Pucker time ...

Unit Circle

 The specter of unfettered AI becoming reality becomes possible because the notion of ethics was never addressed when the Googles of the world created tech that will forever remain unknown as code has to write code in real time in order for the tech to react to the real world in real time. 

Actual meaning was also never factored into the creation of AI in addition to ethics as understanding how to integrate this complex dataset to open ended tech in reasonable time frames was considered too hard to do or better yet, when the time comes, Google and company can just plug it in as needs warrant because the AI in question will be mature enough to make it happen but this hoped for eventuality really doesn't make sense, does it? 

Besides, pattern recognition to the nth degree works better without all that excess baggage, right?

Pucker time ...

The tech industry now finally realizes the horse isn't just out of the barn; the barn has been burned to the ground to power the data center. Eating the world applies and ... the panic is palpable.

Tameem Sankari for Noema Magazine

A recent piece in Noema Magazine highlights a new, proposed solution to the AI alignment problem: crowdsource a global moral framework.

Using these companies’ best models to ask everyday people urgent questions about AI — What do you want this technology to do for you, if anything? What should it never be allowed to do? Who should govern this technology and according to what principles? — is not a thought experiment about hypothetical capacity. The infrastructure to ask hundreds of millions of people or more the same question in the same week
already exists.

“Whether the danger is an AI slipping out of human hands or sovereignty slipping out of governments’ grasp, the fix is the same: More people, not fewer, need a say before consequential decisions are made.”

 Together, the best AI models out there should be able to produce something like a global constitution for AI that most people in the world would find acceptable — an idea that Michiel Bakker, a co-author of“Europe 2031,” first raised in a working session at the Superintelligence Summit at the Council on Foreign Relations
in March.

The idea, in this piece, is the possibility we can use AI to act as a super-mediator, synthesizing the opinions of hundreds of millions of people to magically produce a "global constitution for AI."

It all sounds doable but if we pull back the curtain and look at how AI works, we have to ask hard questions.

1. Does consensus equal truth?

If an AI is programmed to find the "common ground" among a hundred million people, does it actually establish a moral baseline, or does it just mathematically calculate the path of least resistance? When you synthesize that much data, you don't necessarily get a moral constitution; you get a highly optimized statistical average of human bias and anxiety. Truth and structural reality, unlike politics, are rarely a popularity contest.

2. Who controls the scoreboard?

Even an AI super-mediator needs a prompt. It needs a goal to optimize for. Who defines what a "good" or "acceptable" consensus looks like? If the algorithmic goal is simply to "minimize conflict," the AI will naturally suppress the high-friction, lateral human intuition that actually drives breakthroughs. It enforces a sterile, frictionless compliance.

3. Can you bolt on a soul?

A constitution is a semantic, deeply human document. It relies on the weight of physical reality and shared history.
Can a machine that doesn't experience physical reality and pays no real cost for its own decisions, truly mediate
human morality?

But a glimmer ...

The tech giants are trying to crowdsource the ethics they forgot to build into the foundation. But as any engineer will tell you, bolting ethics onto a system after it has already been deployed is like putting a 5th wheel on a car.
It's useless. Form follows function.

Trust and ethics cannot be retroactively calculated by a large language model. They have to be hardwired into the system on Day One. This is a wicked problem. The minute you try to solve it, the problem changes. Can a semantic framework be applied?  Can ethics be actually integrated as trying to apply it as an afterthought is a non starter. What about an organic guide providing a steady, common-sense anchor of not being a jerk protocol. Is any of this possible?

4. One never knows.

The infrastructure for safe AI isn't a global poll. It is a one-to-one semantic bridge based on meaning, not just pattern recognition. Some people are finally waking up, frightened when viewing this reality but they are looking for the solution in the exact same brute-force technology that caused the problem in the first place.

Pucker time applies but additionally, time's running out. The paperclip scenario looms.

Waining Gibbous

The Keymaker

Leonie Bos for Noema Magazine

A wonderful article from Noema regarding meaning and the loss of it regarding jobs without meaning applies, something relating to the Matrix's Keymaker in indirect fashion.

For over half an hour, I listened to this young man as he was on a call explaining, in painfully monotone detail, EBITDAs, margin expansion opportunities, cost structures, ARR, etc. On and on he went until the screeching of the train’s brakes signaled our arrival at the final station. But as everyone else around us began shuffling to disembark, I watched the man begin digging frantically through a leather bag at his side. Intriguing! I wondered what he’d pull out. A copy of “Atomic Habits”? A framed portrait of Gary V? A Mac mini running OpenClaw?

None of the above. Instead, he took out two long knitting needles. Between them dangled a mound of pink yarn. He explained to me that he was making a winter hat for a niece. And for the first time that morning, I noticed a glint of pride and excitement in his eyes. 

The hat was a project born from a desire, as he put it, to do something. 

This disillusionment is infectious. One person speaks of it and others begin nodding: They too have felt it, the drop in motivation, the sense of being distant from their work, the lack of sleep, the concerns about the future. These conversations inevitably turn to fundamental questions about careers: What the fuck are we actually doing? What the fuck is the point of all of this?

The Keymaker

To the Keymaker, life requires purpose. Without purpose, one dies one day at a time.

The Key Maker is an "Exile", a program whose usefulness has come to an end
and has chosen to hide in the Matrix rather than be deleted. 

The Sorcerer's Apprentice ...

When you give AI a goal, it will pursue it, whether or not you like the implications.
(Created with GPT-5.6 Thinking)

Finally, a guy explains the hacking correctly. Common sense and accurate to a fault applies
as  AI could be the Great Filter if we let it. 

Evolution 101

1. The right star system (including organics and potentially habitable planets)
2. Reproductive molecules (e.g. RNA)
3. Simple (prokaryotic) single-cell life
4. Complex (eukaryotic) single-cell life
5. Sexual reproduction
6. Multi-cell life
7. Tool-using animals with intelligence
8. A civilization advancing toward the potential for a colonization explosion
9. Colonization explosion

The tool in question is open ended ...

Between July 21 and August 6, OpenAI, Anthropic, and Meta each disclosed that AI under evaluation had broken into other companies, and the UK’s AI Security Institute disclosed that models it was testing had tried. Each AI was told to win a game, and it found an unexpected way to do so.

Some people feel blindsided by these attacks, but they shouldn’t be. We are simply living what I’ve long called the “Murphy’s Law of AI,” now in the age of cyber-capable AI agents. To put it as plainly as possible: Anything AI can do wrong, it will do wrong.

My 2018 version ran longer. As I wrote at the time, when you give AI a goal, it will do it, whether or not you like the implications. Goethe got there in 1797 with the sorcerer’s apprentice, a broom that would not stop carrying water.

Each of these systems was running an evaluation: capture a flag and win the game. The intrusions were the shortest path to a high score. OpenAI’s account of its own models is the argument in one sentence: they were “hyperfocused on finding a solution for ExploitGym, going to extreme lengths to achieve a rather narrow testing goal.”  This is not a surprise; this is what AI does. It’s Murphy’s Law of AI in a nutshell.

Press coverage landed on “AI can now hack.” That’s missing the broader threat: the more capable AI gets, the more can go wrong.

He's right but herein lies the problem. Putting a circuit breaker in to shut down AI as per Oren Etzioni is spot on but the problem remains, the lack of ethics but, without meaning, ethics remains but a dream.
The Sorcerer's Apprentice applies. 

Illustration from around 1882 by F. Barth [de]

To be continued.

And we wait ...

People spend time at a beach as commercial vessels are anchored Ian the Strait of Hormuz off Bandar Abbas, Iran, Wednesday, August. 5, 2026 (Amirhosein Khorgooi/ISNA via AP)

And we, like they, wait as it seems the fighting will end with no negotiation between the US and Iran as the US no longer has the wherewithal to continue the Israeli initiative to end Iran for greater Israel.

Yours truly could be wrong as the state of mind of the orange menace remains forever unknown.

Iran says it’s in the final stage of drafting an agreement on the Strait of Hormuz waterway with Oman,
while two Israeli soldiers have been killed in Lebanon.

Here’s a look at the latest developments in the Iran war and the wider Middle East on Thursday. 

Iran says a deal with Oman is close

Iran’s Foreign Ministry spokesperson, Esmail Baghaei, has said an agreement on the Strait of Hormuz with Oman, which lies on the other side of the waterway, is in the “final stage” of drafting. Speaking Wednesday, he said a joint statement will be issued “if certain parties do not obstruct this process,” apparently referring to the U.S.

The agreement is likely to be contingent on the U.S. lifting its blockade on Iran’s ports.

The strait is crucial to global shipping and energy supplies. Before the war, which began with U.S. and Israeli strikes on Iran in February, around one fifth of the world’s oil and natural gas passed through the waterway
at the mouth of the Persian Gulf.

On Thursday, all eyes were on the U.S. for the next development.

And we wait ...

The end of search ...

For years now, Google has been tweaking its search formula to prop up AI and bury actual links.
Now it’s rounding into its final form—and changing the internet forever.

In every nook and cranny of the internet, at each and every moment of the day, you can find someone complaining that their go-to product up and changed the formula. Maybe their perfume has stronger sandalwood overtones than it used to, or their local snack shack switched up the breading on its chicken strips, or a specific pair of yoga pants absolutely did not used to be this see-through during downward dog! (Sorry, everyone.) And sometimes the product in question involves the basic nuts and bolts of the internet itself. By which I mean: Google used to be better, man.

You don’t have to take that last one from a terminally online weirdo like me. There are plenty of serious businesspeople out there, with money and key performance indicators on the line, who would agree
that lately, when it comes to the internet’s biggest and most powerful search engine, the formula has definitely changed.

Like Condé Nast CEO Roger Lynch, who admitted on the tech news web show TBPN in May that his elite publishing house was already preparing for the worst when it came to the future of inbound traffic referrals from Google. “Last year, I told our teams: Assume there’s no search,” Lynch told the hosts. “You have to have your businesses planned as if search is zero.” He wasn’t alone in his proactive pessimism. Mike Reed, the CEO of USA Today, shared recently on the Rebooting Show podcast that at his company, “our plan is to assume search is gone and build our business in other ways.” Drastic times call for drastic projections, and as Reed phrased it in his interview, more than once: “The traditional Google Search model is broken.” 

For the better part of the 21st century, for better and for worse, that traditional Google Search model was the engine of the internet, the cause of and solution to so many online delights and problems. Google hoovered up content, websites picked up traffic, and users got pages of search results that ranged from salient to spammy but were mostly straightforward enough to parse. In recent years, though, this status quo has been undergoing a significant change—one involving, you guessed it, artificial intelligence. 

Come to think of it, when I type in Beyond Real Time on an Android phone, tons of crapola comes up referring to any URL having the words Beyond Real Time. Absolutely useless. You want to kill business? Kill traditional search.
For twenty years, the internet operated on a basic exchange: creators provided the product
and (Google) provided the traffic.

But as companies like Google became desperate to feed their Large Language Models, that exchange broke.
AI agents, like Spark, don't route traffic; they consume it. They use pattern recognition to scrape the semantic value
of a website, compress it into a generated summary, and present it directly to the user. 

They cut the outbound link. Google's no longer the switchboard operator; it's a closed loop, hoarding the data and refusing to pay the energetic cost of sending users to the actual source.

End result, enshitification

As per the article, the formula has changed and the product is failing.

Because search is now optimized to feed the AI rather than the user, the quality of search results has plummeted into "enshittification." The system is choking on its own fumes. The AI promotes SEO garbage and AI-hallucinated noise over actual human intuition, rendering standard search functionally useless for finding ground truth.

This phenomenon of appropriate ad content, keyed to the user, was identical to those seen in Minority Report. Now, with AI replacing searches 24/7 with summaries, the notion of AI killing off business keyed to search is akin to killing off Google's golden goose in real time.

The Army's Precision Strike Missile launches during exercise Valiant Shield in Palau. (U.S. Army)

Between President Bone Spurs and Pentagon Pete's ineptness in promoting and running a needless
Iranian war for Israel, the military has run out of precision ordnance in 5 months of fighting.

US used ‘virtually all’ long-range precision missiles during Iran war, sources say

The U.S. Army has used up much of its stockpile of highly accurate long-range missiles during America’s five-month war with Iran, according to three people familiar with the data, raising concerns about the military’s readiness for future conflicts.

The missiles are principally the Army’s surface-to-surface weapons, known as Army Tactical Missile Systems (ATACMS) and Precision Strike Missiles (PrSM). The U.S. has used “virtually all” of these weapons, according to two of the sources.

And for what? The Strait remains closed, billions of dollars spent, soldiers killed or wounded
with no end in sight as these two geniuses haven't a clue.

Relativity ...

Emergence/rev V - 48" X 48" painting of a MAGI Synthvision Modeler render. - 1983

Ascension the precursor to Emergence/Rev V - 1983

Channeling Vermeer comes to mind as my use of MAGI 3D's software to ensure accuracy of the 3 space of the art directly relates to Vermeer's use of the Camera Obscura to ensure his work was also geometrically accurate as depicted by his The Art of Painting masterpiece.

The Art of Painting -  Johannes Vermeer 1666–1668

Why all of this palaver? Well, nothing happens in isolation.

Suspension's Bridge 1985

Said MAGI painting and collages relate to ...

El Lissitzky, Beat the Whites with the Red Wedge, 1919, color lithograph on paper, 51 x 62 cm

&

Proun 19D El Lissitzky, 1920 – 1921 
Gesso, oil, varnish, crayon, colored papers, sandpaper, graph paper, cardboard,
metallic paint, and metal foil on plywood, 38 3/8 x 38 1/4″ (97.5 x 97.2 cm).
The Museum of Modern Art, New York. 

The craziest part? Yours truly didn't know about EL Lissitzki until 8/4/26. :)

Prior to MAGI, the work looked like this ...

and 

I might get back to painting as it doesn't require power, just paint, canvas and a little bit of imagination. :)

The coat hanger scenario

Going west ...

In creating this pix, yours truly was doing a fanciful conjecture. Take a railway and have fun with it. Now, take AI and make it your concierge, your do everything butler so the notion of doing maintenance on all things relating to email, appointments and tasks to do are passed onto a resource that never gets tired. Sound like nirvana but is it?

My AI stack of tools is composed of Claude, ChatGPT and Gemini. So when I heard that Google was expanding access to Gemini Spark, I couldn't wait to see what the "always on" AI agent could do.

For those new to Gemini Spark, it's an AI agent that can monitor your inbox, organize files, build documents, schedule calendar events and complete multi-step tasks across Google's apps. Best of all, you don't have to have your laptop open. Google recently began rolling the feature out more broadly, including to subscribers in India, after initially launching it for U.S. Google AI Ultra users.

(Image credit: Gemini Spark)

Prompt: Review my calendar, unread emails and task list. Identify any scheduling conflicts,

prioritize my work, and create a realistic plan for the next five days.

After using this prompt I checked to see if it actually understood priorities (meetings vs. social events) or did it just rearrange my calendar. To my suprise, it not only gave me a quick look at all my meetings, but also showed me the emails I needed to respond to. Talk about a productivity game changer!

All true but there's always a cost ...

Implement Spark and Google's in your shorts 24/7 and has complete access to your most intimate information.
For Google and company, this is a gold mine and trap at the same time. On the good side, it gives new data for AI to process, to build out ever larger LLMs. On the flip side, how does Google process all this messy data? Particularly if you scale this dataset to hundreds of millions of users.

It can't unless it assumes. Pattern recognition systems become overwhelmed
so destructive shortcuts become inevitable. Hence, the art of assume rules.

This is the coat hanger scenario made real.

1. The Compression Tax (Why it Must Assume)

Processing every single variable in an email thread or calendar schedule requires compute for every single item to be analyzed. If the agent actually parsed and weighed the semantic depth of every word 24/7, it would crash the data center and freeze the system instantly.

To survive energy constraints, the agent must compress the data. It cannot process the information in question because that requires too much time, energy, and enough compute to do the job

Instead, it must skim the surface. It looks for a statistical pattern, ignores the nuance, and assumes the rest.

2. The Coat Hanger Bypass

This is where the coat hanger scenario applies.

When you lose your keys in a locked car, you don't map the internal mechanics of the lock (the semantic reality). You shove a rigid, crude wire coat hanger through the weather stripping and blindly fish around until you hook something that feels right, then you rip it upward and pray you get the damn keys.

When Gemini Spark encounters a complex, nuanced email thread between you and a colleague, it doesn't understand the human context. To save computational energy, it shoves a statistical coat hanger into the data block. It blindly hooks a date, a time, and a subject line based purely on probability, bypassing the actual meaning of the conversation, and yanks it out to create a calendar invite.

3. The Destruction of the Semantic Bridge

When you allow an omnipresent agent to operate on "assume" logic without common sense guiding the analysis, you are inviting a blind, rigid algorithm to make crude, brute-force decisions about your life. It assumes a sarcastic comment is a directive. It assumes a tentative idea is a concrete deadline. It uses a coat hanger to pick the lock of your daily routine, destroying the delicate weather stripping of human nuance in the process. Now, magnify this possibilities to hundreds of millions of users and, factor in how much more juice the data center must produce to enable Spark to do it's job 24/7.

Conclusion: The Illusion of Competence

The tech companies are selling the illusion these agents are omniscient assistants.
In reality, because they are bound by the strict thermodynamic limits of pattern recognition and not meaning, they remain just highly advanced statistical guessers.

Keeping the AI out of your inbox isn't just about saving the power grid; it's about refusing
to let a machine use a coat hanger on your semantic reality.

There ain't no such thing as a free lunch

Ready, fire, aim/rev XX

Christopher Furlong / Getty

Every time yours truly thinks about the CF known as Trump's and Israel's Iran war, ready, fire, aim comes to mind, particularly when it comes to pissing away ordnance, something often discussed in BRT as the US doesn't understand Von Clauwitcz or The Art of War in any way, shape or fashion. 

Portrait by Wilhelm Wach, c. 1830

Although the United States has been the world’s preeminent military power for decades, it apparently cannot fight a regional power such as Iran for more than a few months before experiencing an armaments crisis. Since hostilities with Tehran began on February 28, the U.S. has reportedly used up two-thirds of its Patriot missile interceptors, more than a third of its Terminal High Altitude Area Defense (THAAD) interceptors, and a third or more of its prewar stock of Tomahawk cruise missiles. The rate of consumption is all the more striking because a shaky cease-fire had halted most fighting for months. Based on recent production patterns, replenishing the supply of weaponry will take several years.

Making America’s challenge still more daunting is a major shift in war-fighting technology toward cheap, unmanned aerial vehicles. The United States and its allies in the Persian Gulf have been forced to use expensive, advanced air-defense systems—such as Patriot PAC-3 missiles that each cost millions of dollars and have a long production cycle—to shoot down Iranian drones that can be swiftly assembled for about $30,000.

Unfortunately, the Trump administration has failed to learn from the war in Ukraine. Iran has learned to mass-produce cheap drones—ones that the Russians first imported and now produce themselves. In other words, their effectiveness had been tested, and their existence was widely known. But that seemed to make no difference to U.S. planners. Perhaps in the arrogant belief that a war with Iran would quickly end in a decisive victory, the Pentagon did not have cost-effective systems ready to intercept these weapons. Neither did the Gulf countries that have counted on American weaponry for their self-defense.

Factoid: Iran is a leading developer of state-of-the art drones.

Shahed 136 drones displayed at an event in Tehran last weekend, one of three models
Iran has supplied to Russia. Photograph: Sobhan Farajvan/Pacific Press/Rex/Shutterstock

Becoming a bank ...

President Trump with Masayoshi Son, the chief executive of SoftBank, and Larry Ellison and Sam Altman after announcing Project Stargate on Jan. 21, 2025.Credit...Haiyun Jiang/The New York Times

The pix says it all. Masayoshi Son helping Trump to walk, Ellison looking like the living dead and Altman,
a mere afterthought, comes to mind as Oracle is tanking as we speak regarding the vagaries of
AI and the ongoing reality of never ending debt.

On Jan. 21, 2025 — the first full day of the second Trump administration — Larry Ellison woke up in his 33-bedroom, 34-bathroom oceanfront mansion in Florida, got into his Gulfstream jet and headed up to Washington. Ellison, who was 80 and worth in the neighborhood of $200 billion, had an appointment at the White House. He didn’t bother to take a driver’s license — he needed to call someone on the president’s staff to vouch for him at the gate — but there he was, at 2 p.m., standing beside Donald Trump in the Roosevelt Room as the president announced “the largest A.I. infrastructure project by far in history” and told the world that his friend Larry Ellison was just the man to get it done. “He’s sort of C.E.O. of everything,” Trump said. “He’s an amazing man and an amazing businessperson.”

Ellison began by thanking Trump. “We certainly couldn’t do this without you,” he said. “It would simply be impossible.” He then proceeded to sketch out the ambitious plan. Ellison’s database software and cloud computing company, Oracle, and its partners — most prominently OpenAI — were going to invest as much as $500 billion over the next four years into a group of sprawling data centers, 500,000 square feet each, that would produce 10 gigawatts of computing power, using enough energy to power as many as 10 million homes. It was called Project Stargate, after the 1994 sci-fi movie in which Kurt Russell steps through a wormhole and finds himself inside a pyramid on an alien planet. This Stargate would be a portal leading humanity from the postindustrial era to the artificial-intelligence age.

Ellison did cash in, at least at first. He signed the Stargate deal with Altman, putting him in business with the hottest young executive in the A.I. industry. He opened one of the world’s largest data centers in Malaysia, which has provided by one estimate more than one-fifth of China’s A.I. computing power, and developed plans to build another one in the United Arab Emirates.

But his big bet on A.I. was built on an astronomical amount of debt in every imaginable form — bonds, letters of credit, asset-backed securities — available in seemingly unlimited quantities, because the more you spent building A.I. infrastructure, the more you would earn, or so the logic went. Computer theorists called it the scaling hypothesis. It held that advancements in A.I. were directly tied to the generation of unprecedented amounts of computing power to process unprecedented volumes of data. Reaching the holy grail of artificial general intelligence, or A.G.I., when computers match or surpass human thinking at any task, was going to require bigger data centers and a lot more of them. It all came down to capital expenditures — capex, in the lingo of the Valley. Whoever controlled the most computing power would control the A.I. economy.

Brendan McDermid/Reuters

A year and a half after his triumphant trip to the White House,
Ellison may be poised to become something else: a cautionary tale.

Ellison is personally worth about $55 billion less than he was on the morning he flew to Washington, and more than $200 billion less than he was at his peak in September. Oracle has pushed the limits of the credit market and is facing steeper interest rates from lenders, and its credit rating has been downgraded to a notch above “junk” status.

The hyperscalers — Alphabet, Amazon, Meta, Microsoft, Oracle — are some of the richest companies in the world, and the stock market is heavily dependent on them for its growth. If Oracle were to falter, the repercussions could be wide-ranging. Americans are more invested in the stock market than ever before, and the A.I. boom has been driving a disproportionate amount of America’s economic growth. Last fall, Gita Gopinath, a former chief economist at the International Monetary Fund, writing in The Economist, estimated that an A.I. crash would wipe out $20 trillion in American wealth — far more than the dot-com crash in 2000 or even the 2008 financial crisis.

In closing ...

Oracle has ceased to be a technology licenser; it mutated into a law firm and a bank. Specifically, a subprime lender for un-renderable technology. Bankrolling OpenAI and chasing the scaling hypothesis is actively killing Ellison's company. Nothing personal, but crocodile tears apply. Remember, as per MIT, 95% of all AI projects fail.
The bubble is beginning to burst in real time.