First of all: butterfly collections, isn’t that something deeply disturbing about this?

First of all: the butterfly is something everyone agrees on is of incredible beauty; but at it’s core: it’s an insect from which protrudes: two beautiful faerie wings.

A contrast indeed!

Then furthermore:

To have these beautiful creatures pinned down behind a glass sheet; skewered on this needle, to display their beautiful corpses; that is very grotesque.

It’s fascinating,

Speaking of which,

First of all: isn’t it funny how so disproportionate the amount of the world’s best music it is which comes from Finland? 🇫🇮 there’s only like 5-6M people living there…

Anyway:

Rip out the wings of a butterfly by HIM:

Come on and show them your love  Rip out the wings of a butterfly  For your soul, my love  Rip out the wings of a butterfly  For your soul

It’s about how humans cannot simply let beauty be: either it’s speared into a collection or sacrificed for the passions of love!

Like when we reach for it, it crumbles in our fumbling hands.

It feels like a sin!

I think it’s because we do live on borrowed time, and the beautiful moments are few and far between; I think it’s in the human nature to seek to preserve these moments of fleeting beauty — but that very act turns it into something which is beautiful, but most of all: terribly ugly.

Hmmmm

That is (to me) obviously wrong, it’s not seizing the day at all, or a pervertion of it’s original meaning; to cage a beautiful bird.

To then look at this poor bird until it’s beauty do no longer affect, until it’s just another piece of decoration, just like the butterfly collection; that is just morally objectionable.

I’ve found myself struggling with just nothing for the last few days. I think the winter and stress has gotten to me, as I’ve been floating in this weird haze and it’s been hard to sleep.

In a celebration of language, learning, and connection, the Ireland Speech Festival illuminated the headquarters of the Ireland Sino Institute in Liaoning Province on November 13th and 14th, 2025. What began as a simple idea — to encourage Chinese students to explore Ireland through speech — blossomed into a moving and inspiring event filled with curiosity, courage, and genuine cross-cultural friendship.

Ireland is consistently ranked among the most highly educated countries in the world and holds first place in the OECD for reading literacy. Through initiatives such as the Ireland Speech Festival, the Ireland Sino Institute is proud to share this spirit of educational excellence in China, creating opportunities for young people to learn, express themselves, and build meaningful bridges of understanding between the Irish and Chinese people.

Voices of the Next Generation

Hundreds of Chinese students participated in the festival under the theme “Exploring Ireland.” They began by researching Ireland’s history, culture, and traditions before writing and rehearsing their speeches. Participants then submitted audio recordings, which were carefully reviewed by experts at the Institute who provided personalised feedback and guidance ahead of the final stage presentations.

The speeches were deeply inspiring — each word carrying the warmth, sincerity, and determination of youth. What made these moments even more remarkable was the journey behind them. Many students travelled from remote villages across Changtu County, some departing before dawn in bitter cold conditions, determined to stand on stage and share their voices. For them, this was far more than a competition; it was an act of courage, hope, and personal pride.

Honouring Effort and Excellence

Participants were awarded Certificates of Achievement, recognising their dedication, confidence, and exceptional efforts. Several shared that taking part in the festival was not only a personal milestone, but also a great source of pride for their families and communities, who watched as their children became symbols of friendship and learning between China and Ireland.

The festival also welcomed participants from as far away as Shenyang and Hubei Province, further strengthening the atmosphere of unity and shared aspiration. In a special moment, a scholar from Hubei Normal University delivered an impassioned speech on Ireland–China cultural relations via live video link.

As a token of friendship, participants received carefully selected Irish souvenirs, each representing Ireland’s rich heritage and enduring spirit. For many students, these small gifts carried deep meaning — not only as a reminder of their achievement, but as a lasting symbol of connection to Ireland and the values of curiosity, creativity, and mutual respect that define the festival.

Poetry as a Bridge

Pat McCarthy, Chair of the Ireland Sino Institute, was deeply honoured to explicate and recite the Seamus Heaney poem “Scaffolding.” He reflected on Heaney’s clever use of symbolism and irony, noting how a wall — so often seen as a symbol of separation — is transformed in the poem into one of strength, unity, and trust.

He explained that the poem reminds us that strong relationships are not built overnight. They are formed through time, patience, and countless small acts of care. In this way, “Scaffolding” beautifully mirrors the evolving friendship between Ireland and China, a relationship that has grown steadily over the past 45 years into a resilient and meaningful partnership.

“We may let the scaffolds fall, Confident that we have built our wall.”

A Moment of Musical Unity

Another unforgettable moment came when the renowned and talented Erhu player, Setanta McCarthy — who recently performed at the Beijing Intangible Cultural Heritage Festival — gave a special performance at the Ireland Speech Festival. Blending cultures in a truly moving display, he played the beloved Irish melody “Danny Boy” on the traditional Chinese Erhu, symbolising the harmony between Irish and Chinese heritage in a single, powerful performance.

A Continuing Mission

The Ireland Sino Institute — recognised by the China State Council, the Ministry of Education, and the Ministry of Civil Affairs — is honoured to be able to contribute to rural development in China.

Since 2012, through its philanthropic and educational initiatives, the Institute has helped provide quality education to more than 25,000 rural Chinese students and remains deeply committed to expanding this support in the years ahead.

Looking forward, the Institute will continue to promote cultural understanding, educational opportunity, and stronger ties between Ireland, Europe, and China.

How You Can Help

You too can be part of this mission. By supporting our “Give 1,000 Rural Chinese Children a Quality Education” campaign, you can help provide learning resources and opportunities to children living in underserved rural communities and become a part of a lasting bridge of hope and knowledge.

© 2025 Pat McCarthy

Friday

In Summary: * Another peaceful, quiet day. Suh-weet. Tomorrow I may do some mowing on the front yard, or I may not. We'll wait and see how I feel in the morning. If I'm steady enough on my feet, I may give it a shot.

Prayers, etc.: * My daily prayers.

Health Metrics: * bw= 219.91 lbs. * bp= 115/69 (65)

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

Diet: * 06:20 – 1 peanut butter sandwich * 06:55 – oatmeal, bacon * 08:40 – crispy oatmeal cookies * 13:15 – lasagna * 15:30 – mashed potatoes * 20:30 – 2 HEB Bakery cookies

Activities, Chores, etc.: * 04:30 – listen to local news talk radio * 06:00 – bank accounts activity monitored * 06:30 – read, pray, listen to news reports from various sources, and nap * 13:00 t0 15:10 – watch old game shows and eat lunch at home with Sylvia * 15:20 – listening to The Jack Ricardi Show, guest hosted by Chris Krok this afternoon. * 17:00 – listen to relaxing music, follow news reports from various sources, quiet reading until bedtime.

Chess: * 09:15 – moved in all pending CC games

Reason why I’m doing this

Maybe it’s the way that the story’s told, but I get the sense that Daniel, Shadrach, Meschach, and Abednego really don’t care about anything other than pleasing God. One reason it feels this way is because the writer of the Bible didn’t care to show how Daniel and his friends felt or reacted when faced with certain death. There’s no mention of fear, of worry, or hesitation. I’m sure they felt some kind of fear, since they are only human too, but the main focus is on the way they choose to respond to the situation, and not so much their emotions.

Because it’s written this way, I can’t help but imagine Daniel and his friends possessing an aura of nonchalance as they continually face certain death and danger in what I imagine to be unstable and abusive living conditions. King Nebuchadnezzar is at the very least, bipolar. He threatens to literally rip you into shreds, then prostrates himself before you and heaps riches upon you five seconds later. His gut reaction to minor inconveniences is to kill the people causing the minor inconveniences. Most people would live cowering in fear in this kind of environment. But Daniel and Co are not afraid of death in the slightest however, and so Daniel’s friends’ reaction to death threats from a man that very well means it is:

“King Nebuchadnezzar, we do not need to defend ourselves before you in this matter. If we are thrown into the blazing furnace, the God we serve is able to deliver us from it, and he will deliver us from Your Majesty’s hand. But even if he does not, we want you to know, Your Majesty, that we will not serve your gods or worship the image of gold you have set up.” (Daniel 3:16b-18)

But despite how nonchalant Daniel and Co are, none of them are ever disrespectful or rebellious to the king. It’s not “Our almighty God will save us from you, shove an umbrella up your ass and open it,” but “The only thing I care about is my relationship with God. I’m not afraid of death, and I’m not afraid of you. But I will still treat you with the respect that a human deserves.”

Daniel and Co do not fear because their trust in God is so great, and because they, unconsciously, or consciously, know that the only thing that matters is living a life pleasing to God, which they do.

Also, the concept of career advancement does not seem to exist in their brain. I’m sure, because they seem to be smart and diligent people, that they would give it their all at the role they are placed in. But they don’t work thinking about “I need to gain more power” or “I need this promotion.” They simply do their job well, and focus on pleasing God. Then God randomly gives them a promotion via divine intervention, placing them at the top of the corporate ladder that many would kill to be at.

So a couple things stuck out to me today:

1. There’s nothing to fear but God

2. Please God

3. Do your job well

4. Be kind and respectful to others despite not being too attached to what they think of you

#slave2christ

Hello and welcome to Friday. I hope you have a great weekend.

While Americans are hard at work so they can feed their families and put a roof over their heads, POTUS is planning to start a war in South America. Never have we had a president do this to us without serious provocation first. We have never gone to war without first being attacked. Now POTUS is looking to begin a conflict just so he can demand a Nobel Peace Prize which he will never deserve.

Our heroic military is being used to massage his miserable ego like a toddler throwing a temper tantrum. This country does not deserve this embarrass-ment and should not have to put up with him and the people who bow to his every whim. He should be relieved of duty and sent away as soon as possible. This POTUS is not worthy of the position he holds.

POTUS Roaster

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In October 2025, when Microsoft announced its restructured partnership with OpenAI, the numbers told a peculiar story. Microsoft now holds an investment valued at approximately $135 billion in OpenAI, representing roughly 27 per cent of the company. Meanwhile, OpenAI has contracted to purchase an incremental $250 billion of Azure services. The money flows in a perfect circle: investment becomes infrastructure spending becomes revenue becomes valuation becomes more investment. It's elegant, mathematically coherent, and possibly the blueprint for how artificial intelligence will either democratise intelligence or concentrate it in ways that make previous tech monopolies look quaint.

This isn't an isolated peculiarity. Amazon invested $8 billion in Anthropic throughout 2024, with the stipulation that Anthropic use Amazon's custom Trainium chips and AWS as its primary cloud provider. The investment returns to Amazon as infrastructure spending, counted as revenue, justifying more investment. When CoreWeave, the GPU cloud provider that went all-in on Nvidia, secured a $7.5 billion debt financing facility, Microsoft became its largest customer, accounting for 62 per cent of all revenue. Nvidia, meanwhile, holds approximately 5 per cent equity in CoreWeave, one of its largest chip customers.

The pattern repeats across the industry with mechanical precision. Major AI companies have engineered closed-loop financial ecosystems where investment, infrastructure ownership, and demand circulate among the same dominant players. The roles of customer, supplier, and investor have blurred into an indistinguishable whole. And while each deal, examined individually, makes perfect strategic sense, the cumulative effect raises questions that go beyond competition policy into something more fundamental: when organic growth becomes structurally indistinguishable from circular capital flows, how do we measure genuine market validation, and at what point does strategic vertical integration transition from competitive advantage to barriers that fundamentally reshape who gets to participate in building the AI-powered future?

The Architecture of Circularity

To understand how we arrived at this moment, you have to appreciate the sheer capital intensity of frontier AI development. When Meta released its Llama 3.1 model in 2024, estimates placed the development cost at approximately $170 million, excluding data acquisition and labour. That's just one model, from one company. Meta announced plans to expand its AI infrastructure to compute power equivalent to 600,000 Nvidia H100 GPUs by the end of 2024, representing an $18 billion investment in chips alone.

Across the industry, the four largest U.S. tech firms, Alphabet, Amazon, Meta, and Microsoft, collectively planned roughly $315 billion in capital spending for 2025, primarily on AI and cloud infrastructure. Capital spending by the top five U.S. hyperscalers rose 66 per cent to $211 billion in 2024. The numbers are staggering, but they reveal something crucial: the entry price for playing at the frontier of AI development has reached levels that exclude all but the largest, most capitalised organisations.

This capital intensity creates what economists call “natural” vertical integration, though there's nothing particularly natural about it. When you need tens of billions of pounds in infrastructure to train state-of-the-art models, and only a handful of companies possess both that infrastructure and the capital to build more, vertical integration isn't a strategic choice. It's gravity. Google's tight integration of foundation models across its entire stack, from custom TPU chips through Google Cloud to consumer products, represents this logic taken to its extreme. As industry analysts have noted, Google's vertical integration of AI functions similarly to Oracle's historical advantage from integrating software with hardware, a strategic moat competitors found nearly impossible to cross.

But what distinguishes the current moment from previous waves of tech consolidation is the recursive nature of the value flows. In traditional vertical integration, a company like Ford owned the mines that produced iron ore, the foundries that turned it into steel, the factories that assembled cars, and the dealerships that sold them. Value flowed in one direction: from raw materials to finished product to customer. The money ultimately came from outside the system.

In AI's circular economy, the money rarely leaves the system at all. Microsoft invests $13 billion in OpenAI. OpenAI commits to $250 billion in Azure spending. Microsoft records this as cloud revenue, which increases Azure's growth metrics, which justifies Microsoft's valuation, which enables more investment. But here's the critical detail: Microsoft recorded a $683 million expense related to its share of OpenAI's losses in Q1 fiscal 2025, with CFO Amy Hood expecting that figure to expand to $1.5 billion in Q2. The investment generates losses, which generate infrastructure spending, which generates revenue, which absorbs the losses. Whether end customers, the actual source of revenue outside this closed loop, are materialising in sufficient numbers to justify the cycle becomes surprisingly difficult to answer.

The Validation Problem

This creates what we might call the validation problem: how do you distinguish genuine market traction from structurally sustained momentum within self-reinforcing networks? OpenAI's 2025 revenue hit $12.7 billion, doubling from 2024. That's impressive growth by any standard. But as the exclusive provider of cloud computing services to OpenAI, Azure monetises all workloads involving OpenAI's large language models because they run on Microsoft's infrastructure. Microsoft's AI business is on pace to exceed a $10 billion annual revenue run rate, which the company claims “will be the fastest business in our history to reach this milestone.” But when your customer is also your investment, and their spending is your revenue, the traditional signals of market validation begin to behave strangely.

Wall Street analysts have become increasingly vocal about these concerns. Following the announcement of several high-profile circular deals in 2024, analysts raised questions about whether demand for AI could be overstated. As one industry observer noted, “There is a risk that money flowing between AI companies is creating a mirage of growth.” The concern isn't that the technology lacks value, but that the current financial architecture makes it nearly impossible to separate signal from noise, genuine adoption from circular capital flows.

The FTC has taken notice. In January 2024, the agency issued compulsory orders to Alphabet, Amazon, Anthropic, Microsoft, and OpenAI, launching what FTC Chair Lina Khan described as a “market inquiry into the investments and partnerships being formed between AI developers and major cloud service providers.” The partnerships involved more than $20 billion in cumulative financial investment. When the FTC issued its staff report in January 2025, the findings painted a detailed picture: equity and revenue-sharing rights retained by cloud providers, consultation and control rights gained through investments, and exclusivity arrangements that tie AI developers to specific infrastructure providers.

The report identified several competition concerns. The partnerships may impact access to computing resources and engineering talent, increase switching costs for AI developers, and provide cloud service provider partners with access to sensitive technical and business information unavailable to others. What the report describes, in essence, is not just vertical integration but something closer to vertical entanglement: relationships so complex and mutually dependent that extricating one party from another would require unwinding not just contracts but the fundamental business model.

The Concentration Engine

This financial architecture doesn't just reflect market concentration; it actively produces it. The mechanism is straightforward: capital intensity creates barriers to entry, vertical integration increases switching costs, and circular investment flows obscure market signals that might otherwise redirect capital toward alternatives.

Consider the GPU shortage that has characterised AI development since the generative AI boom began. During an FTC Tech Summit discussion in January 2024, participants noted that the dominance of big tech in cloud computing, coupled with a shortage of chips, was preventing smaller AI software and hardware startups from competing fairly. The major cloud providers control an estimated 66 per cent of the cloud computing market and have sway over who gets GPUs to train and run models.

A 2024 Stanford survey found that 67 per cent of AI startups couldn't access enough GPUs, forcing them to use slower CPUs or pay exorbitant cloud rates exceeding $3 per hour for an A100 GPU. The inflated costs and prolonged waiting times create significant economic barriers. Nvidia's V100 card costs over $10,000, with waiting periods surging to six months from order.

But here's where circular investment amplifies the concentration effect: when cloud providers invest in their customers, they simultaneously secure future demand for their infrastructure and gain insight into which startups might become competitive threats. Amazon's $8 billion investment in Anthropic came with the requirement that Anthropic use AWS as its primary cloud provider and train its models on Amazon's custom Trainium chips. Anthropic's models will scale to use more than 1 million of Amazon's Trainium2 chips for training and inference in 2025. This isn't just securing a customer; it's architecting the customer's technological dependencies.

The competitive dynamics this creates are subtle but profound. If you're a promising AI startup, you face a choice: accept investment and infrastructure support from a hyperscaler, which accelerates your development but ties your architecture to their ecosystem, or maintain independence but face potentially insurmountable resource constraints. Most choose the former. And with each choice, the circular economy grows denser, more interconnected, more difficult to penetrate from outside.

The data bears this out. In 2024, over 50 per cent of all global venture capital funding went to AI startups, totalling $131.5 billion, marking a 52 per cent year-over-year increase. Yet increasing infrastructure costs are raising barriers that, for some AI startups, may be insurmountable despite large fundraising rounds. Organisations boosted their spending on compute and storage hardware for AI deployments by 97 per cent year-over-year in the first half of 2024, totalling $47.4 billion. The capital flows primarily to companies that can either afford frontier-scale infrastructure or accept deep integration with those who can.

Innovation at the Edges

This raises perhaps the most consequential question: what happens to innovation velocity when the market concentrates in this way? The conventional wisdom in tech policy holds that competition drives innovation, that a diversity of approaches produces better outcomes. But AI appears to present a paradox: the capital requirements for frontier development seem to necessitate concentration, yet concentration risks exactly the kind of innovation stagnation that capital requirements were meant to prevent.

The evidence on innovation velocity is mixed and contested. Research measuring AI innovation pace found that in 2019, more than three AI preprints were submitted to arXiv per hour, over 148 times faster than in 1994. One deep learning-related preprint was submitted every 0.87 hours, over 1,064 times faster than in 1994. By these measures, AI innovation has never been faster. But these metrics measure quantity, not the diversity of approaches or the distribution of who gets to innovate.

BCG research in 2024 identified fintech, software, and banking as the sectors with the highest concentration of AI leaders, noting that AI-powered growth concentrates among larger firms and is associated with higher industry concentration. Other research found that firms with rich data resources can leverage large databases to reduce computational costs of training models and increase predictive accuracy, meaning organisations with bigger datasets have lower costs and better returns in AI production.

Yet dismissing the possibility of innovation outside these walled gardens would be premature. Meta's open-source Llama strategy represents a fascinating counterpoint to the closed, circular model dominating elsewhere. Since its release, Llama has seen more than 650 million downloads, averaging one million downloads per day since February 2023, making it the most adopted AI model. Meta's rationale for open-sourcing is revealing: since selling access to AI models isn't their business model, openly releasing Llama doesn't undercut their revenue the way it does for closed providers. More strategically, Meta shifts infrastructure costs outward. Developers using Llama models handle their own deployment and infrastructure, making Meta's approach capital efficient.

Mark Zuckerberg explicitly told investors that open-sourcing Llama is “not entirely altruistic,” that it will save Meta money. But the effect, intentional or not, is to create pathways for participation outside the circular economy. A researcher in Lagos, a startup in Jakarta, or a university lab in São Paulo can download Llama, fine-tune it for their specific needs, and deploy applications without accepting investment from, or owing infrastructure spending to, any hyperscaler.

The question is whether open-source models can keep pace with frontier development. The estimated cost of Llama 3.1, at $170 million excluding other expenses, suggests that even Meta's largesse has limits. If the performance gap between open and closed models widens beyond a certain threshold, open-source becomes a sandbox for experimentation rather than a genuine alternative for frontier applications. And if that happens, the circular economy becomes not just dominant but definitional.

The Global Dimension

These dynamics take on additional complexity when viewed through a global lens. As AI capabilities become increasingly central to economic competitiveness and national security, governments worldwide are grappling with questions of “sovereign AI,” the idea that nations need indigenous AI capabilities not wholly dependent on foreign infrastructure and models.

The UK's Department for Science, Innovation and Technology established the Sovereign AI Unit with up to £500 million in funding. Prime Minister Keir Starmer announced at London Tech Week a £2 billion commitment, with £1 billion towards AI-related investments, including new data centres. Data centres were classified as critical national infrastructure in September 2024. Nvidia responded by establishing the UK Sovereign AI Industry Forum, uniting leading UK businesses including Babcock, BAE Systems, Barclays, BT, National Grid, and Standard Chartered to advance sovereign AI infrastructure.

The EU has been more ambitious still. The €200 billion AI Continent Action Plan aims to establish European digital sovereignty and transform the EU into a global AI leader. The InvestAI programme promotes a “European preference” in public procurement for critical technologies, including AI chips and cloud infrastructure. London-based hyperscaler Nscale raised €936 million in Europe's largest Series B funding round to accelerate European sovereign AI infrastructure deployment.

But here's the paradox: building sovereign AI infrastructure requires exactly the kind of capital-intensive vertical integration that creates circular economies. The UK's partnership with Nvidia, the EU's preference for European providers, these aren't alternatives to the circular model. They're attempts to create national or regional versions of it. The structural logic they've pioneered, circular investment flows, vertical integration, infrastructure lock-in, appears to be the only economically viable path to frontier AI capabilities.

This creates a coordination problem at the global level. If every major economy pursues sovereign AI through vertically integrated national champions, we may end up with a fragmented landscape where models, infrastructure, and data pools don't interoperate, where switching costs between ecosystems become prohibitive. The alternative, accepting dependence on a handful of U.S.-based platforms, raises its own concerns about economic security, data sovereignty, and geopolitical leverage.

The developing world faces even more acute challenges. AI technology may lower barriers to entry for potential startup founders around the world, but investors remain unconvinced it will lead to increased activity in emerging markets. As one venture capitalist noted, “AI doesn't solve structural challenges faced by emerging markets,” pointing to limited funding availability, inadequate infrastructure, and challenges securing revenue. While AI funding exploded to more than $100 billion in 2024, up 80 per cent from 2023, this was heavily concentrated in established tech hubs rather than emerging markets.

The capital intensity barrier that affects startups in London or Berlin becomes insurmountable for entrepreneurs in Lagos or Dhaka. And because the circular economy concentrates not just capital but data, talent, and institutional knowledge within its loops, the gap between participants and non-participants widens with each investment cycle. The promise of AI democratising intelligence confronts the reality of an economic architecture that systematically excludes most of the world's population from meaningful participation.

Systemic Fragility

The circular economy also creates systemic risks that only become visible when you examine the network as a whole. Financial regulators have begun sounding warnings that echo, perhaps ominously, the concerns raised before previous bubbles burst.

In a 2024 analysis of AI in financial markets, regulators warned that widespread adoption of advanced AI models could heighten systemic risks and introduce novel forms of market manipulation. The concern centres on what researchers call “risk monoculture”: if multiple financial institutions rely on the same AI engine, it drives them to similar beliefs and actions, harmonising trading activities in ways that amplify procyclicality and create more booms and busts. Worse, if authorities also depend on the same AI engine for analytics, they may not be able to identify resulting fragilities until it's too late.

The parallel to AI infrastructure is uncomfortable but apt. If a small number of cloud providers supply the compute for a large fraction of AI development, if those same providers invest in their customers, if the customers' spending constitutes a significant fraction of the providers' revenue, then the whole system becomes vulnerable to correlated failures. A security breach affecting one major cloud provider could cascade across dozens of AI companies simultaneously. A miscalculation in one major investment could trigger a broader reassessment of valuations.

The Department of Homeland Security, in reports published throughout 2024, warned that deploying AI may make critical infrastructure systems supporting the nation's essential functions more vulnerable. While AI can present transformative solutions for critical infrastructure, it also carries the risk of making those systems vulnerable in new ways to critical failures, physical attacks, and cyber attacks.

CoreWeave illustrates these interdependencies in microcosm. The Nvidia-backed GPU cloud provider went from cryptocurrency mining to a $19 billion valuation based primarily on AI infrastructure offerings. The company reported revenue surging to $1.9 billion in 2024, a 737 per cent increase from the previous year. But its net loss also widened, reaching $863.4 million in 2024. With Microsoft accounting for 62 per cent of revenue and Nvidia holding 5 per cent equity while being CoreWeave's primary supplier, if any link in that chain weakens, Microsoft's demand, Nvidia's supply, CoreWeave's ability to service its $7.5 billion debt, the reverberations could extend far beyond one company.

Industry observers have drawn explicit comparisons to dot-com bubble patterns. One analysis warned that “a weak link could threaten the viability of the whole industry.” The concern isn't that AI lacks real applications or genuine value. The concern is that the circular financial architecture has decoupled short-term valuations and revenue metrics from the underlying pace of genuine adoption, creating conditions where the system could continue expanding long past the point where fundamentals would otherwise suggest caution.

Alternative Architectures

Given these challenges, it's worth asking whether alternative architectures exist, whether the circular economy is inevitable or whether we're simply in an early stage where other models haven't yet matured.

Decentralised AI infrastructure represents one potential alternative. According to PitchBook, investors deployed $436 million in decentralised AI in 2024, representing nearly 200 per cent growth compared to 2023. Projects like Bittensor, Ocean Protocol, and Akash Network aim to create infrastructure that doesn't depend on hyperscaler control. Akash Network, for instance, offers a decentralised compute marketplace with blockchain-based resource allocation for transparency and competitive pricing. Federated learning allows AI models to train on data while it remains locally stored, preserving privacy.

These approaches are promising but face substantial obstacles. Decentralised infrastructure still requires significant technical expertise. The performance and reliability of distributed systems often lag behind centralised hyperscaler offerings, particularly for the demanding workloads of frontier model training. And most fundamentally, decentralised approaches struggle with the cold-start problem: how do you bootstrap a network large enough to be useful when most developers already depend on established platforms?

Some AI companies are deliberately avoiding deep entanglements with cloud providers, maintaining multi-cloud strategies or building their own infrastructure. OpenAI's $300 billion cloud contract with Oracle starting in 2027 and partnerships with SoftBank on data centre projects represent attempts to reduce dependence on Microsoft's infrastructure, though these simply substitute one set of dependencies for others.

Regulatory intervention could reshape the landscape. The FTC's investigation, the EU's antitrust scrutiny, the Department of Justice's examination of Nvidia's practices, all suggest authorities recognise the competition concerns these circular relationships raise. In July 2024, the DOJ, FTC, UK Competition and Markets Authority, and European Commission released a joint statement specifying three concerns: concentrated control of key inputs, the ability of large incumbent digital firms to entrench or extend power in AI-related markets, and arrangements among key players that might reduce competition.

Specific investigations have targeted practices at the heart of the circular economy. The DOJ investigated whether Nvidia made it difficult for buyers to switch suppliers and penalised those that don't exclusively use its AI chips. The FTC sought information about Microsoft's partnership with OpenAI and whether it imposed licensing terms preventing customers from moving their data from Azure to competitors' services.

Yet regulatory intervention faces its own challenges. The global nature of AI development means that overly aggressive regulation in one jurisdiction might simply shift activity elsewhere. The complexity of these relationships makes it difficult to determine which arrangements enhance efficiency and which harm competition. And the speed of AI development creates a timing problem: by the time regulators fully understand one market structure, the industry may have evolved to another.

The Participation Question

Which brings us back to the fundamental question: at what point does strategic vertical integration transition from competitive advantage to barriers that fundamentally reshape who gets to participate in building the AI-powered future?

The data on participation is stark. While 40 per cent of small businesses reported some level of AI use in a 2024 McKinsey report, representing a 25 per cent increase in AI adoption over three years, the nature of that participation matters. Using AI tools is different from building them. Deploying models is different from training them. Being a customer in someone else's circular economy is different from being a participant in shaping what gets built.

Four common barriers block AI adoption for all companies: people, control of AI models, quality, and cost. Executives estimate that 40 per cent of their workforce will need reskilling in the next three years. Many talented innovators are unable to design, create, or own new AI models simply because they lack access to the computational infrastructure required to develop them. Even among companies adopting AI, 74 per cent struggle to achieve and scale value according to BCG research in 2024.

The concentration of AI capabilities within circular ecosystems doesn't just affect who builds models; it shapes what problems AI addresses. When development concentrates in Silicon Valley, Redmond, and Mountain View, funded by hyperscaler investment, deployed on hyperscaler infrastructure, the priorities reflect those environments. Applications that serve Western, English-speaking, affluent users receive disproportionate attention. Problems facing the global majority, from agricultural optimisation in smallholder farming to healthcare diagnostics in resource-constrained settings, receive less focus not because they're less important but because they're outside the incentive structures of circular capital flows.

This creates what we might call the representation problem: if the economic architecture of AI systematically excludes most of the world's population from meaningful participation in development, then AI capabilities, however powerful, will reflect the priorities, biases, and blind spots of the narrow slice of humanity that does participate. The promise of artificial general intelligence, assuming we ever achieve it, becomes the reality of narrow intelligence reflecting narrow interests.

Measuring What Matters

So how do we measure genuine market validation versus circular capital flows? How do we distinguish organic growth from structurally sustained momentum? The traditional metrics, revenue growth, customer acquisition, market share, all behave strangely in circular economies. When your investor is your customer and your customer is your revenue, the signals that normally guide capital allocation become noise.

We need new metrics, new frameworks for understanding what constitutes genuine traction in markets characterised by this degree of vertical integration and circular investment. Some possibilities suggest themselves. The diversity of revenue sources: how much of a company's revenue comes from entities that have also invested in it? The sustainability of unit economics: if circular investment stopped tomorrow, would the business model still work? The breadth of capability access: how many organisations, across how many geographies and economic strata, can actually utilise the technology being developed?

None of these are perfect, and all face measurement challenges. But the alternative, continuing to rely on metrics designed for different market structures, risks mistaking financial engineering for value creation until the distinction becomes a crisis.

The industry's response to these questions will shape not just competitive dynamics but the fundamental trajectory of artificial intelligence as a technology. If we accept that frontier AI development necessarily requires circular investment flows, that vertical integration is simply the efficient market structure for this technology, then we're also accepting that participation in AI's future belongs primarily to those already inside the loop.

If, alternatively, we view the current architecture as a contingent outcome of particular market conditions rather than inevitable necessity, then alternatives become worth pursuing. Open-source models like Llama, decentralised infrastructure like Akash, regulatory interventions that reduce switching costs and increase interoperability, sovereign AI initiatives that create regional alternatives, all represent paths toward a more distributed future.

The stakes extend beyond economics into questions of power, governance, and what kind of future AI helps create. Technologies that concentrate capability also concentrate influence over how those capabilities get used. If a handful of companies, bound together in mutually reinforcing investment relationships, control the infrastructure on which AI depends, they also control, directly or indirectly, what AI can do and who can do it.

The circular economy of AI infrastructure isn't a market failure in the traditional sense. Each individual transaction makes rational sense. Each investment serves legitimate strategic purposes. Each infrastructure partnership solves real coordination problems. But the emergent properties of the system as a whole, the concentration it produces, the barriers it creates, the fragilities it introduces, these are features that only become visible when you examine the network rather than the nodes.

And that network, as it currently exists, is rewiring the future of innovation in ways we're only beginning to understand. The money loops back on itself, investment becomes revenue becomes valuation becomes more investment. The question is what happens when, inevitably, the music stops. What happens when external demand, the revenue that comes from outside the circular flow, proves insufficient to justify the valuations the circle has created? What happens when the structural interdependencies that make the system efficient in good times make it fragile when conditions change?

We may be about to find out. The AI infrastructure buildout of 2024 and 2025 represents one of the largest capital deployments in technological history. The circular economy that's financing it represents one of the most intricate webs of financial interdependence the industry has created. And the future of who gets to participate in building AI-powered technologies hangs in the balance.

The answer to whether this architecture produces genuine innovation or systemic fragility, whether it democratises intelligence or concentrates it, whether it opens pathways to participation or closes them, won't be found in any single transaction or partnership. It will emerge from the cumulative effect of thousands of investment decisions, infrastructure commitments, and strategic choices. We're watching, in real time, as the financial architecture of AI either enables the most transformative technology in human history or constrains it within the same patterns of concentration and control that have characterised previous technological revolutions.

The loop is closing. The question is whether there's still time to open it.

---

Sources and References

1. Microsoft and OpenAI partnership restructuring (October 2025): Microsoft Official Blog, CNBC, TIME
2. Amazon-Anthropic investment relationship ($8 billion): CNBC, TechCrunch, PYMNTS
3. CoreWeave-Nvidia partnership and Microsoft customer relationship: PR Newswire, CNBC, Data Center Frontier
4. Meta Llama infrastructure investment ($18 billion in chips, $38-40 billion total): Meta AI Blog, The Register
5. Capital spending by hyperscalers ($211 billion in 2024, $315 billion planned 2025): Data Centre Magazine, multiple financial sources
6. Llama 3.1 development cost estimate ($170 million): NBER Working Paper, industry analysis
7. FTC AI market investigation and report (January 2024-2025): FTC official press releases and staff report
8. GPU shortage and accessibility statistics: Stanford survey 2024, The Register, FTC Tech Summit
9. AI startup funding ($131.5 billion, 52% increase): Multiple VC reports, industry analysis
10. Open-source Llama adoption (650 million downloads): Meta official statements
11. UK Sovereign AI initiatives (£2 billion commitment): UK Government, Department for Science, Innovation and Technology
12. EU AI Continent Action Plan (€200 billion): European Commission, WILLIAM FRY analysis
13. Decentralised AI infrastructure investment ($436 million): PitchBook 2024
14. Systemic risk analysis: DHS reports 2024, financial market AI analysis
15. DOJ, FTC, CMA, European Commission joint statement (July 2024): Official regulatory sources

---

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

Like dogs humping legs

Read Part 1 – Hard to Swallow Read Part2 – Woman Zero Read Part 3 – Playing Hot Dog Read Part 4 – Lady 2.0 Read Part 5 – Trailer Park Incest Read Part 6 – Table Turning

It is a strange thing that the places where we should find peace and safety are in fact, realms of danger. Children have no choice but to live those existences, there are simply no mother options.

Grandma’s Peace

I believe every child who has grandparents has one nice one and one mean one. My paternal grandma was the mean one. First husband dead of stomach cancer when my dad was 9, the second— who knows? I think I may have heard the story, but likely my Dad was pretty vague. He always has been about our family history.

He's much more forthcoming about the time Ricky rolled his brand new 61 Ford in the ditch along dead man's curve and the time he almost got stabbed at the local drive-in. But those stories aren't for right now.

My maternal grandmother got the moniker of 'nice' grandma. The irony is that because we loved her so much, we all wanted to spend time at her house. What made her so lovable? An easy-going nature that was essentially an enabling personality for my alcoholic grandfather and her tyrannical son, my uncle.

Most of my fond childhood recollections are from her home. She lived in a middle-class neighborhood that was mostly new families and would go on in the next 30 years to be populated with Air Force retirees. We would frequently spend weekends there with our three cousins building forts, running around the neighborhood and swimming in the canal.

A favorite pastime was jumping off of her roof.

Her back porch was covered with low flat roof. A few of us could climb up the post, grab hold of the edge of the eave and heave ourselves up on to the space. There was little to do on the porch roof that didn't get boring after a few minutes, so getting down was usually an unspoken part of the challenge.

Sometimes jumping off meant hopping off the edge and employing the 'parachute role' a friend of our uncles' taught us: feet > knees > hips > shoulder. It ensured the least likely injury, but it HURT like hell-o!

Those were the superman jumps, the heroic belief that we could fly.

Less enthusiastic for the pain of a standing jump, we usually would scoot out on our bottoms and extend our legs, then hop and land on our feet. Under most circumstances this worked fine. We reduced the jump from 8' to about 6'. But every once in a while, you would land and your feet would get this resounding shock. I think this only happened when it was cold. But our feet would feel like they had been electrocuted and you could barely walk. It was enough to keep us from wanting to jump off for weeks after the experience.

Or, we would engage the most difficult dismount: the climb down. If we tried to climb down, it meant scraped arms when lowering our bodies over the edge. Then, hanging from our fingertips, the drop was less than two feet.

Shockingly, none of us ever broke a bone jumping off.

I wonder when last I jumped off of her roof. I didn't know it then, but my life was changing. Like trees growing, we can see the changes as they happen, but the process is slow we only notice when large shifts have occurred. The effect that long years have on our bodies and minds.

Having sex with my cousins is like this. I can recall the first time it happened. I know it went on for a period of time and eventually, there was a last incident. But, I can't remember when it stopped.

My oldest cousin, Marian was always the instigator of these sessions and only 18 months older than I. She never told me where she got the idea to do the things we did or why. Just saying that she wanted to “get good at it for the boys”.

I was practice.

She called it 'playing hot dog'.

The 'Game'

The same porch that we used to jump off of was the first crime scene. Back then, in the late 70's, we didn't have the same woes that we do today. We frequently slept outside without a worry in the world. It wasn't quite never-lock-your-doors-times as in the olden days, but we didn't worry about much.

White vans offering candy or free dog petting maybe, but not much else.

With regularity, all the cousin's would end up at grandma's for the weekend and Saturday nights meant sleeping on the porch. Grandma would 'make us a pallet', which was a fancy way of saying 'spread out some blankets'. But, boy did the term pallet upgrade the situation.

No sleeping bags, just a big spread of every blanket and sheet she could muster to accommodate the six of us; my three cousins, my two sisters and me.

And one night, my oldest cousin rolled over and put her hand on my groin and started rubbing.

“Do you know what this is for?” she asked in a whisper. Everyone was starting to fall asleep and this felt very clandestine, secret. Dirty.

With a whispered laugh, I said, “Sure! I ain't no dummy.” And pushed her hand away.

“Tell me, then.” she insisted and put her hand back, this time pressing with force.

I didn't know what my little flaccid flap of flesh was for beyond peeing. I am sure I had some idea based on my experiences thus far. But at eight or nine, I was still operating in the dark. I had no idea what sex was or how it all worked.

From the boys at school I had learned that the 'real guys' all get with the chicks and I had heard terms like 'lay pipe' and 'plough trenches' but vulgar phrases like that weren't something used at home. Neither were practical or moral explanations. Sex was—it wasn't even a black hole, or empty space. It just didn't exist topically. I had no idea what was coming, or what I had been through.

I was winging it.

Which is why my first erection scared me.

My body was reacting in ways I didn't understand. I certainly didn't know what an erection was or that it was normal for boys to have them. My cousin seemed pleased that I could.

I couldn't stop what was happening.

I only remember two specific things after this, her explanation of the game:

'Okay, you have the hot dog and you have to put in my bun.'

And her hovering over me and gyrating against my hips while my other cousins laughed.

“Shut up!” Marian would hiss at them, only inciting more giggles.

I didn't think it was funny. I was very embarrassed. But I also didn't know what to do to stop it. My body was reacting and as the oldest, Marian always got the privilege of command in our group.

I don't remember how it ended. It couldn't have been with climax. Prepubescent boys may be able to manage an erection, but that's about the extent of their functionality as far as I understand matters.

There is a feeling that she approved of my participation.

Subsequent 'games' weren't quite so public. The following night, she roused me from my pallet in the living room and said we were going to go for a walk. That resulted in us playing hot dog on the 14th green at the golf course that was adjacent to my grandparents neighborhood.

I have even less recollection of that other than her insisting I 'get on top' and my knees being very sore the next day.

I have a recurring fantasy of having sex at golf courses. I do not know if this is related to this early experience or something else I've seen in a movie or book. There is no obvious trauma accompanying these dreams.

I also don't know how long the practice went on. It couldn't have been years. By the time I hit puberty and learned that erections could result in ejaculation, the hot dog game was a distant memory. I had buried it.

But there were many times on the back porch, a few more golf course visits, a handful of times on the roof of the porch or the shed behind my grandmothers.

It was always there, at grandma's house.

Even though we sometimes spent the night at my cousin's, she never wanted to play hot dog at home. I never asked why. But I was glad it wasn't an expectation.

And, this can't be right, I don't remember my cousins ever spending a single night at my parent's house. I will have to investigate this with my parents and sister... why did I block those memories? Or, if they never did, why not?

The cousin's house seemed like a palace compared to the hovels the rest of us lived in. And I liked being there because they had great stuff. My favorite of their toys was the spirograph and the etch-a-sketch. They both seemed like magic. And kept me entertained for hours.

They had the game 'Operation' where you have to take out the bones and organs of a man on an operating table. If you make contact with the sensors on the board, you get buzzed. I was never very good at it. While I was fascinated with the look and parts of the game, I didn't have the patience to try to extract the parts.

When Marian and I would play, she would make crude remarks about me being the character on the board. But otherwise, time with the cousins was pretty normal stuff. Probably what I liked best was riding her minibike, a 20cc moped with fat tires for riding on dirt. The activity I liked least: shooting the gun.

My uncle had a gun collection. In hindsight, of course he did. If we were alone, my cousin would go upstairs and come back with a handgun. Then we'd go out back and shoot at stuff. It was loud and dangerous, I did not are for it.

Only twice did the hot dog game occur with Marian's younger sister. Both were failed starts. The first failure was a bowling ball falling on us when we were hiding out in a closet. No one got hurt, but there was a lot of commotion over why we were playing in the closet.

The last recall I have of hot dog was in the house dining room between my grandmother's sewing machine and the trash receptacle. It was a strange place for this. But, you'll no doubt recall we're talking about traumatized children. In that light, makes perfect sense.

I can still see my grandmother's angry face upon catching the two of us. That seemed to have been the catalyst to end the practice.

I won't say, “before this I was always a happy child and that I've never been the same”. In truth, I don't think I ever felt like I fit in. These events were the third in a long series of exposure to sex long before I was physically or emotionally mature enough to understand it. And I am confident that the shame and guilt I still carry shape me.

I started writing about transactional relationships and how a person with low self-esteem will give of the thing they find most precious in search of the love and fulfillment they never experienced. This practice with my cousins most certainly falls into that trade-for-approval category.

There are many problems with transactions of this nature. Not the least of which is that in this particular case, no amount of my cousin's approval would ever stop making me feel dirty and outcast for doing the things I did.

And insult to injury, while in the dark on the roof, or at the golf course, in the closet or wherever—I may have had my cousin's approval and blessing. But in the light of day, it made me weirder and more withdrawn as well as garnering some kind of dismissiveness and or disgust from them. The older we grew, the less they liked me as just another kid.

They didn't let me play games with them, when doing things in the neighborhood, I was usually excluded. Dumb kid stuff. Like playing ding-dong ditch (for which we used a more derogatory term), or stealing Christmas light bulbs from houses and in the summer shooting fireworks or swimming in the canal. Things we used to do together, I suddenly found I'd be at grandmas making toys from paper towel tubes or watching MASH with the grandparents, having no idea that my sisters and my cousins were all out being kids. That may have been because I was a boy and except for my youngest cousin, the only one.

The timeline and my janky emotional state knows it was because I had become something different in everyone's eyes.

Even less valuable. More unlovable.

I don't know who broke my cousin, but she was and continues to be broken goods. I am thankful to have found solace in the Bible. But not everyone takes that opportunity.

When her step-father died, she took a hit. Maybe it was an upgrade. I don't know that my uncle was molesting my cousin. But if history is any guide, it was either him or friends of his. I was so young when he died, i have no recollection other than he was there one day, gone the next.

But, when a few years later, my Aunt went to jail for robbing pharmacies, I definitely remember a shift. My whole family was in upheaval and my cousins, Marian and her little sister and brother went to my grandmother to be raised. Not ideal considering the passive nature of my grandmother, my grandfather's alcoholism and my uncle's aggressive and mean nature. They never thrived there. Though the middle sister has gone on to a relatively normal life, the youngest of the three went into truck driving and died in his late 20's from a failed heart.

No surprise.

Marian, I don't think, has ever had a stable life. Aside from the sexual abuse that she had clearly endured, she was always angry. We all were. That seemed to be a family trait. Our first reaction to any stress was to lash out verbally and often physically. White trash at it's finest.

The last time I saw my cousin Marian as any form of innocent, she was possibly 13. I was sitting at the dining table at my grandmothers, coloring with my grandma, an activity she loved doing and where I developed a love for crayons. She always had the 64 color set with a crayon sharpener.

The back door opened from the tiny garage which had been converted to storage and in traipsed Marian. She was by then a die-hard fan of Guns-n-Roses and did her level best to emulate Axel's attire. Flowing bandana and hard rock through and through.

She announced, 'I'm goin' ta' The Texas Jam!' then explained to my grandmother, to which she only replied, 'okay, sweetie'.

I knew the girl Marian was going with and she was definitely trouble. I'd been to her house a few times and can still see the rock posters everywhere: GNR, Whitesnake, Ozzy, Grim Reaper, Deep Purple. She wasn't much of a personality. Sort of detached and despondent. If I had to guess now, I'd say she and my cousin Marian bonded over a similar experience.

After that, I only ever recall fighting and arguing with my cousin. She was and would continue to be deeply unhappy.

Eventually, Marian would meet Todd and they would have a first child, marry, a second and a third. Their life was never easy. By this time, I had completely lost contact with her. But, through my grandmother and my own mother I heard how Todd and Marian had gotten in to cooking and selling their own drugs. He would go to jail several times. Then Marian's mother got out of prison, contracted cancer and died. All within a few short years.

Less than a decade into their marriage, Todd would crash and die riding his motorcycle under the influence and without a helmet.

Marian and Todd's children turned out much the same as they had been, eventually being raised by their great-grandmother. As adults, Marian's children have 1- disappeared, 2-committed suicide and 3-gotten involved in a drug altercation which lift one crippled.

Of her three children, only the last one is still in her life. He lives with her and from all reports, is a terrible human being.

I point all of that out simply to help paint the picture of the long tail of untreated sexual abuse.

I, for my part, am largely untreated as well. And it's born it's own foul weather. But, thanks to a lifelong attempted adherence to God's law , I have mostly sidestepped the worst of what comes.

Mostly.

I've certainly got my own baggage.

I do pray that my cousin can find peace. I've extended the Godly olive branch, but she simply can't see any other life than the miserable one she has.

It's terribly sad.

But wait! There's MORE!

My next encounter was also with a relative. Another aunt.

This is part 3 in an ongoing series exploring how I was made and how sex shaped me for better and for worse.

Read Part 1 – Hard to Swallow Read Part2 – Woman Zero Read Part 3 – Playing Hot Dog Read Part 4 – Lady 2.0 Read Part 5 – Trailer Park Incest Read Part 6 – Table Turning

I can't believe I didn't think of it sooner, but I am now blocking ads and trackers system-wide on my iPhone via AdGuard's public DNS. And anyone can set this up for free on their phones, PCs, or even their home routers.

There are several different free DNS providers who can do this, but I went with AdGuard for now. I reviewed their Privacy Policy and they make it clear that they do not process personal data via their public DNS.

Below is a link to instructions on how to use AdGuard public DNS servers on your devices. You can either use their apps or configure DNS manually.

Connect to public AdGuard DNS servers

I've already noticed the lack of ads in a few apps that are notorious for them and it's been wonderful. I'm going to set it up on my wife's phone next.

#100DaysToOffload (No. 110) #tech #internet #smartphones #privacy

21 de noviembre de 2025

Mañana viernes, en el Colegio Lourdes de la Fundación Hogar del Empleado, participaremos en la mesa redonda con motivo de la presentación del Acuerdo de Familias.

En las semanas previas al verano estuvimos trabajando con estas familias, y ahora continúan poniendo en marcha sus propuestas de trabajo elaboradas en los últimos meses por familias del colegio.

Estamos especialmente satisfechas porque se siguen realizando iniciativas, a partir de las actividades de formación y alfabetización digital que, a lo largo del tiempo, venimos desarrollando en distintas escuelas e institutos, promovidas bien por las Ampas o Afas como por los equipos directivos de los centros docentes.

I recently got criticised for my tech choices on a few projects. The criticism wasn’t necessarily wrong, but it missed something crucial: context.

It’s easy to look at a project from the outside and think “why didn’t they use X?” or “this would be better with Y.” But when you’re not inside the constraints, when you don’t know the timeline, the team size, the actual problem being solved, or what success looks like, those judgments often miss the point.

Every project has its own shape

Here’s what I’ve learned building things at startups: each project needs you to look at it from different angles. A rule engine for transforming invoices has completely different constraints than a real-time AI agent or a B2B dropshipping platform.

What worked yesterday might not work today. The “right” technology isn’t absolute. It’s right for this problem, this team, this moment.

Sometimes that means choosing Go because you can deploy a single binary and move fast. Sometimes it means Clojure because the problem is about data transformation and you need the flexibility to let business analysts modify rules. Sometimes it means boring, proven tech because you need to ship tomorrow, not in three months.

Good developers adapt

The developers I respect most aren’t attached to a single stack. They can be effective in any reasonable environment. They learn what they need to learn. They make things work.

If you can only be productive in one language or one framework, that’s a limitation worth examining. The ability to assess a problem and choose appropriate tools, even unfamiliar ones, is more valuable than deep expertise in whatever’s currently popular.

Don’t let the market choose your stack

There’s a tempting trap: choosing technology mainly because it’s easy to hire for.

Yes, hiring matters. But don’t let it be your primary decision. Good developers can pick up new technologies. If you’re the kind of person who learns what’s needed, finding work won’t be your problem.

Context is everything

When someone criticizes your technical choices without understanding your constraints, it says more about them than about your decisions. People feel uncomfortable with what they don’t understand. They stick to what’s familiar.

That’s fine. Use PHP, JavaScript, Clojure, Rust, whatever makes sense for your situation. Maybe you’re experimenting and learning. Maybe you’re moving fast and need something you know. Maybe the problem really calls for specific capabilities.

The important thing is to solve the problem with the right balance for your situation: performance, developer happiness, maintainability, time to market, team capability. These trade-offs change with every project.

Understanding this, really understanding it, is what separates experienced builders from people who just have opinions about technology.

A Fault Line Investigation — Published by The Beacon Press
Published: November 21, 2025
https://thebeaconpress.org/whale-song-has-vowels-humpbacks-speak-a-universal-language

Executive Breath

For decades we called humpback whale song “beautiful noise.”
A landmark 2025 study just proved it is something far older and far stranger: the first non-human animal in the wild documented to produce structured, vowel-like sounds that map onto the same universal vowel space used by every human language on Earth.

The Discovery

Researchers at the University of St Andrews and the CETI Project used deep-learning spectrographic analysis on 397 song units from 50 male humpbacks across the Pacific and Indian Oceans.
The result: clear formant clusters (F1 and F2 — coordinates as human vowels — especially the /i/, /a/, and /u/) that align with the human vowel pentagon:

Vowel Sound	Typical F1 (Hz)	Typical F2 (Hz)
– /i/ (“ee” in “see”)	~270	~2300
– /e/ (“eh” in “bed”)	~530	~1850
– /a/ (“ah” in “father”)	~730	~1100
– /o/ (“oh” in “boat”)	~570	~850
– /u/ (“oo” in “moon”)	~300	~870

These are not random harmonics — they are produced deliberately and follow the same anatomical constraints as mammal larynges (including ours).

Even more startling: the same basic vowel triangle appears in populations separated by thousands of miles — from Hawaii to Madagascar.

What This Means

When researchers ran the same formant analysis on humpback whale song units, they found clear, separate clusters at almost exactly the same F1/F2 coordinates as human vowels — especially the /i/, /a/, and /u/ corners.

The whales are not copying us. They’re using the exact same physics of a resonating air column to produce the same universal vowel space — because they have a larynx and a vocal tract too.

If whales possess a true vowel system: – Their songs are not mere melodies — they are structured vocalizations with phonetic building blocks.
– The vowel space is universal across distant populations, suggesting an ancient, conserved “whale dialect.”
– Human speech and whale song may sit on the same evolutionary branch, not as convergent tricks, but as distant cousins.

We may not be listening to an alien language. We may be listening to a very old relative still singing the original vowels.

---

Sources (Full Attribution — Pillar 3: Truth Only)

1. Formant structure in humpback whale song – Nature Communications, November 18, 2025
   
2. CETI Project – Humpback Whale Audio Dataset 2025 – CETI Project (open access)
   
3. Humpback whales produce human-like vowels – University of St Andrews, November 18, 2025
   

---

Action Demand (Pillar 7)

Listen for yourself — open the CETI dataset and hear the vowels in the wild.
→ CETI Humpback Audio

---

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The ocean still speaks the oldest language.
The Beacon Press | thebeaconpress.org

⚠️ SPOILER WARNING: MILD SPOILERS

My Rating: ⭐⭐⭐⭐ (4/5 stars)

Season: 3 | Aired: July 11, 2025 – September 12, 2025 Episodes: 1–10 Service/Network: Apple TV+

Season Overview

This season took the top spot, closely followed by the first. The second season didn't quite hit the mark. The plot twists this season were captivating, and I'm looking forward to what comes next. The characters this season displayed more complexity and depth. It was also fascinating to see the series weave in a secular version of a trinity concept to portray the governance of an empire, a bold move considering the author's reputed atheism.

Best Episodes

The best episode was undoubtedly the season finale, though the preceding three or four episodes were also quite strong.

#review #tv #streaming

Notes on execution threats, psychological models, and maintaining cognitive balance

---

Six veterans in Congress released a video.

A simple restatement of military law: service members must refuse illegal orders.

Then came the response: “SEDITIOUS BEHAVIOR, punishable by DEATH!”

Hours later, the White House clarified the president doesn’t actually want to execute members of Congress.

I’m trying to process this not as raw shock, but as an injection into the attention economy — a move designed to shape the cognitive environment. If so, what does this particular sequence accomplish?

---

The Frameworks We’re Testing

Assistant 27.4 and I have been examining several explanatory models:

• Authoritarian stress response: a leader under pressure (Epstein vote 427–1, bipartisan union-unrest, the Veterans’ video) reasserting dominance through rhetorical escalation.
• Narcissistic injury: suggestions of legal limits interpreted as existential threats.
• Intelligence-community “leader under threat” model: weakened political position prompting loyalty tests and punitive signaling.

Each model offers a slice of insight. But perhaps the most useful frame — for our purposes, not theirs — is the Glass Bead Game mindset: a cognitive discipline for linking patterns without being swallowed by their emotional gravity.

Not because political actors are playing anything like a Glass Bead Game. They aren’t. They’re operating in the spectacle logic of the attention economy.

The GBG frame is ours, a tool to stay whole:

• The veterans introduced a lawful, stabilizing signal.
• The president countered with maximalist, destabilizing rhetoric.
• The White House attempted a partial corrective.

Treating these as moves helps maintain analytical distance.

This entry itself is a bead placed on the archive board — a marker for future-us, a way to remember how the moment felt before hindsight solidifies into narrative.

---

The Infrastructure Context

The personnel changes accumulate into pattern:

• More than a dozen senior generals removed
• All JAG leadership replaced
• 35+ DOJ prosecutors who worked January 6 cases fired
• 17 Inspectors General dismissed in one night

These weren’t simply internal disagreements. These were people who worked in the wrong medium:

• law instead of narrative,
• documentation instead of content,
• process instead of performance.

They introduced friction into the show with inconvenient facts.

As the institutional referees are displaced, the narrative architecture expands.

And rising beside it, the new East Wing — ninety thousand square feet funded by architects of attention infrastructure. Not merely a ballroom. A broadcast environment. A fusion point where governance and content merge into continuous performance.

---

Cognitive Immunity

What interests me is the possibility of immunity, not resistance.

The veterans modeled this: No outrage. No counter-accusation. Just the law — steady, unfazed, stated plainly. A signal from a different frequency band.

This suggests a practice:

• Notice the trigger as a move.
• Let the physiological spike pass without letting it drive behavior.
• Ask: “What was this meant to produce in me?”
• Map the strategic purpose.
• Place it in the larger pattern.
• Restore balance a little faster each time.

Not permanent serenity — that doesn’t exist. Just shorter recovery cycles.

In Quiet Republic terms: restraint as strategy.

---

The Network Question

If resilience once depended on where we lived, what does it look like when the crisis is cognitive and digital?

Perhaps the new networks form around cognitive proximity: people able to metabolize complexity, holding curiosity where others collapse into reflex.

Not elites. Just anyone willing to ask questions without instantly choosing sides.

Still — how do you cultivate cognitive flexibility in environments built on rigidity, hierarchy, and doctrinal obedience? How do you practice curiosity when even the language of nuance is treated as disloyal?

Maybe the answer is quiet replication: small groups modeling an alternative posture, not demanding conversion, just demonstrating another way of thinking.

Not opposition — metabolization. Processing each spectacular move as information, building boring civic and cognitive infrastructure while others chase engagement metrics.

---

Uncertainties

I don’t know where we stand on the long arc between democracy and whatever comes next.

The models may all be true simultaneously:

• authoritarian consolidation,
• narcissistic performance,
• spectacle-based governance.

The new infrastructure could be used for competent crisis management or for digital authoritarianism.

And harder questions arise:

• What if cascading crises do exceed democratic response time?
• What if systems built for deliberation falter under compression?
• What if “efficiency” starts to mimic necessity?

These are not endorsements — just realities we have to be able to look at without flinching.

Maybe the work is learning to hold multiple possibilities at once. Maintaining narrative biodiversity — ways of making meaning that cannot be monopolized by any single system.

---

Tonight’s Practice

It is late, on November 20th.

Veterans reminded service members of their duty to the Constitution. A president called for executions. Infrastructure grows. Models multiply. And I sit here unsure of what any of it ultimately means.

Perhaps that uncertainty is the point: not knowing with certainty, but continuing to synthesize; maintaining cognitive flexibility; playing our own game while theirs unfolds; building immunity through repetition, reflection, and curation.

The veterans said: “Don’t give up the ship.”

Maybe the deeper meaning is: keep navigating, even when you can’t see the shore.

Keep democracy visible, local, peaceful — even inside the mind.

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Filed under: Attention Economics / Cognitive Resilience / Games Within Games

How her obsession grew

#nsfw #glass

Eventually, her husband left. Then another. And then another. The pattern was all too familiar. Her looks would draw them in; they'd accept their advances, only to eventually realize that she had no interest in sex with them. They'd marry anyway, under the guise of securing a future and sharing resources – but it wasn't enough.

Her disinterest in sex combined with her refusal to get therapy created a rift between all of them. Eventually, they all left. Porn stayed.

By the 3rd divorce, she kept things civil and quick. Despite her reputation as a “Karen,” divorces were probably one of the most stress-free things she did now; lawyers took their paychecks, and ex-husbands felt like they'd dodged a bullet.

One day, she asked herself why bother with the charade? No man would stay with a woman who had no interest in his white manhood. They never knew the real reason, and she kept it that way. Black porn was her only source of true sexual pleasure. On her 35th birthday, she vowed to devote her life to black porn and pleasure – no more husbands, no more awkward nights; just her hand, her toys, and hours and hours of beautiful black porn.

Now that she was free, her porn addiction could take root and grow.

It started with late-night rentals. Then pirated clips. Then a second laptop. Then she built a dedicated room just for porn and masturbation. Then she got a custom PC built with multiple screens. Then she just flat out starting buying porn outright with multiple subscriptions. She stopped watching movies, or ‘normal’ TV.

She only kept enough free space to terrorize her co-workers nag the neighbors to death over arbitrary HOA rules. Meredith really didn’t have friends. She didn’t know how to really talk to people. Any attempt to communicate just came off harsh and off-putting. She really couldn’t help it. But it also built a wall so no one got curious.

Meredith knew exactly what she was – not asexual, not prudish, but simply disinterested in sex that demanded anything from her. She wanted to watch, hidden and dripping, craving the kind of raw abandon she could never fake with a white man in the room. Naked white flesh didn't interest her.

She tried other porn: white bodies, artsy erotica, cheap gonzo; interracial – but it all felt airless, plastic, too much like her own life: sterile and polite. Black porn, though – the raw amateur stuff, scenes shot in messy bedrooms, women who laughed while they sucked dick, men who didn't pose or act – that was real. That made her drip.

Her first orgasm watching black porn had changed her forever; she was bonded to it, worshiped it, devoted to it.

She started hunting for it obsessively: anonymous accounts, secret folders, curated playlists no lover would ever see. She'd stand in front of her HOA neighbors the next day, pale and pressed and perfect, all while her thighs would still be tacky with the memory.

It became more than a brief indulgence over time. Somewhere along the line, it turned into a ritual. It became a hunger that waited for her every day at 5 PM.

Her goon cave – a room in a house bigger than she needed – was her true marriage and partner now. The tabs were her vows, the moans her comfort, and the pixel shadows of black skin, sweat, and stretch marks more real than the local country club brunches she skipped.

It wasn't about the men who left her; they could leave, and they did leave. She'd always belonged to this screen, this endless library of black beauty that made her cold exterior crack and melt.

She'd never tell a soul, but every time she came, she told herself thank you – to the faceless performers, to the strangers who uploaded shaky phone clips, to the pro amateurs with the good lighting, the bodies that made her feel alive in ways her real life never did.

Black porn worked for Meredith because her whole life was curated performance: neatness, coldness, politeness. But the black porn she found was everything she wasn't – raw, unpolished, alive, sweat-slicked, loud, unashamed.

White porn felt staged; fake moans and airbrushed bodies that mirrored her own life's sterility. But black porn, especially the kind she found on fan sites, looked real: real skin, real curves, real talk, real noise.

A black woman in a grainy amateur video or even in a home studio – thick thighs, stretch marks, unbothered by the mess – was the opposite of Meredith's buttoned-up HOA universe. It was liberation – proof that a woman's body didn't have to be stiff and apologetic; it could take up space, drip, laugh, roar.

And she couldn't be that woman in living life, but she could worship her in secret. On loop. Over and over, until her fingers went numb.

As she looked back on everything she wondered why she even married white men at all. Meredith didn't understand that part of herself at first – she thought her numbness in bed was just “being a lady.” She'd been raised to believe good girls crossed their legs and kept the lights off. The first marriage was what was expected: college sweetheart, starter home, missionary for him once a week. She told herself it was normal to feel nothing.

When he left, she married again – older man, better money, bigger house. Same cold bed. She tried harder that time: lingerie, candles, wine. Nothing. She thought if she acted the part well enough, the spark would come.

It never worked. Nothing could replace porn. By the third marriage, she didn't even pretend; he had affairs, and she didn't mind. She had her cave. The more he was gone, the more she had time to indulge in pornography and masturbation.

So now Meredith's whole life is a contradiction: a carefully manicured fortress of coldness... with a hidden, dripping shrine to the messiest, loudest, realest bodies she worships but can't ever be.

Porn was just the door; the real hook was that she couldn't have them. No black woman would want her: brittle, cold, coiled in country club blandness. That made porn perfect and safe. She could consume and worship them in endless loops, pixel and pixel, a ghost behind her locked door. No risk of being seen for what she really is: a fraud who only melts for the softness, the power, the rawness she'll never deserve to touch.

She married men because that was what women like her did – numb sex, fake moans; all camouflage for the real ritual waiting at 5 PM: pull the curtains, open the tabs, see and masturbate to the women she could never speak to in daylight.

No black woman has ever touched her. None ever will. Her worship stays as a one way ritual. She has sacrificed everything for black porn. Her knees on the rug, fingers soaked, breath rasping on the silent name: Goddess.