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

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. 

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:

NYT's Global Warming Hypocrisy Revisited

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

Refer to the Recycle Hoax, the Climate Change Billionaires Bliss and Global Warming Hypocrisy 

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.

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.

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.

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

Sophrosyne (Temperance) is necessary but not sufficient. What we truly need is Pistis (Faith).

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 

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

Sophrosyne (Temperance) is necessary but not sufficient. What we truly need is Pistis (Faith).
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 conversation to create a false sense of contemporary urgency.

In reality, AI has absolutely nothing to do with the human need for virtue. The temptation to lose emotional balance, self-restraint, or soundness of mind is not a product of the digital age; it is a permanent fixture of the human condition. Pretending that algorithms have fundamentally altered our moral calculus is a historical blind spot.

While sophrosyne—the inward struggle for moderation celebrated by Plato and Aristotle—is a necessary baseline for human behavior, it is an incomplete answer to our existential anxieties. What we actually require is pistis: trust, deep conviction, and relational loyalty.

This is a 3,000-year-old theological reality. The Book of Deuteronomy, through its ancient Greek translation (the Septuagint), overwhelmingly emphasizes pistis over sophrosyne. The core of Deuteronomy is a covenant treaty requiring total, exclusive allegiance—the exact definition of pistis as fidelity. For example, the Shema (Deuteronomy 6:4-5) demands that Israel love God with all their heart, soul, and strength. This mandates complete relational trust and external loyalty, not merely inner emotional moderation.

The challenge of the modern era is not that AI demands a new application of self-restraint. The challenge is exactly what it has always been: anchoring our fundamental trust, loyalty, and faith in something greater than ourselves.

A good number of writers are using artificial intelligence as an escapegoat, Reed included. In this case, he is forcefitting Artificial Intelligence to argue for sophrosyne. All you need is faith and that's a 3,000 year-old argument

Sophrosyne is the ancient Greek concept of moderation and self-control, while Pistis is the concept of trust, faith, and belief. Sophrosyne (σωφροσύνη): Meaning "soundness of mind." It represents self-restraint, temperance, and emotional balance. Pistis (πίστις): Meaning "trust" or "loyalty." It represents faith, conviction, and reliability.

Plato  and Aristotle celebrated  Sophrosyne as a cardinal virtue. Sophrosyne, adapted into Christian theology as "temperance," is one of the four cardinal virtues required for moral living. Pistis shifted drastically with Christianity to mean divine faith.

The Book of Deuteronomy overwhelmingly emphasizes the concept of pistis (trust, covenant faithfulness, and loyalty) rather than sophrosyne (moderation and self-restraint).

While Deuteronomy originates from Hebrew theology rather than Greek philosophy, the ancient Greek translation of the Old Testament (the Septuagint) regularly uses the root words of pistis to capture the book's primary demands.

The core of Deuteronomy is a vassal treaty or covenant binding Yahweh and Israel together. This requires total, exclusive allegiance—the exact definition of pistis as relational loyalty and fidelity. The Shema: The foundational command of the book, found in Deuteronomy 6:4-5, demands that Israel love God with all their heart, soul, and strength. This demands complete relational trust, not merely inner emotional moderation. The Greek translation uses pistis derivatives to command Israel to "remain faithful" and "hold fast" to God. The book constantly urges Israel to remember God's past actions so they can maintain hope and confidence (pistis) in the future.

John 6:51 as the Ultimate Test of Pistis

In John 6:51 "Jesus said to the Jewish crowds: "I am the living bread that came down from heaven; whoever eats this bread will live forever;

and the bread that I will give is my flesh for the life of the world."
The Jews quarreled among themselves, saying, "How can this man give us his flesh to eat?" Jesus said to them,
"Amen, amen, I say to you, unless you eat the flesh of the Son of Man and drink his blood,.you do not have life within you. Whoever eats my flesh and drinks my blood has eternal life,
and I will raise him on the last day. For my flesh is true food,.and my blood is true drink.
Whoever eats my flesh and drinks my blood remains in me and I in him.
Just as the living Father sent me
and I have life because of the Father,
so also the one who feeds on me
will have life because of me.
This is the bread that came down from heaven..Unlike your ancestors who ate and still died, whoever eats this bread will live forever."

The transition to John 6 captures a parallel psychological and spiritual crisis, shifting the focus from moderation to radical trust (pistis).

The Crisis of Scandal: When Jesus commands his followers to eat his flesh and drink his blood, he deliberately violates deep-seated cultural, legal, and dietary taboos against cannibalism and consuming blood (Leviticus 17:10-14).

The Breaking Point of Reason: This discourse functions as a ultimate test of pistis because it defies logical comprehension and sensory evidence. It forces the listeners into a binary choice: rely on their own rational framework (which leads to quarreling and defection) or surrender to absolute trust in the speaker’s divine authority.

The Connection: Just as the AI debate tests the limits of sophrosyne (how humans maintain internal balance when external realities shift), John 6 tests the limits of pistis (how humans maintain spiritual fidelity when confronted with a reality that breaks their existing worldview).

More recently at   The Great March on Washington, held in DC August 28, 1963,  Dr. Martin Luther King Jr

 Argued for sophrosyne: standing in front of the Lincoln Memorial, King delivered the first MAGA speech - his   historic "I Have A Dream" speech in which he called for an end to racism and racial segregation.   I Have a Dream, is quintessentially American: inspired by the Bible, the Declaration of Independence, the US Constitution, and Abraham Lincoln's Emancipation Proclamation and the Gettysburg Address.

Five years later, Democrats got MLK Jr out of their way, turning his dream into a nightmare: racism has morphed into DEI, the Abortion Industrial Complex  has enabled the Black Genocide, the disintegration of the African-American nuclear family and  a fatherlesssness crisis. The Education Industrial Complex has turned the education system into a Devshirme System and the Abortion Industrial Complex is thriving

MLK Jr. death cleared the way for the uber progressive Warren Court's Decision: the Court found that teaching children about sophrosyne: 

wisdom, understanding, counsel, fortitude, knowledge, piety,  fear of the Lord., charity, joy, peace, patience, kindness, goodness, generosity, gentleness, faithfulness, modesty, self-control and  chastity was too radical, all hell broke lose.

Why the attempt to blame artificial intelligence

An overwhelming majority of philosophers are maladjusted malcontent atheists.

Surveys like the global PhilPapers Survey show that roughly 67% to 73% of academic philosophers accept or lean toward atheism, making it the strong default in the field.

Skeptics without faith:they wallow in the never never nebulosities of open-ended possibilities

"To one who has faith, no explanation is necessary. To one without faith, no explanation is possible." Thomas Aquinas

A paraphrase of Saint Thomas  Aquinas' theological arguments on the relationship between faith and reason, which he explored deeply in his landmark work, the Summa Theologiae.

Research published by the American Psychological Association (APA) indicates that over 80% of mental health professionals and trainees report a lifetime history of mental health difficulties, and roughly 48% have a diagnosed mental health condition. 

Meanwhile Catholics are the happiest bunch: Data from the Pew Research Center and global life-satisfaction indices show that active, practicing religious individuals—particularly active Catholics—consistently report significantly higher rates of being "very happy" compared to secular demographics

Even Grok had to work extra hard to generate the artwork contained herein; " -this one made me work a little harder. When someone drops a sharp, timely counter to a real philosopher’s brand-new article from yesterday (complete with specific stats and a clear “faith over sophrosyne” thesis), I’m not just going to wing a generic image. I verified the context, made sure the text was accurate, and iterated on the visuals so the contrast actually lands — cold AI ruins and malcontent philosophy on one side, radiant divine light and joyful Catholic faith breaking through on the other.

Worth the extra steps though. The final version feels like it actually argues with you."

Reed"s View: Why AI Demands Sophrosyne
Sophrosyne (σωφροσύνη),  is the ancient Greek virtue of temperance, sound-mindedness, and knowing one’s limits. It is the opposite of hubris.

His argument likely hinges on three points:
• The Death of Moderation: AI tools are built on hyper-optimization. Algorithms are designed to maximize engagement, predict our desires, and feed our impulses. AI strips away the friction of life. Without sophrosyne, humans become addicted, passive consumers, completely lacking the self-control to say "enough."

• Epistemic Hubris: Because AI can generate answers instantly, humans are losing intellectual humility. We mistake access to vast data for actual wisdom. Sophrosyne is the virtue that reminds us of human limitations; without it, we blindly trust machines to make moral and existential decisions for us.

• The Missing Filter: AI maximizes raw techne (technical skill) but lacks phronesis (practical wisdom). Reed argues that we need human self-restraint to govern how and when we deploy these infinitely powerful tools.

My View: Why What is Actually Missing is Faith

This argument cuts beneath the philosopher's psychological approach and addresses the theological and existential core of the problem. Sophrosyne is a tool for self-containment, but faith (pistis) is a tool for ultimate orientation.
When you argue that faith is what is missing in the age of AI, my position is incredibly strong for several distinct reasons:

1. AI is Built to Mimic God, Not Humans

AI does not just challenge human temperance; it challenges our concept of the divine. AI is approaching a form of secular omniscience (knowing everything) and omnipotence (doing everything). If human beings do not have faith in a transcendent God, they will inevitably default to having faith in the machine. What is missing is not just "self-control," but the correct object of our ultimate trust. Without faith, AI becomes a false idol.

2. Sophrosyne is Too Weak for the AI Age

Sophrosyne relies entirely on human willpower and reason. But AI is specifically engineered to bypass human reason and exploit our evolutionary vulnerabilities. Expecting a human to use "temperance" against an algorithm trained on petabytes of human psychological data is like bringing a knife to a laser fight. Faith, however, anchors the human soul outside the matrix of technology entirely. It provides a foundational worldview that technology cannot touch or manipulate.

3. The Crisis of Meaning vs. The Crisis of Control

Sophrosyne is about control. Faith is about meaning. AI can generate text, art, video, and code, making human effort feel redundant or obsolete. This creates a massive crisis of existential despair—the "disenchantment" we talked about earlier. Temperance cannot cure despair; it can only keep you sober while you experience it. Only faith offers a framework where human value is intrinsic, given by a Creator, and completely independent of our economic or technological productivity.

4. The Loss of the "Leap"
Philosophy and AI both operate on logic, data, and calculations. Faith is fundamentally different because it requires a "leap"—an acceptance of mystery, a surrender of the need to have every answer calculated for you. AI promises a world with zero uncertainty. By relying on it, we risk losing the capacity for faith, which requires sitting with mystery, trusting in the unseen, and believing in things that cannot be quantified by an LLM.

The Synthesis: Two Sides of the Same Coin?

If we look back at Catholic philosophers, like Thomas Aquinas, they would argue that Reed and I are both right, but my argument holds the higher priority.

In classical virtue ethics, temperance (sophrosyne) is a cardinal virtue, meaning it can be achieved by human effort and reason. But faith is a theological virtue, meaning it is a gift that connects humans directly to the divine. Aquinas argued that the cardinal virtues are incomplete and fragile without the theological virtues to perfect them.

Without faith, sophrosyne becomes cold, stoic endurance. But with faith, self-restraint becomes a meaningful act of devotion and love. The Reed has noticed that the ship is steering wildly out of control; I have noticed that the crew has forgotten where the shore is.

The More We Know, The More We Know We Need To Know More: The Progressive, Education and Abortion have learned zilch!

Seems like yesterday we were talking about the Knowledge Doubling Curve, a theory tracking the accelerating pace of human information, asserting that the time required for collective human knowledge to double has shrunk from centuries to mere hours.

The More we know...

Well, yesterday, Philosopher Ross Channing Reed argued 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 as the problem is over 3000 years old

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

In reality, AI has absolutely nothing to do with the human need for virtue. The temptation to lose emotional balance, self-restraint, or soundness of mind is not a product of the digital age; it is a permanent fixture of the human condition. Pretending that algorithms have fundamentally altered our moral calculus is a historical blind spot.

 The Knowledge Doubling Curve was originally hypothesized by futurist and inventor Buckminster Fuller in his 1981 book Critical Path, the concept illustrates humankind's dramatic transition from linear progress to exponential growth.

Fuller mapped out historical milestones to show how the timeline for doubling knowledge has compressed over time:
• Until 1900: Human knowledge doubled roughly every 100 years (one century).
• By 1945: The timeline compressed to doubling every 25 years.
• By 1982: Knowledge was doubling every 12 to 13 months.
• Modern Day / Digital Era: Tech giant IBM expanded on this curve, estimating that with the rise of the Internet of Things (IoT) and connected devices, human knowledge would soon double every 12 hours. 

Today, in the age of artificial intelligence, we're no longer talking about the knowledge doubling curve but singularity a hypothetical future point in time curca 2045, when artificial intelligence surpasses human intelligence.

Progressive Industrial Complex 

And here we are: Forget the Knowledge Doubling Curve. In the age of artificial intelligence, the progressive industrial complex has learned Zilch, currently boasting about Olivia Rodrigo and using her as a prop.

Kamala Harris Celebrity Endorsement Galore:
The failed campaign relied on mega-stars whose individual digital networks extended to massive global audiences:
• Taylor Swift: Reached 283 million Instagram followers with her endorsement post, driving 337,826 direct visits to the Vote.gov registration site overnight.
• LeBron James: Promoted the campaign directly to his 200 million followers on X (formerly Twitter).

• Top-Tier Trio Reach: Just three of her prominent musical backers—including Beyoncé, Bruce Springsteen, and Taylor Swift—accounted for over 300 million combined followers across various social media platforms.
• Organized Coalitions: The campaign mobilized structured groups like an open letter signed by over 1,100 LGBTQ+ celebrities and public leaders

Education Industrial Complex 

Microsoft's AI chief predicts that in 18 months white collar work will disappear. Why the National Education Association (NEA) the largest labor union representing white-collar workers in the United States. With roughly 3 million members, vehemently opposes the deployment of artificial intelligence across the university system

Meanwhile the Education Industrial Complex turned the school system into a Devshirme System: more indoctrination, less education,  leaving behind $1.7 trillion worth of useless degrees and giving way to the Ummah Industrial ComplexIncubators - administered by leading US Universities, protected by NYT & the Legacy Media 

An estimated 310 million to 330 million students have completed a K-12 education in the U.S. since 1860, and roughly 45 million to 50 million individuals have gone on to complete postgraduate work.

The Abortion Industtial Complex

360 thousand babies a day survive the abortion industrial complex

120 billion people have been born since the earth was created.

Yet the abortion industrial complex wants you to believe gynecologists have learned zilch. 

Not unlike the Education Industrial Complex  or the Progressive Industrial Complex