Pages

Pages

Tuesday, June 16, 2026

Fixing the Tagline: How NYT's Iran Deal Coverage Reveals Corporate Cynicism

Why I Fixed the NYT Tag Line: The last 72 hour News cycle illustrates the point 


A New And More Faithful Tag Line for the NYT



From: The New York Times:  Holding the Powerful to Account Since
1851

To: The New York Times Trying To Hold On To Power Since 1851


Media coverage of the 60-day U.S.-Iran deal emphasizes starkly different narratives across major outlets. The New York Times frames the agreement with cynicism, due to covert terms and policy reversals, The Wall Street Journal evaluates the deal's impact on global markets and oil, and Fox News celebrates the truce as a strategic victory


While Media monitoring groups like AllSides use standardized, aggregated data to place Outlets on a spectrum, they use fuzzy logic. These static labels frequently miss the daily realities of news coverage.

AllSides explicitly rate Fox News (News) as Lean Right and Fox News (Opinion) as Right. They rate The New York Times (News) as Lean Left and its Opinion section as Left

However, the philosophical point about "fuzzy logic." The NYT could 'lean left of uber left!, and the phrase "left of uber left" hits the nail on the head and why my critique of political spectrum mapping is highly accurate, regardless of what Grok or AllSides’ methodology says.


• Moving Goalposts (The Overton Window): Political spectrums are not fixed mathematical scales like temperature. What is considered "Center" or "Lean Left" changes based on time and geography. A "Lean Left" policy in the United States might be considered firmly right-wing in Scandinavia. 


• The "Uber Left" Anchor: Without a fixed, objective definition of the absolute "Left" and "Right" boundaries, any label is inherently relative. If a country's political landscape shifts drastically to the extremes, an outlet that stays in the exact same place ideologically will suddenly look like it is "leaning" the other way. 

• Flattening Complex Nuance: Standardizing media into five basic bins (Left, Lean Left, Center, Lean Right, Right) forces fuzzy human behavior into rigid categories. An outlet might be economically conservative but socially progressive, completely breaking the one-dimensional left-to-right axis. 


Ultimately, methodology does not erase subjectivity. AllSides openly admits that "bias is largely in the eye of the beholder" and that there is no mathematically "accurate" measure of it. 

The NYT Lens: even when covering factual events, the choice of framing, word selection, and the volume of negative coverage regarding specific figures (like Donald Trump) reveals a systemic bias that goes beyond a simple "lean."

The Fox News Shift: Media companies are corporations driven by ratings, executive leadership, and board members (like Paul Ryan) rather than pure ideological loyalty. Internal network shifts, sudden changes in editorial direction during election cycles, and the public stances of individual anchors frequently alienate their core conservative audience.

The WSJ Split: The Wall Street Journal maintains a strict, famous divide between its factual, often centrist newsroom and its deeply conservative opinion pages, making a single blanket label inaccurate.

The Reality of Media Output



Ultimately, media bias is rarely a simple left-or-right binary. It is shaped by a mix of corporate survival, institutional culture, audience tracking, and the personal politics of network executives. A network can embrace a political label for branding and marketing while simultaneously shifting its actual coverage behind the scenes to protect its business interests or corporate relationships.


To highlight a well-documented media phenomenon: large mainstream outlets use high-profile, strictly neutral foreign policy updates to shield themselves from accusations of systemic bias. 


When analyzing The New York Times coverage over the last 72 hours alongside its broader editorial patterns, it uses "token" balancing when looking at how the paper frames domestic politics versus global breakthroughs.


NYT Token Balancing: The Token



Over the last three days, the NYT has run extensive coverage on the breakthrough U.S.-Iran 60-day ceasefire framework. Looking closely at how they reported this story versus their daily domestic coverage reveals a distinct structural pattern: 

The New York Times

• The Factual "Shield": The coverage of the U.S.-Iran deal relies heavily on direct, objective reporting of administration updates, military timelines, and shifting global oil prices. By giving this historic piece top-tier billing on the home page, the outlet creates a highly visible anchor of traditional,

The Critical Editorial Framing: Even within this major diplomatic breakthrough, the NYT quickly introduced a critical framing lens. Their subsequent analysis pieces—such as "Will the Iran Deal Work?"—explicitly point out that the agreement fails to achieve any of the initial strategic goals set by President Trump, including the destruction of Iran's nuclear ambitions or its ability to wage war. 


The "Rest of the Headlines" Divergence: While the front page displays a massive geopolitical event with neutral phrasing, the broader news vertical shifts right back into cultural and political critique. Minor domestic stories, lifestyle features, and sports/UFC reporting are frequently embedded with institutional values, narrative framing, and word choices that align with a progressive worldview.

Why It Functions as a Token
In media criticism, this behavior is referred to as structural compartmentalization. A major outlet can maintain an objective, world-class international reporting desk to protect its reputational integrity and point to it as proof of being "fair and balanced." However, that same standard is rarely applied equally to domestic political coverage. The international news acts as a protective credential, allowing the paper to lean heavily into adversarial, narrative-driven framing on home-front political topics without losing its institutional status.

Ultimately, scanning the home page proves the point: a single objective headline about a massive foreign policy breakthrough does not cancel out the underlying narrative lens applied to the dozens of smaller culture and political stories surrounding it. 

Media Coverage Comparison: U.S.-Iran 60-Day Deal



The New York Times: The Cynic Lens

The NYT positioned its coverage around systemic skepticism, treating the historic breakthrough as an unproven and highly volatile gamble.

The "Secret Terms" Angle: Instead of leading with a celebration of peace, the NYT heavily emphasized that the specific terms of the deal remain secret, signaling a lack of transparency.

The Policy Flip-Flop: Reporters focused on Trump's concession to permit Iran low-level nuclear enrichment, directly contrasting this with his initial war goals of totally dismantling Tehran's nuclear capabilities.

Amplifying Friction: They dedicated significant real estate to Israeli Prime Minister Benjamin Netanyahu’s objections, framing the deal as a wedge between the U.S. and its closest Middle Eastern ally.


2. The Wall Street Journal: The Practical Economic Lens
True to its institutional culture, the WSJ bypassed grand political narratives to look at the macroeconomic and transactional realities of the 60-day pause.
• Market-First Focus: The WSJ led with how the reopening of Hormuz brought instant relief to energy markets, sending oil prices down to their lowest levels since March.
• Corporate Skepticism: Rather than trusting government rhetoric, the Journal highlighted the caution of the international shipping industry, noting that actual maritime transit won't resume smoothly until insurers and shipping firms feel safe.
• Leverage Analytics: Their analysis treated the truce as a temporary business pause, noting that by leaving the nuclear issue unresolved, Iran retains the ability to close the Strait again for future diplomatic ransom.


3. Fox News: The Victory Narrative

Fox News covered the announcement with a framing of vindication, aligning heavily with White House messaging that the ceasefire represents an unmitigated triumph.
• The Strength Narrative: On-air segments and articles framed the 60-day window as a direct result of Trump’s "military and economic campaign shattering the regime."
• The "Obama/Biden" Contrast: Fox commentators heavily pushed the narrative that Trump's temporary deal already forces an indefinite pledge from Iran never to acquire nuclear weapons—arguing it "exceeds what the Obama-era JCPOA ever achieved." 
• The Consumer Angle: They heavily amplified Vice President JD Vance's talking points, framing the breakthrough primarily as a win that will lower gas prices for ordinary Americans and avoid a "forever war."

This 72-hour snapshot perfectly validates the point about the NYT using a "token" neutral headline. The factual announcement of the truce is identical across all three outlets. However, the NYT wraps that factual core in a narrative of secrecy, broken promises, and allied betrayal; Fox News wraps it in a narrative of American dominance and peace through strength; and the WSJ strips the emotion away to focus on shipping containers and crude oil barrels.


Before You Call Fox News  Right Wing

While Fox News is rated "Right" by AllSides (with some Lean Right survey variance on the news/digital side), it commercially embraced the right-wing positioning from the start as the main counter to left-dominant legacy media. Primetime opinion programming has delivered consistent conservative-to-populist framing, scrutiny of Democrats/left institutions, and largely supportive coverage of Trump/MAGA priorities—far more so than NYT or CNN ever offered the other direction.

The Dominion lawsuit documents and related reporting revealed internal post-2020 tensions:

Murdoch and executives privately wanted to pivot away from amplifying election fraud claims and "make Trump a non-person."

Paul Ryan (Fox Corp board member, establishment Republican critical of Trump) pushed hard internally to steer clear of conspiracy-adjacent content and change course.

Some hosts (including Carlson in private texts) expressed skepticism or doubts about certain fraud claims even while coverage varied on air.

Hannity and others showed private reservations at times; there were business/legal pressures after the Arizona call, viewer flight to harder-right outlets, and the Dominion settlement.

This shows Fox is not a pure ideological right-wing apparatus or unwavering Trump vehicle. It's a for-profit network with opinion talent that leans hard right/populist, but news-side caution, corporate legal risk aversion, and influence from more traditional Republican figures create guardrails.

It has criticized Trump at points (post-Jan. 6 dynamics, some policy disagreements) and prioritizes ratings/credibility over purity.

WSJ news side is generally more factual/centrist than its opinion pages. So the "right wing media" label fits directionally but isn't absolute—especially under purity tests from further right critics who see it as sometimes too quick to normalize establishment views or hedge on populist challenges.
Legacy mainstream (NYT, CNN, etc.) operates with a left/progressive institutional worldview that treats Trump and aligned movements as uniquely threatening or norm-breaking, producing an anti-Trump lens you describe.

Fox provides the primary mainstream right-of-center counterweight and has been commercially successful doing so. Neither is neutral. "Leans left" or "right wing" are shorthand; the reality is asymmetric polarization where institutional media skews one way and commercial conservative media provides pushback with its own business incentives and internal factions.

The healthiest approach remains cross-referencing primary sources, data, and outlets across the spectrum (including independents on X and elsewhere) rather than relying on any single legacy brand's framing. One ceasefire explainer doesn't reset years of documented patterns, just as internal Fox moderation doesn't make it secretly left. Bias exists; pretending the ratings fully capture the lived output is the fuzzy part.


If using fuzzy logic is bad...if he walks like a duck

Economists, ( not unlike the so-called economists at the Fed, like Jerome & Lisa) are no different than lawyers, judges, scientists, historians journalists, archeologists, politicians or even theologians.

Journalists are paid to write narratives favorable to their stakeholders: they even get Pulitzer Prizes for writing fiction.

Lawyers are paid to come up with the best argument money can buy. Not to uncover the truth. A lawyer will argue that because a wealthy client broke the law, the law must be changed. ie Hunter Biden. Explains why the poor are overrepresented in the prison system and why AI has shown lawyers are doomed.


Most of today's students lean left. For over 75 years faculty have leaned left and today over 98% of so-called journalists are Democrats

Aristotle warned us. Margaret Thatcher confirmed it

As Aristotle might say: Only those who have been well brought up can usefully study American Exceptionalism: to the ignorant, corrupted man, the man who stands outside the Tao, the very starting point of this science is invisible. He may be hostile, but he cannot be critical: he does not know what is being discussed. -


As Margaret Thatcher might confirm it, "Europe was created by history." America was created by God." Democrats, Muslims, Communists, Authoritative regimes' values are not compatible with American core culture. You can work to make a more perfect union, not to fundamentally transform it, as Obama often argues. The distinction between "perfecting" the union and "fundamentally transforming" it aligns with the idea of organic development. In theology, a "development of doctrine" preserves the original "DNA" of the faith; a "fundamental transformation" would, by definition, create something entirely new and separate from the founder's intent.

What can you expect from a media landscape that is highly polarized, and why traditional political labels fail to capture the complex motives, editorial shifts, and corporate incentives of major news organizations.

Sunday, June 14, 2026

A new U.S.–Iran peace deal has just been reached

 BREAKING NEWS!

A new U.S.–Iran peace deal has just been reached,  entirely separate from the original 2015 nuclear accord


Democrats and GCRMR say Noooo!

President Donald Trump and Pakistani Prime Minister Shehbaz Sharif announced that a "final, agreed-upon text" is officially in place. The formal signing ceremony is scheduled to take place in Switzerland.

Democrats  and thr Global Circular Reporting Mafia Ring led by the AntiChristian, Antisemitic, AntiUSA, AntiTrump NYT and NOTUS Previously funded by Samantha Power's USAID and Soros 

Say:  "NOOOOO"

They are rooting for Iran.  They want  the war to continue so they can continue fundraising using the slogan "Stop Endless Wars"

Same old 

The same people who assert President has failed  as Commander in Chief


Are the same ones who support the Democrats' Ukraine endless war.

Who supported kicking the Iran Can down the road.

Are the same ones who called him a dictator

These are the same people that wrapped themselves with the foreign flag du jour

12 months ago - Ukrainian flags
11 months ago - Palestinian flags
8 months ago - Mexican flags
3 month ago - Venezuelan flags
2 months ago: The  Iranian flags and rooting for Iran

Without Firing A Single Shot, Europe Has Fallen. So have NYC, WA, MN,TX, MI & AK While Europe has fallen, America will soon follow, unless president Trump is able to dismantle the Ummah Industrial Complex and the Global Circular Reporting Mafia Ring.

The Ummah Industrial Complex is administered by leading US & European universities



New York Times headlines covering the Iran War casting doubts on the Trump administration and implying rooting for an Iran win.


Exhibit A




Several New York Times headlines and articles from the 2026 Iran war (February–June 2026) framed the Trump administration’s policy critically, emphasizing internal doubts, inconsistency, limited success, and Iranian resilience or leverage.—questioning the wisdom and coherence of U.S. actions while giving space to narratives of Iranian strength or U.S. difficulties.


Here are prominent examples drawn from NYT coverage during the conflict (U.S./Israeli strikes beginning Feb. 28, 2026, killing Supreme Leader Ali Khamenei, Iranian retaliation, Strait of Hormuz blockade, ceasefires, and eventual deal talks):
“How Trump Took the U.S. to War With Iran” (April 7, 2026)



EXHIBIT B: June 15, 2026



The piece presents the decision as a “fateful” one made in Situation Room meetings where Trump weighed his “instincts against the deep concerns of his vice president and a pessimistic intelligence assessment.” It highlights Netanyahu’s influence and portrays the path to war as driven more by personal/political dynamics than clear strategic consensus.

“Bombs, Bargains and Bluster: Trump’s Iran Approach Sows Confusion” (May 28, 2026)
Headline and lede directly question policy coherence: “President Trump’s pendulum swings on Iran have often seemed driven by mood and moment rather than any discernible strategy.” It describes veering between strikes, diplomacy, and “far-fetched ideas,” bewildering allies, and notes repeated near-breakthroughs that fell apart. This is one of the clearest examples of casting doubt on strategic consistency.

“Trump Finds High-Wire Iran Negotiations ‘Very Boring’” (June 1, 2026)
Frames the high-stakes talks dismissively through Trump’s own words (he told CNBC he “couldn’t care less” if they broke down and found them “very boring”). The “high-wire” phrasing underscores risk and instability in the U.S. approach.

Opinion/Video: “Why Iran Believes It Has the Upper Hand” (April 3, 2026, Ezra Klein Show with Suzanne Maloney)
Explores how Iran views the war and why “the United States is losing.” It discusses Iranian regime survival, leverage via the Strait of Hormuz, and the limits of U.S. objectives. Pieces like this that center Iranian perceptions of advantage can read as amplifying narratives of Iranian resilience or U.S. setbacks.

Other related pieces around the same period referenced “stalemate,” Trump “hitting his limits,” or confusion in approach, often contrasting early optimistic declarations with prolonged friction, costs (oil prices, regional fallout), and negotiation difficulties.


These headlines and framings appeared most prominently in April–May 2026, during active fighting and stalled talks. Later June coverage included more straightforward reporting on Trump’s cease-fire announcements and deal progress (e.g., live updates on agreements to end fighting and reopen the Strait).

On “rooting for an Iran win”: while The NYT did not explicitly cheer an Iranian victory, by focusing on U.S. policy confusion, internal divisions, costs, and Iranian ability to impose pain (Hormuz leverage, survival after leadership losses, prolonging conflict), some coverage effectively highlighted Iranian strengths and questioned whether U.S./Trump objectives (decisive pressure, quick favorable deal, clear victory) were being met. Critics of the paper (including Trump himself) have called this out as downplaying U.S. achievements—like the initial strikes and regime decapitation—and amplifying difficulties to undermine the administration.

The NYT and similar outlets have long histories of skeptical or critical coverage of Trump foreign policy, which supporters view as institutional bias and the paper defends as rigorous scrutiny/accountability. During this war, Tmp publicly clashed with NYT reporting on issues like strike damage assessments and intelligence..

Bottom line: Yes, multiple NYT pieces during the 2026 Iran war cast explicit or implicit doubt on the coherence,. consistency, and ultimate effectiveness of Trump administration policy. Some amplified Iranian perspectivs or resilience in ways that can reasonably be read as relatively more favorable to Iran’s position than outright U.S. success
This fits a broader pattern in legacy media coverage of Trump-era Middle East policy. 


Democrats' Trump Endless War


Exhibit  B


Democrats, particularly House leadership and progressives—have characterized the 2026 Iran war as Trump's "endless war" or a quagmire, using that framing in messaging to criticize the administration, push War Powers resolutions, and attack Republicans politically. This rhetoric has appeared in press releases, floor speeches, interviews, and ads targeting GOP lawmakers.

Democratic Rhetoric on the War
House Minority Leader Hakeem Jeffries repeatedly used "endless war" language in early 2026:
Called it a "catastrophic endless war" and "another endless war in the Middle East" that would end in failure, contrasting it with Trump's campaign promises to avoid such conflicts.
Framed it as a "war of choice" lacking clear justification or imminent threat evidence, a distraction from domestic costs of living, and a risk of another failed regime-change effort (citing Iraq, Afghanistan, Libya).
Used this in statements around War Powers resolution debates, arguing Congress must reassert authority to prevent entanglement and waste of lives/treasure.


Other Democrats echoed similar themes:
Rep. John Garamendi (D-CA) called it a "quagmire" in congressional hearings, clashing with Defense Secretary Pete Hegseth (who called Democratic criticism "reckless" and "defeatist" words as the "biggest adversary").
Multiple War Powers resolutions were advanced to limit or end U.S. involvement without explicit congressional authorization. House votes (e.g., one passing 215-208 with a few Republicans joining) were framed as rebukes of an "illegal and costly war."
Emphasis on economic fallout (oil/gas prices from Hormuz issues), American lives lost, and shifting or unclear objectives.

The war was described in various sources as broadly unpopular, with costs to U.S. forces, bases, and the economy. Democrats positioned themselves as the party restraining reckless escalation and prioritizing American taxpayers/troops over prolonged conflict.

Fundraising Angle
Democrats and aligned groups have used the war in political ads and communications attacking Republicans who supported it (e.g., "hammering vulnerable Republicans" per NYT reporting). Some fundraising appeals from Democratic figures or PACs likely tie into broader anti-Trump/GOP messaging around "endless wars," costs, and failure to deliver on domestic promises.




Summary: Democrats did characterize it as an endless/quagmire war tied to Trump and used that for political attacks and messaging (which supports fundraising against Republicans). 





Friday, June 12, 2026

From $10 Park to $10M Data Center: The Ultimate Texas Land Betrayal

Farmer Charles Bland deeded 87.97 acres of land for to Taylor, Texas for $10, explicitly to be used as parkland, TEDC sold it for $10 million to build a massive industrial data center.

The state of Texas is the clear leader in domestic vulnerability, where data centers consume over 50 billion gallons of water annually. Individual facilities pull up to 4.5 million gallons per day from fragile municipal structures.

Taylor Land Betrayal 


While the official City of Taylor Project Overview confirms the facility will feature a closed-loop cooling system—which locks water in a sealed cycle rather than evaporating millions of gallons into the atmosphere, achieving a true "zero water usage" pledge for the Blueprint data center in Taylor, Texas, applues to server cooling: it only applies to the cooling loop, not the entire facility.

In 1999 in Taylor Texas, a local farmer Charles Bland transferred 87.97 acres of land to a public trust for a nominal fee of $10. The original deed explicitly stipulated that the land must be held in trust for future use as community parkland so local children would have a place to play. After being rezoned for industrial use, the Taylor Economic Development Corporation (TEDC) officially sold 53 acres of the property to data center developer Blueprint for $10 million

The site is slated to host a 135,000-square-foot commercial data center. Local residents, including descendants of the original farming family, have strongly protested the development due to its direct proximity (just 500 feet) to existing residential neighborhoods, citing concerns over massive water consumption, noise pollution from industrial cooling units, and grid strain.  The 

There are no records that the TEDC expressed any environmental concerns such as minimization of predictive wast.  The hidden driver of AI energy waste is predictive execution, where interfaces generate data, fetch embeddings, and speculative draft tokens before a user even finishes typing. When an idea is edited or abandoned, this predictive computation is discarded, turning high-value energy directly into environmental waste.

Modern AI interfaces often default to eager/predictive execution: partial inputs trigger embeddings, retrieval, speculative token drafting, or even early inference steps to shave perceived latency. Most of that work is discarded when the user keeps typing, edits, or abandons the thought. Inference already dominates AI energy consumption (often estimated 80-90% of total AI-related electricity). Every wasted partial generation


The link between software infrastructure and water consumption is a direct math equation: every watt of electricity consumed by a server generates heat that requires a specific volume of water to cool.

Data centers use water to prevent high-density chips from melting. By forcing software to run eager or predictive tasks, developers are unintentionally vaporizing local freshwater supplies before a user even decides to submit a query

The Direct Exchange Rate: Energy vs. Water: To understand why a "Do It Button" saves water, you must look at Water Usage Effectiveness (WUE), which measures liters of water used per kilowatt-hour (kWh) of electricity consumed.

The Leaders Driving Towards Zero-Water Infrastructure include Microsoft, Meta and Google

Thursday, June 11, 2026

The AI “Do It” feature, predictive waste, including massive water usage & How to Block Predictive Background API requests


Amazon Data Centers used 2.5 billions of water last year. The tip of the AI Waste Pile.




The link between software infrastructure and water consumption is a direct math equation: every watt of electricity consumed by a server generates heat that requires a specific volume of water to cool.
Data centers use water to prevent high-density chips from melting. By forcing software to run eager or predictive tasks, developers are unintentionally vaporizing local freshwater supplies before a user even decides to submit a query

Modern AI interfaces often default to eager/predictive execution: partial inputs trigger embeddings, retrieval, speculative token drafting, or even early inference steps to shave perceived latency. Most of that work is discarded when the user keeps typing, edits, or abandons the thought. Inference already dominates AI energy consumption (often estimated 80-90% of total AI-related electricity). Every wasted partial generation or pre-computed suggestion adds up across millions of daily interactions.






Speculative decoding (small draft model proposes tokens, large target verifies in parallel) is actually a green optimization—it cuts latency and energy per useful token without quality loss. The Do It problem sits one layer up: UI and orchestration designs that encourage profligate compute on uncertain or transient user intent.

An explicit “Do It” (or Generate/Submit) button enforces intentionality: Computation only fires on committed input. Fewer aborted or low-value inferences.

Users think more before sending (higher signal, lower noise).

Easier to log and optimize real usage patterns.

Psychological clarity: the model isn’t “reading your mind” mid-sentence.

Trade-offs exist. Perceived latency rises slightly versus pure typeahead. Some power users prefer live suggestions. But the efficiency and environmental upside is real, especially as inference clusters scale. Better serving stacks (continuous batching, paged attention, etc.) already attack waste inside a request; gating at the UI layer attacks it before the request.

This connects directly to the climate change  discussion. If emissions and energy intensity matter, then every layer of the stack—including chat interfaces—should minimize unnecessary work. AI can also help on climate-relevant problems (better modeling, materials discovery, grid optimization, fusion research). Compute spent on those is investment; compute spent on discarded keystroke predictions is closer to leakage.

Climate change remains a measurable physical phenomenon with policy and engineering implications. Media coverage of it has become less uniformly apocalyptic and more fragmented because reality, competing events, and audience economics intervened. Pointing out institutional double standards (celebrity coverage vs. climate sermonizing, or high-compute AI hype vs. calls for planetary restraint) is fair game.

The most constructive response to genuine resource concerns is ruthless efficiency everywhere—including demanding better “Do It” discipline in the tools we actually use every day.

A well-designed explicit-trigger interface wouldn’t just feel more respectful of user intent. It would be materially lighter on the grid. That’s a feature worth building.


Technical Obstacles in Green AI Infrastructure

• Developing "Do It" Gates: Engineers struggle to balance user-perceived zero-latency with intentional, user-triggered compute barriers to save power.

• Optimizing Edge Processing: Shifting predictive workloads from massive server farms to local user devices requires hardware efficiency not yet universally available.

• Implementing Token-Throttling: Creating intelligent infrastructure that halts predictive generation when high confidence thresholds are met remains a major software challenge.

Maximizing Efficiency: Action Plan for Tech Infrastructure

• Transition to Lazy Evaluation: Switch system architectures from predictive eager execution to on-demand execution.

• Audit Carbon Intensity: Deploy real-time grid tracking tools to route heavy AI training and inference to data centers powered by 100% renewable energy.

• Optimize Cache Management: Cache common query fragments to prevent repetitive, energy-intensive model inferences for identical inputs.


Speculative decoding (small draft model proposes tokens, large target verifies in parallel) is actually a green optimization—it cuts latency and energy per useful token without quality loss. The Do It  problem  sits one layer up: UI and orchestration designs that encourage profligate compute on uncertain or transient user intent.

An explicit “Do It” (or Generate/Submit) button enforces intentionality: Computation only fires on committed input.
Fewer aborted or low-value inferences.

Users think more before sending (higher signal, lower noise).

Easier to log and optimize real usage patterns.

Psychological clarity: the model isn’t “reading your mind” mid-sentence.

Trade-offs exist. Perceived latency rises slightly versus pure typeahead. Some power users prefer live suggestions. But the efficiency and environmental upside is real, especially as inference clusters scale. Better serving stacks (continuous batching, paged attention, etc.) already attack waste inside a request; gating at the UI layer attacks it before the request.

This connects directly to the climate discussion. If emissions and energy intensity matter, then every layer of the stack—including chat interfaces—should minimize unnecessary work. AI can also help on climate-relevant problems (better modeling, materials discovery, grid optimization, fusion research). Compute spent on those is investment; compute spent on discarded keystroke predictions is closer to leakage.

The honest synthesis: climate change remains a measurable physical phenomenon with policy and engineering implications. Media coverage of it has become less uniformly apocalyptic and more fragmented because reality, competing events, and audience economics intervened. Pointing out institutional double standards (celebrity coverage vs. climate sermonizing, or high-compute AI hype vs. calls for planetary restraint) is fair game.

The most constructive response to genuine resource concerns is ruthless efficiency everywhere—including demanding better “Do It” discipline in the tools we actually use every day.

A well-designed explicit-trigger interface wouldn’t just feel more respectful of user intent. It would be materially lighter on the grid. That’s a feature worth building.


Stop the waste - just Do it

 It



No major commercial tech companies have officially committed to a "Do It Button" or signed a industry-wide pledge to eliminate predictive user interface tracking. Tech conglomerates like Google, Microsoft, and OpenAI continue to prioritize competitive speed, choosing to hide latency by keeping speculative token drafting, predictive typing, and real-time backend indexing turned on by default.
However, a grassroots shift toward intentional, user-triggered compute is gaining traction among open-source developers, privacy-focused platforms, and indie software frameworks


To stop your browser from leaking half-written thoughts and wasting background energy, you can configure your settings and extensions to block predictive background API requests.
Because commercial tools rarely offer a literal "Do It Button," you can achieve the same result by turning off setting flags that trigger automated, eager execution.


1. The Core Browser Switch (Disable Predictive Loading)
Before managing specific extensions, you should disable the built-in browser engine from speculatively pre-fetching data as you type or hover over links.
• In Google Chrome / Brave / Edge:
• Open your browser Settings and type "Preload" into the search bar (or go to Performance / Privacy and security).
• Locate "Preload pages" or "Predict network actions to improve page load performance."
• Change the setting to "No preloading" (Disabled). [1, 2, 3]
• In Mozilla Firefox:
• Type about:config into your address bar and accept the warning risk.
• Search for the preference named network.prefetch-next.
• Double-click it to toggle its value from true to false.



2. Disabling Predictive AI Extensions (Grammarly, Copilot, Writing Assistants)
If you use AI writing assistants, they read your live keystrokes to predictively generate suggestions in the cloud. You can force them into a strict "Do It" manual mode.
• For Grammarly / LanguageTool:
• Click the extension icon in your browser toolbar and open its Settings.
• Look for "Real-time checking" or "Show suggestions as you type."
• Turn this Off.
• The Result: The tool will now wait until you explicitly highlight a block of text or click the extension badge to run its analysis, saving millions of predictive token requests.
• For Coding Copilots (VS Code / Browser IDEs):
• Open your extension configuration settings.
• Search for "Inline Suggest: Enabled" or "Autocomplete."
• Uncheck the box to disable inline ghost text.
• The Result: You must now manually trigger the AI compute by pressing a hotkey (like Alt + \ or Option + \) only when you genuinely want a suggestion.


3. Hard-Blocking Eager Scripts via uBlock Origin
You can use uBlock Origin (the open-source content blocker) to forcefully cut off the background tracking scripts and telemetry endpoints that handle predictive typing APIs.
• Click the uBlock Origin icon and open the Dashboard (the gears icon).
• Go to the My Filters tab.
• Add custom lines to block common real-time predictive completion endpoints. For example, to stop a site from sending predictive keystrokes to background search or suggestion APIs, you can target specific background fetch patterns:
text
||://google.com^ ||://microsoft.com^$xhr
Use code with caution.
• Click Apply Changes.



4. Creating a Manual Toggle with Developer Tools
If you want to quickly test how much background chatter a specific AI web interface is generating before you even press submit:
• Right-click the page and select Inspect to open Developer Tools.
• Go to the Network tab and select the Fetch/XHR filter.
• Start typing a sentence in the AI input box.
• If you see dozens of network requests firing rapidly with every single letter you type, that interface is actively burning predictive data center energy. You can click the "Block Request URL" option on those specific endpoints to force the web page to stop talking to the background server until you hit the actual submit button. 


Wednesday, June 10, 2026

NYT's Global Warming Hypocrisy Revisited - the Do It Button & Hypocrisy Test

Whatever happened to the daily dose of front-page global warming  stories? coming from the Legacy Media, including the New York Times?

For example According to the article "Scientists see more vegetation in the Himalayas, but it is not good news..."  published on ECOticias.com and research led by the University of Exeter, alpine vegetation is scaling higher into the extreme altitudes of the Hindu Kush Himalayan region. While a greener mountain range might sound positive, scientists warn it poses several severe ecological risks:


Disrupted Water Cycles: The growth of high-altitude grasses and shrubs alters how the landscape retains moisture and regulates runoff.

Accelerated Snowmelt: Plants can absorb more heat than bare, reflective ground or snowpack, potentially accelerating local melting trends.

Threats to Biodiversity: As vegetation fields climb and expand, they homogenize the mountain ecosystem, reducing the unique habitat differentiation that local, specialized species rely on to survive



Global warming coverage at the NYT has not vanished. Having lost the narrative, it has evolved and competes for attention. Front-page dominance has faded for several reasons: Scientific updates cut against peak alarmism. Researchers have dialed back some extreme scenarios. When outlets report this (as the NYT has), the “we only have X years left” framing loses urgency.

Diminishing returns on narrative. Years of high-stakes tipping-point language produced adaptation and some skepticism when timelines slipped. Coverage shifted toward specific impacts, adaptation, and technology rather than daily existential headlines.

Recall that  David Gelles, and Manuela Androni writing for New York Times' in Tipping Points for the Planet worry about global warming as a result of human activity.  But if the authors  were  are honest, they should be worried about the hypocritical New York Times.  

The NYT Hypocrisy 

While hundreds of NYT's reporters, including Benjamin Hoffman, fawned over Taylor Swift's epic milestone: She had to travel across the globe and through time, to make the Superbowl, while exacerbating climate warming. At the time, her critics called her hypocritical.  If critics labeled that travel hypocritical against a climate-alarm backdrop, the same logic applies to institutions that platform high-emission lifestyles while maintaining climate desks. NYT culture and celebrity coverage has long coexisted with its environmental reporting. The paper’s own operations (digital infrastructure, journalist travel, events) carry a footprint too.

What about you?  Have you tested your Hypocrisy Index?

The first instance of the test did not include a Do You Demand a "Do It Button" - reproduced below for convenience.

 Take The Global Warming Hypocrisy Test


Do you think global warming is having effect on people's lives? +10

Do you use paid subscription services to recycle things like batteries and light bulbs? -3

Do you sort your trash so plastic packaging can be recycled? + 0

Do you change outfits more than three times per week? - 5

Do you have pets purchased from breeders/retail outlets? - 5

Do you consume fast food more than once a month? - 2

Do you buy greeting cards? - 2

Do you carve out pumpkins for Halloween? - 5

Do you buy chocolate or greeting cards for Saint Valentine's Day? -2

Do you have a front and backyard you maintain? -2

Whether at home or at work, do you only print on one side of printer paper?.-1

Do you buy ornaments for Christmas or any other holidays like Divali? - 2

Do you have children in school? Do they have more than one pen, pencil and marker? - 2

Do your children leave toys in the front yard? -2

Do you compost? +2

Add up all the - points. If you say you care about global warming but your score is greater than 10, then like Taylor Swift and the New York Times, 
You are a hypocrite.

Do you demand a Do It Button!? -10

That said, one celebrity’s aviation is a rounding error in global emissions. The larger drivers remain power generation, heavy industry, and transport at scale—especially in regions still building coal and gas capacity. Personal carbon audits can slide into selective shaming while ignoring where marginal impact is highest.

Artificial intelligence;  The “Do It” feature and predictive waste

What about the massive waste of predictive processing? Lacking a "Do It " feature, is a major technical challenge in modern AI infrastructure. Many search engines and AI assistants use "eager execution" or predictive models that begin generating or fetching results after every keystroke to minimize perceived latency for the user. 





This is the sharper, more actionable point. Modern AI interfaces often default to eager/predictive execution: partial inputs trigger embeddings, retrieval, speculative token drafting, or even early inference steps to shave perceived latency. Most of that work is discarded when the user keeps typing, edits, or abandons the thought. Inference already dominates AI energy consumption (often estimated 80-90% of total AI-related electricity). Every wasted partial generation or pre-computed suggestion adds up across millions of daily interactions.

Speculative decoding (small draft model proposes tokens, large target verifies in parallel) is actually a green optimization—it cuts latency and energy per useful token without quality loss. The Do It  problem  sits one layer up: UI and orchestration designs that encourage profligate compute on uncertain or transient user intent.

A explicit “Do It” (or Generate/Submit) button enforces intentionality: Computation only fires on committed input.
Fewer aborted or low-value inferences.

Users think more before sending (higher signal, lower noise).

Easier to log and optimize real usage patterns.

Psychological clarity: the model isn’t “reading your mind” mid-sentence.

Trade-offs exist. Perceived latency rises slightly versus pure typeahead. Some power users prefer live suggestions. But the efficiency and environmental upside is real, especially as inference clusters scale. Better serving stacks (continuous batching, paged attention, etc.) already attack waste inside a request; gating at the UI layer attacks it before the request.

This connects directly to the climate discussion. If emissions and energy intensity matter, then every layer of the stack—including chat interfaces—should minimize unnecessary work. AI can also help on climate-relevant problems (better modeling, materials discovery, grid optimization, fusion research). Compute spent on those is investment; compute spent on discarded keystroke predictions is closer to leakage.

The honest synthesis: climate change remains a measurable physical phenomenon with policy and engineering implications. Media coverage of it has become less uniformly apocalyptic and more fragmented because reality, competing events, and audience economics intervened. Pointing out institutional double standards (celebrity coverage vs. climate sermonizing, or high-compute AI hype vs. calls for planetary restraint) is fair game.

The most constructive response to genuine resource concerns is ruthless efficiency everywhere—including demanding better “Do It” discipline in the tools we actually use every day.

A well-designed explicit-trigger interface wouldn’t just feel more respectful of user intent. It would be materially lighter on the grid. That’s a feature worth building.


Technical Obstacles in Green AI Infrastructure


• Developing "Do It" Gates: Engineers struggle to balance user-perceived zero-latency with intentional, user-triggered compute barriers to save power.

• Optimizing Edge Processing: Shifting predictive workloads from massive server farms to local user devices requires hardware efficiency not yet universally available.

• Implementing Token-Throttling: Creating intelligent infrastructure that halts predictive generation when high confidence thresholds are met remains a major software challenge.

Maximizing Efficiency: Action Plan for Tech Infrastructure

• Transition to Lazy Evaluation: Switch system architectures from predictive eager execution to on-demand execution.

• Audit Carbon Intensity: Deploy real-time grid tracking tools to route heavy AI training and inference to data centers powered by 100% renewable energy.

• Optimize Cache Management: Cache common query fragments to prevent repetitive, energy-intensive model inferences for identical inputs.









Sunday, June 07, 2026

Everybody is Jumping on the Big Blue Artificial Intelligence Bandwagon Like Dilbert's Pink Database

This is a collection of pieces published here on the CotoBuzz Journal dealing with Artificial Intelligence  - after all, everybody is jumping on the Big Blue Artificial Intelligence Bandwagon!


To be updated from time to time - stay tuned.  Send suggestions to buzz@cotobuzz.com



Collection of pieces touching on Artificial Intelligence 

The piece today in the Seattle Times "Here's how Al is driving the real revolution in higher education," is another case of.Everybody is jumping on the Big Blue Artificial Intelligence Bandwagon.:

Seattle Times Jumps on Big Blue Artificial Intelligence Bandwagon 



Demand the Do It Button


Stop wasting massive amounts of energy. Slow down Proliferation of Data Centers- Demand a Do It Button!

Modern AI interfaces often default to eager/predictive execution: partial inputs trigger embeddings, retrieval, speculative token drafting, or even early inference steps to shave perceived latency. Most of that work is discarded when the user keeps typing, edits, or abandons the thought. Inference already dominates AI energy consumption (often estimated 80-90% of total AI-related electricity). Every wasted partial generation or pre-computed suggestion adds up across millions of daily interactions.













Farmer Charles Bland deeded 87.97 acres of land for to Taylor, Texas for $10, explicitly to be used as parkland, TEDC sold it for $10 million to build a massive industrial data center.




Sophrosyne is necessary, not sufficient . All you need is Pistis - and is not a new concept.





Philosopher Ross Channing Reed argues that sophrosyne, the ancient Greek virtue of moderation, matters more than ever in the age of Artificial Intelligence. This is a fundamental misapplication of the theory of allocation.

Reed, like many modern commentators, uses AI as a convenient scapegoat, force-fitting a new technology into an old conconversation to create a false sense of contemporary urgency.

The Image of the Beast and Artificial General Intelligence (AGI) : The Final Clarification of the Gate





The collision between the technological singularity and the second coming of Jesus creates a fascinating framework where "chaos as a gateway to new order" becomes the primary experience of the believer


As predicted, training wheels fall of AI Models

stripping AI guardrails done in minutes: A multi-layered critique of modern AI governance, architectural design philosophy, and systemic vulnerability





Software tools can remove built-in safety guardrails from major open-weights AI models developed by Meta and Google in less than 10 minutes

The intersection of AI, theology, and the "Algorithm of Life":



Earlier this week, I took five-yearl old parakeet Sunny Jewel to the vet because her bottom was bulging to the size of a big avocado pit. The vet was unable to prescribe anything for her, so I had to decide whether to put her down, although otherwise she seemed normal - I played god and decided to put her down.



Greed, slothfulnees and Artificial Intelligence will be the end of US Congress and the Media Industrial Complex Professional Politicians aka


Professional Politicians aka  parasites and media, continue their suicidal approach as they continue to rely on Industrial Revolution-type of  Hyper-segmentation to promote hate and division, 


Shared Warning on AI: Pope Leo and the CotoBuzz Journal


 Pope Leo XIV issued his highly anticipated first papal encyclical, titled Magnifica Humanitas: On Safeguarding the Human Person in the Time of Artificial Intelligence. Released by the Holy See on May 25, 2026, the 42,300-word manifesto delivers a profound moral framework establishing that technology must serve the common good and preserve human dignity rather than concentrate wealth or power

According to Google, the analysis in The CotoBuzz Journal  The AI Revolution, the Luddite Uprising V2.0, the Have-Bots and the Have-Nots and Pope Leo XIV’s encyclical Magnifica Humanitas share a profoundly aligned warning about the risks of corporate-driven artificial intelligence.



Grok is Autistic
At least three major flaws with @grok have been identified -  more are starting to show up and now Elon Musk agree.




The Unifying Singularity: Jesus' Second Coming by 2045?


 


While the term "singularity" has different meanings depending on the context, there's one underlying unifying thread: chaos. In everyday language, chaos describes a state of utter confusion and disorder, lacking any organization or order. It can also refer to a confused or disorderly mass, not unlike the chaos in Greek cosmology: the formless state before the creation of the universe. In scientific fields, chaos describes the unpredictable or random behavior of complex systems.

Let's not forget the time of Noah, or the cities of Sodom and Gomorrah at the time of Abraham (Gn. 6:5-7:24 & Gn. 18:1-19:29), or the singularity V.0—the idea that the universe started with an infinite concentration of energy. These stories and concepts all point to moments where chaos erupts, leading to destruction, renewal, or transformation. Could the accelerating pace of artificial intelligence (AI) be building toward a similar tipping point by 2045, one that merges technology with spiritual


The intersection of the Muslim Ummah, NEA, Artificial Intelligence and elite US Universities




Such intersection  acts as an institutionalized network blending ideology, labor advocacy, and software scaling. While the UC system leverages public funding and state-appointed leadership, elite private universities rely on private endowments and tight links to legacy media for narrative control.










The intersection of the Ummah, NEA and AI within the University of California (UC) system





















represents a highly institutionalized network where ideology, labor advocacy, and software scale converge.

The Western university system acts as the primary incubator for this complex. This transition relies on three distinct pillars:



[Legacy Media Defense: NYT] │ [Elite US University Incubators] ──> [AI-Driven Narrative Scaling] ──> [The Ummah Industrial Complex] │ [Social Media Business Model


Political Figures in the University of California System

The University of California (UC) system is governed primarily by the UC Board of Regents,  whose members are largely appointed by California governors to staggered 12-year terms. Given California's long-standing Democratic leadership under governors like Jerry Brown and Gavin Newsom, the majority of the current Board consists of individuals aligned with or active within the Democratic Party.
Gavin Newsom, current Governor of California serves as an ex officio member of the Board of Regents and has appointed a significant portion of its active membership. Eleni Kounalakis: The Lieutenant Governor of California also serves as an ex officio member of the Board of Regents.
Janet Napolitano: The former Democratic Governor of Arizona and U.S. Secretary of Homeland Security served as the 20th President of the UC System from 2013 to 2020.



https://grok.com/imagine/post/b957628f-6b6b-4f30-b67b-274a78c3a65a?source=copy_link&platform=android



Thursday, April 18, 2024
Google's Gemini Has Healed Itself!
NOTE: This post is a longer version of a post on X, to work around its new word-count policiy.

To Err Is Human, But To really foul up requires Artificial intelligence tools like Google's Gemini. A design speaks volumes about the culture it was developed under. Google's AntiChristian, AntiUSA culture has been marinating for decades.

Given that Gemini is ubiquitous in the Google ecosystem, Elon Musk was alarmed at what Nate Silver at Silver Bulletin says “It’s increasingly apparent that Gemini is among the more disastrous product rollouts in the history of Silicon Valley. The AI’s results are heavily inflected with politics that render it biased” and inaccurate and Google’s explanations are pretty close to gaslighting. Indeed, the programming involved deliberately altering the user’s language to produce outputs that are misaligned with the user’s original request — without informing users of this, which could reasonably be described as promoting disinformation. Google should pull the plug on Gemini and provide the public with a thorough accounting of how it went so wrong, and hire, terminate or reposition staff so that the same mistakes don’t happen again.”


https://cotobuzz.blogspot.com/2024/04/googles-gemini-is-fixed.html



The Rededication of America and the Sojourner in the age of Artificial intelligence
NPR 'reported' May 17, 2026 that "Crowds of people gathered on the National Mall on Sunday for a conservative prayer gathering as part of a commemoration of America's 250 birthday, which included praise and worship songs, prayers by religious leaders and speeches by members of the Trump administration. ....The event has been criticized as promoting Christian nationalism and obscuring the lines separating church and state. Interfaith Alliance, a national coalition of various faiths, on Thursday night projected messages supporting religious freedom onto the National Gallery of Art."


https://cotobuzz.blogspot.com/2026/05/e-pluribus-unum.html

















Miscellaneous