited their ability to truly differentiate and left them vulnerable to changes in these upstream relationships.

The barrier to entry for building a competitive search index was immense. Google had spent decades and tens of billions of dollars crawling the web, indexing pages, and refining ranking algorithms. Microsoft's Bing represented a similar massive investment. Smaller players simply couldn't match this scale of infrastructure investment and ongoing operational costs.

In November 2024, Ecosia and Qwant announced a partnership to build a European search index, explicitly aiming to reduce dependence on US technology companies. The initiative acknowledged that the Digital Markets Act's requirement for Google to share data provided an opening, but it would take years and substantial investment to build a competitive alternative index.

The shift towards generative AI created additional barriers for smaller players. Training large language models required not just vast amounts of data but also expensive computing infrastructure. Smaller AI firms often faced 12 to 18-month wait times for GPU delivery, whilst well-capitalised hyperscalers secured priority access to scarce H100 and next-generation G100 accelerators through billion-dollar pre-purchase contracts.

Cloud infrastructure dependency compounded these challenges. Smaller AI companies weren't just running on the cloud; they were locked into it. Big Tech companies structured deals to ensure that partner rollouts were routed through their cloud infrastructure, creating additional revenue streams and control points. A startup building on Amazon's Bedrock platform or Microsoft's Azure AI services generated ongoing cloud computing fees for these giants, even if it charged end-users directly.

Yet open-source models provided some countervailing force. Over 50 per cent of foundation models were available with open weights, meaning an AI startup could download a state-of-the-art model and build on it rather than investing millions training from scratch. Meta's Llama models, Mistral's offerings, and numerous other open alternatives lowered barriers to entry for application developers, even if training truly frontier models remained the province of well-funded labs.

The Apple-OpenAI deal illustrated both the opportunities and limitations for AI startups in this environment. On one hand, OpenAI's access to over a billion Apple devices represented extraordinary distribution that no startup could hope to match independently. On the other, the deal didn't provide OpenAI with direct payment from Apple, relying instead on the assumption that exposure would drive premium subscriptions and enterprise deals.

For smaller AI model providers, securing similar distribution deals appeared nearly impossible. Anthropic, despite raising billions from both Amazon and Google, took a different path, focusing on enterprise partnerships with companies like Cognizant, Salesforce, and Palantir rather than pursuing consumer platform deals. Anthropic's strategy reflected a pragmatic assessment that without Apple or Google-scale consumer platforms, the path to scale ran through business customers and cloud marketplaces.

Amazon's $4 billion investment in Anthropic, completed in March 2024, illustrated the deepening vertical integration between cloud providers and AI model developers. The investment gave Anthropic capital and guaranteed compute access through Amazon Web Services, whilst Amazon gained a competitive AI offering for its cloud customers. Similar dynamics played out with Google's investments in Anthropic and Microsoft's OpenAI partnership.

These investment structures created a new kind of gatekeeping. If the major cloud providers each had preferred AI partners, smaller model developers might struggle to secure both the computing resources needed for training and the distribution channels necessary for reaching customers. The market appeared to be consolidating into a handful of vertically integrated stacks: Microsoft-OpenAI, Google-Anthropic-Google's own models, Amazon-Anthropic, and Apple's multi-partner approach.

Search Monetisation in the AI Era

The transition from traditional search to AI-powered experiences raised fundamental questions about monetisation. The old model was straightforward: users entered queries, search engines displayed results along with relevant advertisements, and advertisers paid per click. This generated enormous revenues because queries signalled clear intent, making search advertising uniquely valuable.

AI-powered interactions threatened to disrupt this model in multiple ways. When a user asked ChatGPT or Claude a question and received a comprehensive answer, no advertisement appeared, and no advertiser paid anyone. The AI companies were essentially providing information services without a clear revenue model beyond subscription fees and enterprise licensing.

Google faced this challenge most acutely. The company had begun rolling out AI Overviews, which used generative AI to provide summaries at the top of search results. These summaries answered many queries directly, reducing the need for users to click through to websites. Studies found that clicks for URLs included in AI Overviews decreased by 8.9 per cent compared to when they appeared as normal search result links.

For publishers and websites that relied on search traffic, this was potentially catastrophic. If AI systems summarised content without driving clicks, the entire ecosystem of ad-supported content faced an existential threat. This explained the wave of licensing deals between AI companies and publishers throughout 2024.

OpenAI signed content licensing deals with News Corp (reportedly worth over $250 million over five years), The Atlantic, Condé Nast, and Hearst. Microsoft signed deals with the Financial Times, Reuters, Axel Springer, and USA Today Network for its Copilot Daily feature. Google signed its first publisher deal with the Associated Press in January 2025. Amazon courted publishers for its reinvented Alexa, securing a deal with The New York Times.

These deals typically involved two components: one-off payments for training rights to historical content, and ongoing variable payments for featuring current content with attribution. Axel Springer's $25 million deal with OpenAI, for instance, included both a training payment and backend fees based on usage.

The licensing deals served multiple purposes. They provided AI companies with high-quality training data and current information to improve model accuracy. They gave publishers new revenue streams to offset declining search traffic and programmatic advertising revenue. And they began establishing a new economic model for the AI era, where content creators received compensation for their contributions to AI training and operation.

But the deals also raised competitive concerns. If only the largest, best-funded AI companies could afford expensive licensing arrangements with major publishers, smaller model providers faced yet another barrier to competing effectively. The cost of content licensing could become a significant moat, favouring incumbents over startups.

Moreover, these deals didn't solve the fundamental monetisation challenge. Even with licensed content, AI companies still needed business models beyond subscriptions. ChatGPT Plus cost $20 per month, whilst enterprise deals commanded higher rates, but it wasn't clear whether subscription revenue alone could support the massive computing costs of running large language models at scale.

Advertising remained the obvious answer, but integrating advertisements into conversational AI experiences proved challenging. Users had grown accustomed to ad-free interactions with ChatGPT and Claude. Introducing advertisements risked degrading the user experience and driving users to competitors. Yet without advertising or equivalently robust revenue models, it wasn't clear how these services could achieve sustainable profitability at massive scale.

Google's experiments with advertising in AI Overviews represented one potential path forward. By embedding contextually relevant product recommendations and sponsored content within AI-generated summaries, Google aimed to preserve advertising revenue whilst providing the enhanced experiences users expected. But clickthrough rates remained lower than traditional search advertising, and it remained to be seen whether advertisers would pay comparable rates for these new formats.

The average ad spending per internet user in the Search Advertising market was estimated at $58.79 globally in 2025. For AI-powered experiences to generate comparable revenue, they would need to capture similar or greater value per interaction. This seemed plausible for high-intent commercial queries but much harder for informational searches where users simply wanted answers without purchase intent.

Collaboration, Competition, and Consolidation

The deals between platform owners and AI providers, search engines and publishers, and cloud providers and model developers painted a picture of an industry in flux. Old competitive boundaries were dissolving as former rivals became strategic partners whilst ostensibly collaborating companies competed in adjacent markets.

Apple's dual strategy with Google and OpenAI exemplified this complexity. The company maintained its lucrative search deal with Google whilst simultaneously partnering with Google's primary AI competitor. This hedging strategy made sense during a transition period when the ultimate shape of user behaviour remained uncertain. But it also created tensions: how would Apple balance these relationships if Google's search and OpenAI's ChatGPT increasingly competed for the same queries?

The regulatory environment added further complexity. The September 2025 ruling allowed Google to continue making payments whilst prohibiting exclusivity, but the practical implementation remained unclear. How would Apple, Samsung, and other partners implement genuine choice mechanisms? Would users face decision fatigue from too many options, leading them to stick with familiar defaults anyway?

The European Digital Markets Act's more prescriptive approach demanded specific interoperability and data-sharing requirements, but enforcement remained challenging. The Commission's investigations and fines demonstrated willingness to punish non-compliance, yet the underlying market dynamics favouring scale and integration proved hard to counteract through regulation alone.

For smaller companies, the landscape appeared increasingly difficult. The combination of infrastructure barriers, data access challenges, capital requirements, and distribution bottlenecks created formidable obstacles. Open-source models provided some relief, but the gap between open models and the capabilities of frontier systems from OpenAI, Google, and Anthropic remained substantial.

The venture capital funding environment for AI startups remained robust, with billions flowing into the sector. But increasingly, strategic investments from cloud providers and large tech companies dominated financing rounds. These investments came with strings attached: compute credits tied to specific cloud platforms, distribution channels through investor platforms, and expectations about technology stack choices. The apparent abundance of capital masked a reality where meaningful independence from the major platforms became harder to maintain.

Industry consolidation appeared likely to continue. Just as the cloud infrastructure market concentrated into three major players (Amazon, Microsoft, and Google), the AI model and digital assistant markets seemed headed towards a similarly concentrated structure. The economics of scale in training, the advantages of vertical integration between models and distribution, and the network effects from user data all pushed towards consolidation.

Yet genuine innovation remained possible around the edges. Specialised models for specific domains, novel interaction paradigms, privacy-focused alternatives, and open-source collaboration all represented paths where smaller players could potentially carve out sustainable niches. The challenge was whether these niches could grow large enough to represent genuine alternatives to the dominant platforms.

The New Digital Divide

The backend deals reshaping search and digital assistants represent more than business arrangements between wealthy corporations. They reflect and reinforce a fundamental divide in the digital economy between companies with platform power and everyone else. Those controlling the devices people use, the operating systems running on those devices, and the default experiences presented to users wield extraordinary influence over which technologies succeed and which fail.

The $20 billion annual payment from Google to Apple isn't just a revenue stream; it's a tax on search monetisation that Google pays to maintain access to Apple's users. The multi-billion dollar investments in OpenAI and Anthropic aren't just capital allocations; they're defensive moats ensuring that Microsoft, Amazon, and Google maintain positions in whatever AI-powered future emerges.

For users, these deals often bring genuine benefits: better integrated experiences, more sophisticated capabilities, and services they can access without explicit payment. Apple users gained ChatGPT integration without monthly fees. Google users received AI-enhanced search results at no additional cost. The major platforms competed partly by giving away AI-powered features that would have seemed miraculous just years earlier.

Yet this largesse came with less visible costs. Competition constrained by billion-dollar barriers to entry was less vigorous than it might otherwise be. Innovation from smaller players struggled to reach users trapped behind platform gatekeepers. And the concentration of power in a handful of companies created systemic risks and governance challenges that societies were still learning to address.

The regulatory response, whilst increasingly aggressive, struggled to keep pace with market evolution. By the time courts ruled on Google's search monopoly, the market was already transitioning towards AI-powered experiences that might render traditional search less central. The remedies imposed risked fighting the last war whilst the next one had already begun.

Looking forward, the competitive dynamics for digital assistants and search monetisation will likely reflect broader patterns of platform power and vertical integration. Success will depend not just on building superior technology but on securing access to users, training data, computing infrastructure, and content licensing. The backend deals determining these access points will shape which companies thrive and which struggle to compete.

The market isn't winner-take-all, but neither is it a level playing field where merit alone determines outcomes. Platform power, network effects, capital resources, and strategic partnerships create strong advantages for incumbents and favourably positioned challengers. Smaller players can succeed, but increasingly only in partnership with or in niches uncontested by the major platforms.

For regulators, the challenge will be balancing the genuine benefits of integration and scale against the competitive and innovation harms from excessive concentration. Neither the US antitrust approach nor the EU's ex ante regulatory framework has yet found the right balance, and both will likely require continued adaptation as markets evolve.

The billion-dollar handshakes between platform owners and AI providers aren't ending anytime soon. They're evolving, becoming more sophisticated, and extending into new areas as the technological landscape shifts. Understanding these deals and their implications matters not just for industry insiders but for anyone concerned with how power, innovation, and value are distributed in the digital economy. The search bar on your phone isn't just a tool for finding information; it's a battleground where the future of digital interaction is being determined, one lucrative partnership at a time.

---

Sources and References

1. US Department of Justice. (2024, August 5). “Department of Justice Prevails in Landmark Antitrust Case Against Google.” Official press release. https://www.justice.gov/opa/pr/department-justice-prevails-landmark-antitrust-case-against-google

2. Mehta, A. (2024). United States v. Google LLC, Case No. 20-cv-3010. United States District Court for the District of Columbia. 277-page opinion.

3. IAB & PwC. (2024). “Internet Advertising Revenue Report 2024.” Reports $102.9 billion in US search advertising revenue, representing 39.8% of total digital advertising.

4. Fortune. (2025, July 30). “Apple risks $12.5 billion revenue hit as judge weighs Google antitrust remedies, J.P.Morgan warns.” https://fortune.com/2025/07/30/apple-google-jpmorgan-billion-revenue-hit-antitrust-doj-case/

5. OpenAI. (2024, June). “OpenAI and Apple announce partnership.” Official announcement. https://openai.com/index/openai-and-apple-announce-partnership/

6. Microsoft. (2023, February 7). “Reinventing search with a new AI-powered Microsoft Bing and Edge, your copilot for the web.” Official Microsoft Blog.

7. European Commission. (2024, March 25). “Commission opens non-compliance investigations against Alphabet, Apple and Meta under the Digital Markets Act.” Official press release.

8. Search Engine Land. (2024). “Google admits to paying Apple 36% of Safari revenue.” https://searchengineland.com/google-pay-apple-safari-revenue-antitrust-trial-434775

9. eMarketer. (2024). “Generative Search Trends 2024.” Reports 525% revenue growth for AI-driven search engines and 34.5% lower CTR for AI Overview results.

10. CNBC. (2024, November 12). “Ecosia, Qwant partner on search engine tech to counter Google's power.” Reports on European search index initiative.

11. Digiday. (2024). “2024 in review: A timeline of the major deals between publishers and AI companies.” Comprehensive overview of content licensing agreements.

12. Anthropic. (2024). “Anthropic and Salesforce expand partnership to bring Claude to regulated industries.” Official company announcement.

13. Statista. (2024). “US Google search ad revenue 2024.” Reports Google's search advertising revenue and market share data.

14. Gartner Research. (2024). Prediction of 25% decline in traditional search engine volume by 2026 due to AI chatbot applications.

15. SparkToro. (2024). Research finding that approximately 60% of Google searches end without a click to any website.

16. New Street Research. (2025). Analysis projecting AI Overviews advertising at 1% of Google search ad revenue in 2025, growing to 3% in 2026.

17. Harvard Law Review. (2024). “United States v. Google, LLC.” Legal analysis of the antitrust case. Volume 138.

18. Mozilla Foundation. (2023). Annual financial disclosure showing $510 million in search engine royalties against $594 million total revenue in 2022.

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Tim Green UK-based Systems Theorist & Independent Technology Writer

Tim explores the intersections of artificial intelligence, decentralised cognition, and posthuman ethics. His work, published at smarterarticles.co.uk, challenges dominant narratives of technological progress while proposing interdisciplinary frameworks for collective intelligence and digital stewardship.

His writing has been featured on Ground News and shared by independent researchers across both academic and technological communities.

ORCID: 0009-0002-0156-9795 Email: tim@smarterarticles.co.uk

The mob's roar outside Parliament was a living thing, throbbing against the stained-glass windows like a malarial fever. He adjusted his cravat with fingers still sticky from sealing those damning letters with wax—black, of course. “You've a talent for making enemies, my lord,” sneered the Chancellor, his rheumy eyes tracking the dagger-shadows on the wall. A half-smile. “Only way to know you're moving forward.” The pistol in his desk drawer weighed heavy with its single silver bullet. The first rock shattered a window. “Ah,” he murmured, watching the bloodied cobblestones below, “right on schedule.” History, after all, was just violence with better lighting.

#Scratch

The Architecture of Grief

I didn’t realize the moment I broke

was the same moment God began to rebuild me.

I thought I was being undone, losing strength, coming apart—

but something deeper was being uncovered,

a truer self I had kept quiet for most of my life.

For years I moved through the world small,

careful not to draw attention,

content to stay unseen.

But grief has a way of stripping off what you outgrew

while you weren’t paying attention.

And when my brother died,

something in me cracked in a way that didn’t collapse—

it opened.

It opened a place beneath the pain,

a place where peace rose up like it already knew the way.

Where strength I hadn’t earned began to steady me from the inside.

Where the still, small voice wasn’t small at all—

it was unmistakable.

And in the days that followed,

I found myself standing in rooms where I should have fallen apart.

Yet I was held.

And the room breathed with me.

And grief, instead of drowning me,

began lifting me—

wave after wave.

And then something shifted.

Because becoming was never meant to stay inside of me.

What God rebuilt in the quiet

was always meant to be released into the world.

There comes a moment when grief stops being only something you carry

and becomes something that carries you—

forward, outward, into the lives of others.

A moment when the breaking in you

becomes a doorway for someone else’s healing.

A moment when the voice you kept small for decades

finally rises with the weight of truth behind it—

not to take up space,

but to make space.

And in that turning point, something within me aligned—

a steadying, a knowing—

as if the path that God had been forming in silence

finally came into focus.

This isn’t expression.

It’s assignment.

It’s release.

Grief didn’t move me aside—

it moved me forward.

The calling didn’t free me from the breaking—

it used the breaking to reveal the path.

What God awakened in me

was never meant to end in me.

It was meant to move.

---

Isaiah 58:12 (KJV)

“And they that shall be of thee shall build the old waste places:

thou shalt raise up the foundations of many generations;

and thou shalt be called,

The repairer of the breach,

The restorer of paths to dwell in.”

---

Dedication

For Aaron —

whose life was a beacon of light, whose love brought warmth to all who knew him,

and whose leaving tore the ground open beneath me.

Your memory is the doorway through which this calling began to rise,

and the place where God began to rebuild me.

© SilentSentinel, 2025. All rights reserved. Excerpts may be shared with attribution.

---

La Arquitectura del Duelo

No me di cuenta de que el momento en que me quebré fue el mismo momento en que Dios comenzó a reconstruirme. Pensé que me estaba desmoronando, perdiendo fuerza, deshaciéndome— pero algo más profundo estaba siendo revelado, un yo más verdadero que había mantenido en silencio la mayor parte de mi vida.

Durante años caminé por el mundo siendo pequeño, con cuidado de no llamar la atención, contento de permanecer invisible. Pero el duelo tiene una manera de arrancar lo que ya habías superado mientras no estabas prestando atención.

Y cuando mi hermano murió, algo en mí se quebró de una manera que no colapsó— sino que se abrió.

Se abrió un lugar por debajo del dolor, un lugar donde la paz se levantó como si ya conociera el camino. Donde una fuerza que no había ganado empezó a sostenerme desde dentro. Donde la voz suave y apacible no era suave en absoluto— era inconfundible.

Y en los días que siguieron, me encontré de pie en habitaciones donde debería haberme derrumbado. Sin embargo, fui sostenido. Y el aire respiró conmigo. Y el duelo, en vez de ahogarme, comenzó a elevarme— ola tras ola.

Y entonces algo cambió.

Porque el llegar a ser nunca estuvo destinado a quedarse dentro de mí. Lo que Dios reconstruyó en la quietud siempre estuvo destinado a ser liberado al mundo.

Llega un momento en que el duelo deja de ser solo algo que cargas y se convierte en algo que te carga a ti— hacia adelante, hacia afuera, hacia la vida de otros.

Un momento en que la ruptura dentro de ti se convierte en una puerta hacia la sanidad de alguien más.

Un momento en que la voz que mantuviste pequeña durante décadas finalmente se eleva con el peso de la verdad detrás de ella— no para ocupar espacio, sino para abrirlo.

Y en ese punto de giro, algo dentro de mí se alineó— un aquietamiento, un saber— como si el camino que había estado formándose en silencio finalmente cobrara enfoque.

Esto no es expresión. Es asignación. Es envío.

El duelo no me apartó— me movió hacia adelante. El llamado no me liberó del quebranto— usó el quebranto para revelar el camino.

Lo que Dios despertó en mí nunca estuvo destinado a terminar en mí.

Estaba destinado a moverse.

---

Isaías 58:12 (RVR1960)

“Y los tuyos edificarán las ruinas antiguas; los cimientos de generación y generación levantarás; y serás llamado Reparador de portillos, Restaurador de sendas para habitar.”

---

Dedicatoria

Para Aaron — cuya vida fue un faro de luz, cuyo amor trajo calor a todos los que lo conocieron, y cuya partida desgarró la tierra bajo mis pies. Tu memoria es la puerta por la cual este llamado comenzó a levantarse, y el lugar donde Dios comenzó a reconstruirme.

© SilentSentinel, 2025. Todos los derechos reservados. Se pueden compartir extractos con atribución.

Listening now to an NCAA women's basketball game, Arkansas Razorbacks at SMU Mustangs broadcast live over Tunein. I'm counting on this game to help me relax and unwind from a rather stressful afternoon trying in vain to access my social security account online.

And the adventure continues.

Introduction

In my previous post “Was Flight MH370 Teleported?”, I broke down two viral videos that appear to show MH370 being surrounded by glowing orbs before vanishing in a flash of light. Whether you believe those videos are real or fake, one thing is clear: they sparked renewed interest in alternative theories about what happened to Flight 370.

But here is the thing. If those videos are real, there should be physical evidence. An event violent enough to make a Boeing 777 disappear would generate acoustic signatures detectable by underwater sensors thousands of kilometers away.

The Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) operates a network of highly sensitive underwater hydrophones throughout the world's oceans. These hydrophones are designed to detect nuclear explosions, but they can also pick up aircraft impacts, underwater explosions, and other violent events.

So what did those hydrophones record on March 8, 2014?

The answer is complicated. They recorded something. But more importantly, they recorded nothing during a critical 25-minute window at the station closest to Diego Garcia.

The Players: CTBTO Hydrophone Stations

The CTBTO operates hydroacoustic monitoring stations throughout the Indian Ocean. Three are particularly relevant to MH370:

Station	Location	Code
HA01	Cape Leeuwin, Western Australia	H01W
HA08	Diego Garcia, British Indian Ocean Territory	H08S/H08N
HA04	Crozet Islands, France	H04S

Each station consists of three hydrophones arranged in a triangular configuration, allowing researchers to determine both the bearing and approximate distance of acoustic events.

Diego Garcia is the location of HA08. It is also a remote coral atoll hosting a major U.S. military installation, Naval Support Facility Diego Garcia, which is shrouded in secrecy. The island has a 12,000-foot runway capable of handling any aircraft in the world.

Remember from Part 1: the coordinates embedded in the “satellite” video are approximately -8.834301, 93.19492, which places the supposed event south of the Nicobar Islands. Diego Garcia sits at approximately 7.3°S, 72.4°E. The distance between these two points is roughly 2,300 km.

Anomaly #1: The 25-Minute Data Gap

What Happened

At 03:07 UTC on March 8, 2014, all three hydrophones at the Diego Garcia station (HA08s) simultaneously stopped recording. They remained offline for exactly 25 minutes.

This is documented in a peer-reviewed paper by Dr. Usama Kadri of Cardiff University, published in Scientific Reports (Nature):

“A fifth signal appears at 3:07... This signal probably indicates restarting the system after it was shutdown for 25 minutes, i.e. there is missing data in these specific CTBTO recordings.”

Kadri, U. (2019). Effect of sea-bottom elasticity on the propagation of acoustic-gravity waves from impacting objects. Scientific Reports, 9, 912.

Why This Matters

Dr. Kadri explicitly addresses the suspicious nature of this gap:

“Due to the sensitivity of the recorded data, it is unlikely that the three hydrophones on HA08s had a simultaneous technical failure and the reason behind the shut down is to-date unknown.”

He then offers a possible explanation:

“A violent nearby activity (including impact, explosion) could have resulted in a shutdown of the system.”

Let that sink in. A scientist publishing in one of the world's most prestigious journals is stating on the record that:

1. A simultaneous failure of all three hydrophones is “unlikely”
2. The shutdown remains “unexplained” by the CTBTO
3. A violent nearby event, such as an aircraft impact or explosion, could cause such a shutdown

The Timeline and the Videos

The official narrative places MH370's crash at approximately 00:19 UTC on March 8, 2014, based on the final satellite “handshake.” But the Diego Garcia data gap occurs nearly 3 hours later.

Here is where it gets interesting. If you plot MH370's trajectory based on the coordinates in the video (-8.834301, 93.19492), the plane would have been in that area sometime between 00:30 and 01:30 UTC. The acoustic signal from such an event, depending on propagation path, would take anywhere from 30 minutes to 2 hours to reach Diego Garcia.

Time (UTC)	Event
18:22, March 7	Last radar contact with MH370
00:19, March 8	Final satellite handshake (official crash time)
~00:30-01:30, March 8	Estimated time at video coordinates (if direct flight from last radar)
01:58, March 8	Signal HA_32 detected at Diego Garcia (military bearing)
03:07, March 8	All three Diego Garcia hydrophones go offline
03:32, March 8	System comes back online
03:47-03:55, March 8	Three signals detected at nearly identical bearings (~170°)

If an acoustic event occurred at the video coordinates around 01:00-01:30 UTC, the signal would reach Diego Garcia somewhere between 02:30 and 03:30 UTC, depending on transmission path through the water and sea-bottom.

The data gap starts at 03:07 UTC. Right in the middle of that window.

Coincidence?

Anomaly #2: Diego Garcia Data “Dismissed” as Too Noisy

The Convenient Excuse

When the U.S. Los Alamos National Laboratory (LANL) analyzed CTBTO hydrophone data for MH370, they focused almost exclusively on the Cape Leeuwin (HA01) station. The Diego Garcia data? Dismissed.

From the official LANL report:

“Analysis of the data from these stations shows... large amplitude repeating signals at H08 that obscure any possible arrivals.”

Stead, R.J. (2014). Seismic and hydroacoustic analysis relevant to MH370. Los Alamos National Laboratory, LA-UR-14-24972.

The “noise” was attributed to seismic survey ships operating in the region. This explanation has been accepted uncritically by most researchers.

Dr. Alec Duncan's Assessment

Dr. Alec Duncan of Curtin University, who led the Australian acoustic analysis effort, also found the Diego Garcia data “unusable”:

“Duncan also analysed data from the other [station], off Diego Garcia island in the middle of the Indian Ocean, but found nothing. The data were too polluted by noises from seismic surveys, he says.”

Butler, D. (2014). Sound clue in hunt for MH370. Nature, 510, 199-200.

The Signal That Pointed Northwest

Here is what makes this dismissal suspicious. Duncan did find a promising signal at Cape Leeuwin, one that pointed to a location northwest of the official search area:

“The sound is believed to have originated somewhere along a strip running to the northwest of the Indian Ocean. That is out of the range of the current search.”

Curtin University's refined location estimate (September 2014) placed the signal origin at 2.11°N, 69.31°E, west of the Maldives, much closer to Diego Garcia than to the 7th arc search area.

This location is roughly 1,100 km from Diego Garcia. And it is within the general region suggested by the video coordinates.

This finding was dismissed as “inconsistent with other data about aircraft position,” meaning the satellite handshake data that forms the entire basis for the southern search.

Anomaly #3: Military Activity Detected During the Critical Window

What the Hydrophones Recorded

Kadri's 2019 paper documents military activity detected by the Diego Garcia hydrophones during the critical timeframe:

“Analyses of signals recorded at station HA08s... were more challenging, partially due to disturbances in the recordings that are believed to have been caused by military action in the region.”

The military signals were detected at two specific bearings:

• 219.2° from HA08s (southwest toward Mauritius/Madagascar)
• 309.7° from HA08s (northwest toward Maldives/India)

These signals were recorded “intermittently” between 23:00 UTC on March 7 and 04:00 UTC on March 8, precisely the window when MH370 would have been in the area.

The Signals from Table 3

Signal	Time (UTC)	Bearing	Distance	Location	Notes
HA_30	11:57 (Mar 7)	247.4°	585±276 km	9°34'S, 67°36'E	Closest to Diego Garcia
HA_31	12:11 (Mar 7)	170.9°	2,300±250 km	28°08'S, 76°20'E
HA_32	01:58 (Mar 8)	241.3°	2,860±900 km	19°05'S, 48°32'E	Within military bearings
HA_34a	03:47 (Mar 8)	170.9°	—	—	Immediately after restart
HA_34b	03:50 (Mar 8)	173.0°	—	—	Immediately after restart
HA_34c	03:55 (Mar 8)	170.9°	—	—	Immediately after restart

Notice the sequence immediately after the system came back online: three signals at nearly identical bearings (~170°) detected within 8 minutes. What did the hydrophones capture the moment they resumed recording?

Kadri notes:

“Note that bearings of signals HA30 and HA32 fall within the military action bearings, so it is also possible that the signals are associated with the military action.”

Connecting to the Videos

In Part 1, I discussed how the videos appear to show military surveillance footage, specifically what looks like Gorgon Stare imagery from an MQ-9 Reaper drone. The second “drone” video shows the same event from a different angle.

If the U.S. military was operating surveillance drones in that area, and if something happened to MH370 that they witnessed (or caused), the “military action” detected by the hydrophones could be related.

Anomaly #4: Cocos Keeling Infrasound Data Never Released

The Silent Witnesses

Cocos Keeling Island sits in the Indian Ocean between the Maldives and Australia. It hosts an array of eight infrasound recorders (station IM.I06) that were continuously collecting data during MH370's disappearance.

This data has never been made public.

From 370Location.org:

“There is an array of eight infrasound recorders at Cocos Keeling West Island that was continuously collecting data during the flight of MH370. That data has been unavailable to the public.”

Two days after MH370 disappeared, the head of the CTBTO noted during a press briefing that their infrasound monitoring stations “would be most suitable for detecting an explosion or impact of the aircraft.” One day later, they released a report claiming no infrasound detections were found.

The Convenient Data Cutoff

In 2017, the CTBTO began releasing infrasound and hydrophone data to public seismic networks, including data from prior years.

For the Cocos Island array, that dataset starts on April 4, 2014.

MH370 disappeared on March 8, 2014.

The publicly released data begins exactly 27 days after the plane vanished. Everything before that remains classified.

The Time Zone Error That Invalidated the Analysis

In May 2014, Lawrence Livermore National Laboratory (LLNL) produced a poster report examining whether the Cocos Island infrasound array could detect aircraft. Their approach was sound: check whether the twice-daily A320 flights to and from Cocos Island airport were detectable on the infrasound array located just a few kilometers from the runway.

They found no infrasound events matching the known aircraft activity. This negative finding became the basis for dismissing further inquiry into the Cocos data.

There was just one problem: they made a time zone error.

From 370Location.org's detailed analysis:

“Ultimately, a simple time zone error flawed the analysis. While the poster listed the correct offsets for local time, UTC+6:30 for Cocos CCK and UTC+7:00 for Christmas CXT, those offsets were erroneously added instead of subtracted from local time to get UTC. The result was that the infrasound was being examined for expected flight traffic in the middle of the night when the airport was closed.”

Let that sink in. The analysis that was used to dismiss the Cocos Island infrasound data was looking at the wrong time window entirely. They were searching for aircraft signatures at 2 AM when no planes were flying.

Terminal departures from Cocos are scheduled for 13:43 and 15:59 local time, which is 07:13 and 09:29 UTC. The LLNL poster incorrectly listed these as 22:37 and 00:50 UTC, off by nearly 12 hours.

The Array Can Detect Aircraft

Independent researcher Ed Anderson later proved that the Cocos Island infrasound array absolutely can detect jet aircraft. Using publicly available data from April 2019 (after the March 2014 data was conveniently excluded), he demonstrated successful detection of commercial flights:

“This is firm confirmation that the Cocos Island infrasound array is capable of picking up jet traffic details.”

The 2019 analysis showed the array detecting:

• Jet engine throttle-up on the runway
• Aircraft movement down the runway
• Takeoff bearing and heading
• Approaches from 25 km away

The Signal at 22:22:22 UTC

Here is where it gets interesting. Despite the flawed official analysis, independent examination of available seismometer data from Cocos Island (station II.COCO) revealed something:

“The seismometer shows that there were no other significant acoustic events there besides the 22:22:22 candidate during the time between the fourth and fifth pings.”

A higher resolution sample from one of the infrasound sensors published in the LLNL poster shows a signal peak at 22:46:40 UTC.

This timing closely matches when MH370 would have crossed near Cocos Island if it flew toward Diego Garcia rather than south toward the 7th arc.

From 370Location.org:

“The Cocos Island infrasound array appears to be perfectly viable for detecting a flyby and confirming the nature of the event detected by the island seismometer.”

Why This Matters for the Videos

Remember: if MH370 flew toward the coordinates shown in the videos (-8.834°S, 93.195°E), it would have passed near Cocos Keeling Island. The flight path from last radar contact to the video coordinates runs almost directly over Cocos.

The infrasound array would have detected the aircraft's engine noise. A Doppler shift in the signal would indicate direction of travel.

If the raw infrasound data from March 7-8, 2014 showed MH370 heading northwest toward Diego Garcia rather than south toward the 7th arc, it would directly contradict the official narrative.

Instead, we have:

• Data conveniently classified until April 4, 2014
• An official analysis invalidated by a basic time zone error
• Independent proof that the array CAN detect aircraft
• A suspicious signal at 22:22-22:46 UTC that was never properly investigated

Source: 370Location.org: Cocos Island Infrasound May Be Key to Locating MH370

The Pattern of Suppression

When you step back and look at the acoustic evidence holistically, a troubling pattern emerges:

Data Source	Status	Official Explanation
Diego Garcia (HA08) hydrophones	Dismissed	"Too noisy from seismic surveys"
25-minute data gap	Unexplained	None provided by CTBTO
Cocos Keeling infrasound	Classified	"No evidence found" (methodology flawed)
Crozet Islands (HA04)	Never Analyzed	Not addressed
Military activity signals	Unexamined	Attributed to exercises
Curtin University signal	Dismissed	"Inconsistent with satellite data"

Every piece of evidence that could point toward Diego Garcia has been either dismissed, classified, or left unexplained.

The “Javanomaly”: A Strong Unexplained Signal

Independent researchers have identified additional signals that warrant investigation. One of the most compelling is what 370Location.org calls the “Javanomaly”:

“A very strong MH370 candidate signal was reported here a year ago, arriving at the Diego Garcia H08 hydrophone array from the direction of Java. The T-wave arrival is far stronger than a later M4.4 quake near Java and four times stronger on local seismometers than a nearby M4.1 quake.”

What makes this signal suspicious:

“Despite the stronger signals, this event was not included in earthquake catalogs like the others. Analysis of nearby seismometers places the origin as 8.36S 107.92E directly on the 7th Arc at 1:15:18 UTC, almost an hour after the expected impact time.”

Source: 370Location.org: A Strong Anomalous Acoustic Event on the Seventh Arc near Java

Tying It Together: What the Hydrophone Data Means for the Videos

If the videos fromPart 1 are real, they show MH370 being surrounded by orbs and disappearing in a flash of light. Such an event would generate multiple types of acoustic signatures:

1. The initial event: Whatever energy was released when the orbs activated would create a pressure wave
2. Aircraft impact/displacement: The sudden movement or destruction of a 200-ton aircraft would generate acoustic signals
3. Possible implosion: If parts of the aircraft sank to depth, implosion of pressurized compartments would create additional signals

The timeline fits uncomfortably well:

Theoretical Event	Time (UTC)	Supporting Evidence
"Teleportation" event at video coordinates	~01:00-01:30	Video timestamp, flight path calculations
Signal HA_32 at Diego Garcia	01:58	Detected at military bearing
Acoustic waves reach Diego Garcia	~02:30-03:30	Based on propagation calculations
Diego Garcia hydrophones shut down	03:07	25-minute gap begins
System restarts	03:32
Three signals at ~170° bearing	03:47-03:55	Captured immediately after restart

The data gap occurs exactly when acoustic evidence of the event would be arriving at Diego Garcia.

What Would Prove or Disprove This Theory?

Several pieces of evidence could definitively address the connection between the videos and the hydrophone data:

1. The Missing 25 Minutes

The CTBTO should release whatever diagnostic data exists from the HA08s station between 03:07 and 03:32 UTC. If the system was truly “shutdown” by a violent event, there should be evidence of what caused it.

2. Cocos Keeling Infrasound Data

If MH370 flew toward the video coordinates (near the Nicobar Islands), infrasound would have detected it. Release the data.

3. Full Diego Garcia Recordings

Not just the data that was deemed “too noisy,” but all recordings from 23:00 March 7 to 04:00 March 8, with proper signal filtering applied.

4. HA04 Crozet Islands Cross-Reference

A third station could triangulate any signals and provide much more precise location data. This analysis has apparently never been done.

5. Raw Satellite Footage

If the U.S. military was operating Gorgon Stare surveillance in the area (as the videos suggest), they have the original, uncompressed footage. Release it.

Conclusion: The Sound of Silence

The hydroacoustic evidence surrounding MH370's disappearance is characterized not by what was detected, but by what was silenced.

In Part 1, I laid out the evidence for and against the authenticity of the videos showing MH370 surrounded by orbs. I noted the extraordinary technical details, the suspicious “debunks” that seemed planted, and the connections to Diego Garcia.

Now we have another piece of the puzzle: 25 minutes of missing data from the hydrophone station closest to Diego Garcia, occurring exactly when acoustic evidence of a violent event would be expected to arrive.

Dr. Kadri's peer-reviewed research explicitly states that the simultaneous shutdown of all three hydrophones is “unlikely” to be a technical failure. He suggests a “violent nearby activity (including impact, explosion)” could cause such a shutdown.

The question is not whether the evidence exists. The question is why it has been systematically dismissed, classified, or erased.

If those videos are real, if MH370 was intercepted by some form of advanced technology, the hydrophone data gap is exactly what you would expect. Not evidence of what happened, but evidence of a cover-up.

Ten years after MH370 vanished, 239 families still have no answers. Perhaps those answers lie not in the depths of the southern Indian Ocean, but in the 25 minutes of silence from a hydrophone station in the shadow of a secret military base.

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Sources & Further Reading

Primary Scientific Sources

1. Kadri, U. (2019). Effect of sea-bottom elasticity on the propagation of acoustic-gravity waves from impacting objects. Scientific Reports, 9, 912.

   • DOI: 10.1038/s41598-018-37626-z
   • Direct link: https://www.nature.com/articles/s41598-018-37626-z

2. Kadri, U. (2024). Underwater acoustic analysis reveals unique pressure signals associated with aircraft crashes in the sea: revisiting MH370. Scientific Reports, 14, 10102.

   • DOI: 10.1038/s41598-024-60529-1
   • Direct link: https://www.nature.com/articles/s41598-024-60529-1

3. Stead, R.J. (2014). Seismic and hydroacoustic analysis relevant to MH370. Los Alamos National Laboratory, LA-UR-14-24972.

   • OSTI: https://www.osti.gov/biblio/1136454

4. Stead, R.J. (2014). How Common are Noise Sources on the Crash Arc. Los Alamos National Laboratory, LA-UR-14-28179.

   • OSTI: https://www.osti.gov/biblio/1160107

5. Butler, D. (2014). Sound clue in hunt for MH370. Nature, 510, 199-200.

   • Direct link: https://www.nature.com/articles/510199a

Independent Research

1. 370Location.org – Flight MH370 Acoustic Location
   • Main site: https://370location.org/
   • Javanomaly analysis: https://370location.org/2018/02/a-strong-anomalous-acoustic-event-on-the-seventh-arc-near-java/

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Read Part 1: Was Flight MH370 Teleported?

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In the fireside nights of us between Paid by our past as a winning matter Shawls in the wind at our better force Of full redemption in peaceful strength Of thoughts to our year and what it stood for We were high on simple things- like our good neighbour In this fortune of simple dreams another year Masts of ever-beating principal To our patches and newest day Asail on gifts of time to blackened water In Trinity we do rise under And so into as Christ’s became Following our inner patterns Of strength in love, and nights in view Ever peaceful without remorse That we love our hist’ry past Winning fields of summer friendship Through the tears of beloved gone But in this trial of thirst and wonder -it is seldom to our day It is common command our neighbours are our friends, And Europe light for us and keeping time

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