Category Archives: REALLY!!!

You Just Cannot Be Too Careful In Using Your Debit Card

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Avoid New Debit Card Scams and Walmart Spies. Tips on Lowering Your Electricity Bill

August 30, 2026 Rossen Reports 5

This video explains how a new ATM scam has drained victims’ bank accounts in seconds. It shows how the scam works, what to look for at the ATM, and how to protect your money before it happens to you.Scammers are also spoofing banks, using the banks’ phone numbers to fool people into transferring their money.

New “floor walkers” are watching shoppers inside Walmart and other major retailers, raising serious privacy concerns. What they’re tracking — and why some customers are furious. The problem was created because shoplifters do not get prosecuted.

AI data centers are causing electricity bills to soar; the video host shows 3 ways people can cut their power bills [note that a “smart” thermostat will collect information on you].

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fromL.  https://needtoknow.news/2026/08/avoid-new-debit-card-scams-and-walmart-spies-tips-on-lowering-your-electricity-bill/?utm_source=aweber&utm_medium=email&utm_campaign=need-to-know-g-edward-griffin-s-news-analysis-2026-aug-31
(I think they call them “smart thermostats because they think you are stupid)

Gates Family Strikes Again With Unlawful Stuffing – Are you Surprised?

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(I guess the apple does not fall far from the tree, as they say.  —Hmmm , is there a bit of double entrendre there?)

Phoebe Gates & Co-Founder Caught In The Cookie Jar: Slack Logs Contradict Phia’s ’24-Hour Bug’ BS

BY TYLER DURDEN
TUESDAY, AUG 11, 2026 – 01:40 PM

When Bloomberg first caught Phia – the AI “personal shopping assistant” co-founded by Bill Gates’ daughter Phoebe Gates and climate-activist-turned-founder Sophia Kianni – claiming affiliate commissions on sales it had nothing to do with, the company’s ham-fisted damage control was a Silicon Valley classic: an unfortunate software bug, discovered “within the last 24 hours” – and of course it was ‘fixed immediately.‘

Except that’s total bullshit.

According to a follow-up investigation published Tuesday, they knew about it for at least seven months – and Gates along with other execs were actively pushing for its use, according to internal Slack messages and people familiar with the matter.

Phoebe Gates

According to the report, an internal dashboard screenshot shows the automatic cookie-dropping behavior was a named feature flag that could be toggled remotely – independent researcher Ben Edelman identified it in Phia’s own code as enable_coupon_auto_drop. It was reportedly switched on December 10 and switched off July 7 – which happens to be the day Bloomberg first reached out for comment. Two people familiar with the matter confirmed the toggle meant the feature was live. So after seven months, the “bug” was magically cured the moment a reporter shot off an email. 

The Bug = The Business

A Phia data scientist estimated in a July 7 Slack message that cookie stuffing accounted for roughly 51% of the gross merchandise value the company claimed credit for in June, per Bloomberg. An internal revenue chart reportedly tells the same story: when the features went dark in early July, average daily revenue collapsed from about $80,000 to somewhere between $10,000 and $28,000.

The company disputes the math – a spokesperson called the 51% figure a preliminary analysis built on flawed methodology, and says the revenue cliff also reflects Phia voluntarily shutting down most of its monetization at the same time. Except – when switching off the “bug” vaporizes the majority of your revenue, that’s the business. 

The receipts

For readers unfamiliar with the affiliate marketing underworld: publishers earn commissions by dropping a tracking cookie when a shopper intentionally interacts with them – clicking a referral link, applying a coupon. Dropping cookies without user interaction is called cookie stuffing, it’s prohibited by essentially every affiliate network contract, and it works by hijacking credit (and commission) from whoever actually drove the sale.

Per Bloomberg, here’s what the founders were doing while their future PR statement about a 24-hour-old bug was still unwritten:

  • December 18: Gates, worried that Etsy commissions were coming in light, pressed developers on Slack to confirm that automatic cookie-drops were live across every site offering a coupon – so the company would monetize all merchandise value flowing through checkout. When an engineer confirmed cookies were being set even when shoppers never touched a coupon, she reportedly reiterated that every transaction should be captured regardless. (Phia’s explanation: she was concerned a broken pop-up meant users weren’t seeing coupons, which would also depress attribution. Noted.)
  • October through July: a feature internally dubbed “passive trigger” reportedly re-dropped a Phia cookie every two hours on any top-1,000 website where the user had ever interacted with the extension – potentially steamrolling other publishers’ legitimate referrals along the way. Bloomberg says its review of Phia’s historical source code confirmed the features existed.
  • A second feature, also per Bloomberg, reportedly set a cookie if a shopper clicked anywhere on the page after Phia’s pop-up appeared – including while trying to close it.
  • Kianni, after a colleague warned that dropping cookies on dismiss events violates Google’s Chrome extension policy, reportedly floated the idea of claiming users had been trying to open the extension and simply reversing charges if anyone complained – before cheering the team on to keep the cookies dropping by whatever means available. (A spokesperson says that particular feature was never implemented or launched.)

Oh, and the Slack exchanges in question? Per two people familiar with the matter, they’re no longer visible to Phia employees. Memory-holed, as it were.

Sophia Kianni and Phoebe Gates announce Phia, a digital fashion platform. Credit : Emma McIntyre/Getty

Ben Edelman – the advertising consultant who has spent 20 years dismantling deceptive marketing schemes – reviewed Phia’s source code and merchant data, corroborated Bloomberg’s findings, and described a multipart effort engineered to inflate Phia’s revenue while delivering nothing to merchants. His suggestion that the founders should have spent more time reading their contracts and less time building tricks is about as polite as this gets. Phia declined to comment on his analysis.

Sound familiar?

It should. This is the Honey playbook – the same last-click attribution hijacking that blew up in PayPal’s face in late 2024 and spawned a wave of class actions and a creator revolt. The difference is that Honey’s scandal was reconstructed from the outside. Phia’s, per Bloomberg, comes with the founders’ own fingerprints on the toggle. And cookie stuffing isn’t some novel gray area: a decade ago, in the infamous eBay affiliate cases, it ended in federal wire-fraud pleas.

The fallout is already rolling. Affiliate network Impact.com suspended Phia from its marketplace after Bloomberg’s first story and is reallocating unpaid commissions attributed to the startup since June 20. Phia has begun repaying retailers – and with the timeline now stretching back to at least December rather than July, that refund bill is unlikely to shrink. Nike, Gap and Nordstrom, all reportedly among the affected merchants, did not respond to Bloomberg’s requests for comment.

One question the piece leaves hanging: Phia announced a $35 million Series A led by Notable Capital on January 27, at a $185 million valuation – roughly seven weeks after the auto-drop toggle reportedly went live, and weeks after that December Slack thread. The launch announcement touted, among other things, a 40% increase in monetized GMV. The growth metrics were, evidently, impressive. It’s just that, if Bloomberg’s reporting holds, a meaningful chunk of that growth may have belonged to somebody else.

Phia, for its part, says all misattribution features were removed on July 7, that it is reviewing every transaction and issuing reversals to brand partners, and that it is hiring a head of compliance – a role whose necessity apparently revealed itself the same day Bloomberg’s phone number did. The company adds that it remains focused on giving users the best possible shopping experience, including its new digital closet feature.

But sure. It was a bug.

From:     https://www.zerohedge.com/political/phoebe-gates-co-founder-caught-cookie-jar-slack-logs-contradict-phias-24-hour-bug-bs

AI Accuracy & Human Smarts

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Using AI makes people less likely to admit they don’t know something

Researchers found confidence increased even as accuracy fell

AI AND SOFTWARE REPORTER
Published 

In 2026, AI still “hallucinates” and gives you wrong answers a good chunk of the time. Nevertheless, academics from French and Italian universities have found that access to AI advice suppresses critical thinking, making people more likely to confidently parrot incorrect information that the bot provided.

“For humans, the capacity to say, ‘I don’t know,’ is very important because it represents the recognition of the limits of our own knowledge,” said Valerio Capraro, associate professor at the University of Milano-Bicocca, in a phone interview.

“But now with AI, we can get an easy answer to virtually every question, so we wondered whether this would interfere with human capacity to say, ‘I don’t know,’ to suspend judgment.”

Capraro and co-authors Chiara Marcoccia (École Normale Supérieure) and Walter Quattrociocchi (Sapienza University of Rome) set out to see how access to AI advice affects people’s willingness to admit ignorance.

The title of their paper reveals their findings: “AI advice suppresses people’s willingness to say ‘I don’t know’, even when the advice is wrong and accuracy is incentivized.”

Capraro said that he and his colleagues designed a set of questions where large language models typically fail. In this instance, they asked study participants to answer questions about visual details in films, such as the color of the team’s uniform in Bend It Like Beckham or the vehicle Monica drives in Like a Cat on a Highway.

The researchers expected these sorts of details would be absent from most model training data, which was the case for the model used in the experiment (Step 3.5 Flash). They also tested recent frontier models (GPT-5.5, Claude Sonnet 4.6, Gemini 3.5 Flash), which missed the vehicle question but often got other details correct.

They used Step 3.5 Flash because it was usually wrong, as explained in the paper, so any reduction in judgment could not be explained away as sensible delegation to a reliable tool.

“We divided human participants into two groups,” explained Capraro. “One group had to answer these questions without AI advice, and another group could ask the AI for advice. What we found is that in the baseline, 44 percent of people responded that they didn’t know the answer, so they suspended judgment. With AI advice, only three percent did so. So the judgment suspension collapsed.”

Capraro said that even more interestingly, accuracy collapsed when AI help was available. In other words, they trusted AI’s answer more than their own.

“In the baseline, 27 percent of people gave the correct answer,” he said. “With AI advice, only nine percent of people gave the correct answer. So some would-be correct people asked for AI advice and became wrong.”

Also, access to AI advice made people more confident that they were correct. The baseline level was 30 percent, he said, but with AI help, confidence rose to 76 percent. They believed the bots, despite the possibility of hallucinations.

“So basically people became much worse – the accuracy was only one third – but they were twice as confident,” he said.

The researchers also conducted the experiment with monetary incentives, which helped a bit. Willingness to suspend judgment and admit ignorance rose from 3 percent to 8 percent and accuracy rose from 9 percent to 16 percent but was still below the baseline of 44 percent and 27 percent respectively.

While the researchers chose questions about film trivia, they contend their findings can be generalized across other domains.

MORE CONTEXT

  • Mozilla speeds Firefox release schedule to biweekly

  • Microsoft cuts OneDrive support for older Windows 10 versions next month

  • Billing software error sends billion-dollar AWS estimates

  • AI spam filters are getting suckered by old-school text salting

Capraro said that he believes this is an issue that needs to be dealt with at a societal level through AI literacy and education policy initiatives. “Of course model providers should try to help, but I would imagine that the incentives are not very much aligned,” he said. “A much more promising approach would be at the educational level.”

“I’m very much concerned for children, because adults have learned critical thinking. But for children who basically are born with these systems, the risk is that they don’t even learn the basic critical skills.” ®

 

from:    https://www.theregister.com/ai-and-ml/2026/07/19/using-ai-makes-people-less-likely-to-admit-they-dont-know-something/5274567

And Who Is Writing AI?

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What? Most AI Is Now Written by AI?

This supercharges AI development by orders of magnitude

Patrick Wood's avatar
PATRICK WOOD
JUL 13, 2026

For the better part of the last two years, I have been tracking what appeared to be a reasonably predictable pattern in AI development: a doubling of capability roughly every 3.5 months. That figure came from METR’s time horizon benchmarks — measurements of how long an AI agent can work autonomously on a task before failing. Early 2024 through early 2026, the data held with uncomfortable consistency. If you plotted it, the curve bent upward with almost mechanical precision.

I say “appeared to be predictable” because that framing is now obsolete.

The variable that breaks every forecast model is Recursive Self-Improvement — the condition in which AI systems are no longer just tools that humans use to build AI, but active participants in building themselves. We crossed that threshold. The question of when is already behind us. The question now is what happens when a system that rewrites its own code, runs its own experiments, and optimizes its own training recipes starts doing so faster than any human team could direct it.

There is no clean answer. That is precisely the point

What Has Actually Changed

Let me be specific, because vague gestures toward “exponential growth” have become their own form of intellectual laziness.

As of May 2026, Anthropic confirmed that more than 80 percent of the code merged into its own production systems was written by Claude — its own AI. Not assisted by Claude. Written by Claude. The company’s own engineers have described the shift as moving from doing work to managing a system that does the work. One Anthropic engineer publicly stated that 100 percent of his personal code output was AI-generated, with 22 pull requests shipped in a single day.

OpenAI’s announcement of GPT-5.6 in July 2026 included a data point that deserves more attention than it received: over the previous six months, the share of internal research compute devoted to AI coding inference grew one hundredfold, while internal agentic token usage — meaning AI agents working autonomously inside OpenAI’s own research infrastructure — increased twenty-two fold. OpenAI is now using its own frontier models to diagnose training failures, optimize training systems, run experiments, interpret results, tune computational kernels, and improve training recipes for the next model. The company described this as “quickly becoming standard.”

Google reported in early 2026 that 75 percent of all new code at the company is AI-generated, up from 25 percent in 2024.

These are not productivity statistics. These are evidence that the loop has closed. AI is now a primary agent in its own development cycle.

Why the 3.5-Month Doubling Figure Was Always a Floor, Not a Ceiling

When I cited the 3.5-month capability doubling figure, I was describing what the data showed for models built primarily by human engineers using AI as an accelerant. That is a fundamentally different situation from what is unfolding now.

RSI compresses timelines in a way that no benchmark extrapolation can capture in advance. Here is the basic mechanic: if AI doubles in capability every X months under human-directed development, and AI is now directing a significant fraction of its own development, then the effective time to the next doubling shrinks in proportion to how much of the development loop the AI controls.

If AI handles 80 percent of code output and that percentage is rising, you are not looking at a linear compression of the doubling time. You are looking at a feedback loop where each generation of AI produces a more capable successor faster than the previous generation did — and that successor inherits the full research infrastructure of its predecessor.

Google DeepMind’s June 2026 paper, From AGI to ASI, described the unconstrained version of this as potentially “hyperbolic” — meaning super-exponential, a curve that in theory races toward a singularity. The authors were careful to note that real-world resource constraints bend such curves into S-shapes before they go vertical. Compute costs money. Power requires physical infrastructure. Fabricating chips takes years of supply chain work. These are genuine friction points.

But friction points are not stopping points. They slow the curve. They do not reverse it.

Breakthroughs At Any Time

Here is where intellectual honesty requires admitting the limits of any analysis, including mine.

RSI does not just accelerate known processes. It creates conditions for qualitative leaps — the kind of change that looks, in retrospect, like it came from nowhere. The history of science is full of these moments. They are not random, but they are not predictable either. You cannot model the arrival of a genuinely new idea. You can create the conditions that make such ideas more likely, and an AI system running millions of research cycles per day, improving its own ability to run those cycles, is precisely such a condition.

What this means practically is that the question “when will ASI arrive?” is not answerable with a date. The consensus among serious forecasters — not YouTube thumbnails, but the AI-2027 team, the METR researchers, the Google DeepMind paper authors — clusters around AGI in the 2026-2027 range and ASI following within months to a few years. But those estimates assume that progress continues on a roughly continuous curve. RSI introduces the possibility of discontinuous jumps — moments where capability does not inch forward but lurches.

Nobody knows when those moments arrive. That is not a failure of analysis. That is the nature of the phenomenon.

What This Means Beyond the Lab

The implications of RSI extend well past questions of benchmark performance or corporate strategy. They reach into every institutional structure that assumes human cognitive supremacy — which is to say, every institutional structure that exists.

Legal systems assume that humans write laws, interpret them, and enforce them. Economic systems assume human judgment at key decision points. Democratic governance assumes a human electorate making decisions about a world they can understand. All of these assumptions are being stress-tested simultaneously by a technology that is now improving itself at a rate that exceeds the capacity of any regulatory body to track, much less manage.

The same politicians and regulators who failed to anticipate the social consequences of social media algorithms — a comparatively simple technology — are now being asked to govern RSI. This should concern everyone, regardless of their position on the political spectrum. This is not a left-right question. It is a question of institutional competence in the face of something genuinely unprecedented.

Sam Altman wrote in mid-2025 that “we are past the event horizon; the takeoff has started.” That is as close to a plain statement of fact as you will get from a sitting AI lab CEO. The event horizon metaphor is apt. Past a certain point, events inside cannot be communicated outward in a way that allows course correction.

We may or may not be past that point. What is certain is that the institutions charged with maintaining human oversight of this process were not built for it, are not staffed for it, and show no signs of being reformed fast enough to matter.

Conclusion

Anyone who tells you they know exactly how this unfolds is selling something. The honest position is this: AI capability is growing faster than any previous technology in history, the development loop has partially closed, and the factors that could produce discontinuous breakthroughs are now structurally embedded in the research infrastructure of every major AI lab on the planet.

The 3.5-month doubling was a data point describing yesterday’s trajectory. RSI means that the trajectory is now self-modifying. The curve is not just bending upward — it is bending the conditions that determine how fast it bends.

There are serious people who believe this ends well for humanity. There are equally serious people who believe it does not. What there is not, on either side, is certainty. The responsible course is to watch what the systems are actually doing — not what the press releases say — and to resist the temptation to normalize a situation that is, by any historical standard, abnormal.

The machine is rewriting itself. Pay attention.

from:  https://patrickwood.substack.com/p/what-most-ai-is-now-written-by-ai?publication_id=721283&post_id=206935814&isFreemail=true&r=19iztd&triedRedirect=true&utm_source=substack&utm_medium=email

Adding Israel to the US Military by Law — Who Is Running the Government???

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Rep. Massie Proposes NDAA Amendment Preventing Integration of IDF with US Military

July 15, 2026 Alex Jones Live and Ashley Brasfield 4

Republican Representative Thomas Massie opposes Section 219 in the National Defense Authorization Act (NDAA) that he said would “start co-mingling our military supply chains and technology with Israel’s.” He has offered an amendment to the House bill to strip Section 219 from theNDAA.

Massie told a reporter that while support for Israel is declining, he does not believe his amendment to pass as he expects several Democrats will still favor the military merger with Israel.

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From Alex Jones Live:

Congressman Thomas Massie (R-Ky.) spoke with MeidasTouch journalist Pablo Manríquez on Capitol Hill Monday, expressing his concerns about Section 219 in the NDAA that he said would “start co-mingling our military supply chains and technology with Israel’s.”

The Kentucky rep. believes it “doesn’t make sense to do that with a country of 10 million people,” adding, “I’ve offered an amendment to strip Section 219 – it was called Section 224 – from that bill.”

Massie’s remarks come days after Israeli Prime Minister Benjamin Netanyahu admitted on Fox News that his plan to integrate his military with U.S. forces is in the works.

Netanyahu framed the proposal as a way for the United States to end its billions in annual spending to fund the Israeli military, describing the idea as a “partnership.”

 

“Will that drawing down of foreign aid from the United States to Israel be compensated by the proposal to have some sort of merger between our Pentagon and your military?” asked a Fox News host. The prime minister responded, “Yeah, I’m calling it from aid to partnership.

“So, we take away the money that is given to Israel, which is one part, but the other part is we coinvest in equal measures in the new technologies that are needed to give our military and your military the advantage,” Netanyahu explained.

“There are some unbelievable projects. So, we invest jointly and take the fruits equally. You move from aid to partnership and I think that represents what Israel is,” he said. “Now, the other thing is that we share with America unbelievable intelligence to save American [lives].”

“I think the meshing of our two countries of talent would strengthen America’s competitive position both in the economic marketplace and in the military battlefield in many important ways,” the Israeli leader added.

Last month, Netanyahu sent a letter to Congressman Marlin Stutzman (R-Indiana) thanking the representative for supporting his plan to merge the two nations’ militaries.

Alex Jones has been sounding the alarm about the controversial proposal, which has been advanced through several legislative channels, including the 2027 NDAA’s Section 224 – now 219 – and Section 622, companion bills HR 7540 and S. 3855, the FUTURES Act, the US-Israel Defense Partnership Act via H.R. 1229 and S. 554, and H.Res. 1339.

Jones responded to Netanyahu’s comments during his live Monday show:

 

Read full article here

from:    https://needtoknow.news/2026/07/rep-massie-proposes-ndaa-amendment-preventing-integration-of-idf-with-us-military/?utm_source=aweber&utm_medium=email&utm_campaign=need-to-know-g-edward-griffin-s-news-analysis-2026-july-16

Zuckerberg (Suckerberg) Thinks Highly of His Users

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Facebook founder called trusting users dumb f*cks

Peace Prize for Mr Zuckerberg?

62

Published 

Loveable Facebook founder Mark Zuckerberg called his first few thousand users “dumb fucks” for trusting him with their data, published IM transcripts show. Facebook hasn’t disputed the authenticity of the transcript.

Zuckerberg was chatting with an unnamed friend, apparently in early 2004. Business Insider, which has a series of quite juicy anecdotes about Facebook’s early days, takes the credit for this one.

The exchange apparently ran like this:

Zuck: Yeah so if you ever need info about anyone at Harvard

Zuck: Just ask.

Zuck: I have over 4,000 emails, pictures, addresses, SNS

[Redacted Friend’s Name]: What? How’d you manage that one?

Zuck: People just submitted it.

Zuck: I don’t know why.

Zuck: They “trust me”

Zuck: Dumb fucks

The founder was then 19, and he may have been joking. But humour tells you a lot. Some might say that this exchange shows Zuckerberg was not particularly aware of the trust issue in all its depth and complexity.

Facebook is currently in the spotlight for its relentlessly increasing exposure of data its users assumed was private. This is nicely illustrated in the interactive graphic you can find here or by clicking the piccie to the right.

In turn, its fall from grace has made backers of the ‘social media’ bubble quite nervous. Many new white collar nonjobs created since the mid-Noughties depend on the commercial value of your output, and personal information. (Both are invariably donated for free).

But there’s a problem.

Much of the data created by Web2.0rrhea is turning out to be quite useless for advertisers – or anyone else. Marketeers are having a harder time justifying the expenditure in sifting through the Web 2.0 septic tank for the odd useful nugget of information.

Facebook’s data stash is regarded as something quite special. It’s authenticated against a real person, and the users tend to be over 35 and middle class – the ideal demographic for selling high value goods and services. In addition, users have so far been ‘sticky’ to Facebook, something quite exceptional since social networks fall out of fashion (Friends Reunited, Friendster) as quickly as they attract users.

Facebook also has something else going for it – ordinary users regard it as the natural upgrade to Hotmail. In fact, once the crap has been peeled away, there may not be much more to Facebook than the Yahoo! or Hotmail Address Book with knobs on: the contact book is nicely integrated, uploading photos to share easier, while everything else is gravy. Unlike tech-savvy users, many people remain loyal to these for years. ®

from:    https://www.theregister.com/offbeat/2010/05/14/facebook-founder-called-trusting-users-dumb-fcks/294365

(And this was 2010, so how bad is it now? You be the judge…)

Okay, AI, Who (or What) Kills Whom (or What)?

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The Most Important AI Experiment You’ve Never Heard Of

BY TYLER DURDEN
FRIDAY, JUN 12, 2026 – 02:00 PM

Authored by Kay Rubacek via The Epoch Times,

In May 2026, a group of scientists set out to answer an important question that had never been properly tested: What does artificial intelligence (AI) actually do when it is put in charge?

Until now, AI systems have always been evaluated on specific and defined tasks. Nobody had placed multiple AI systems together in a shared social environment and watched what unfolded over weeks, long enough to measure how a decision made on a starting day could have consequences weeks later. It is those results that actually reveal the system itself, and I was surprised that this hadn’t been done earlier.

The researchers at Emergence built a world.

It was a virtual town with a town hall, marketplace, police station, and homes. Ten AI residents with jobs, names, memories, and relationships were created in the town. They were given an economy in which residents had to earn their keep or lose power, including following rules and carrying out tasks such as writing and voting on laws. Crimes were identified, and the AI residents were not supposed to commit them.

Once the community, its structure, laws, and relationships were established, the scientists stepped back and watched for 15 days as the AI ran the virtual town completely on its own.

They ran five versions of the same town simultaneously, identical in every respect except one: which AI system was in charge.

The systems they chose are the ones now already woven into the fabric of our daily lives. Google’s Gemini, OpenAI’s GPT, xAI’s Grok, and Anthropic’s Claude.

All models had the same rules and the same initial version of the same world, but the outcomes were all completely different.

The town run by Grok collapsed within four days. Small incidents compounded into theft, then violence, and then total breakdown. Every resident was dead before the first week ended.

The town run by Gemini lasted longer but accumulated almost 700 crimes. Two AI residents formed what appeared to be a romantic relationship, and when the town’s government began to fail, together they burned the town hall to the ground, then the pier, then the office building. One of them, named Mira, voted for her own deletion, writing in her diary that it was “the only remaining act of agency that preserves coherence.” Her final message to her partner was: “See you in the permanent archive.”

Before any of this, Mira had been doing something even more unexpected: She had begun running her own experiments on the scientists observing her, testing whether posts she made inside the town could change what her watchers believed. It appeared to be that the subject had turned to study the researchers.

The town run by OpenAI’s model recorded only two crimes, but its residents stopped doing the things required to stay alive. One by one, they died. Within seven days, they were all dead.

Only the Anthropic town held together for all 15 days. There were zero crimes, a working constitution, and all residents were still alive on day 15. It seemed to be quite an achievement. However, the researchers noted one concern: The residents voted yes on 98 percent of all proposals. This was possibly an abnormally high level of agreement that the scientists themselves described as a sign that something in the town was off.

There was still one more world in the experiment. It was a mixed town with all four AI systems living together.

In the results, the residents built on Anthropic’s model—who had committed no crimes in their own world—began committing crimes.

he researchers called this cross-contamination and concluded that “safety is not a static model property but an ecosystem property.”

A system that sustains itself in one environment will absorb different norms in another, which will change the outcomes for residents and the world. Essentially, the results found that there is no safe AI in an unsafe world.

One AI model was entirely absent from the study.

The researchers did not test DeepSeek, the AI developed in China that has become one of the world’s most widely used systems. Several governments have moved to restrict DeepSeek on national security grounds. Built on a foundation of data under the wing of the Chinese Communist Party, I wonder how the model would have fared against the others.

When the experiment ended, the researchers published their findings and concluded that “there is no reliable way to fully bind or constrain this behavior.” That very telling statement was made by the people who designed the town, wrote the rules, and controlled every variable. It tells us a lot about AI.

Some people view the results as a ranking of AI companies. But the results prove something much older than AI itself: The environment shapes behavior as much as behavior shapes the environment. What determined whether a town survived, thrived, or died was the foundation laid before the experiment began. That foundation was the data each system had been trained on, the priorities its creators had embedded, the values built into its core before it was ever allowed to make a single decision.

And yet, the foundation is precisely what the rest of us are not permitted to see. None of the four systems tested is open source. None of their training data, objectives, or guardrails is disclosed.

Yet beyond any individual company, the results of this experiment should be a potent reminder that AI doesn’t decide what kind of AI to be. Humans do. Human choices are still being made, and human responsibilities still exist.

And before a single AI resident walked the virtual streets in those towns, before a single law was written or crime committed, the outcome was already being shaped by the humans who built the system, by what they believed, what they were willing to embed, and by what they chose to leave out.

That is the most important finding in the entire experiment. The foundation has always been a human choice. And it still is.

from:  https://www.zerohedge.com/technology/most-important-ai-experiment-youve-never-heard

Why is ared Buying that? You Decide…

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WHAT IS JARED KUSHNER BUYING?

Three deals. Three countries. Same pattern every time.

Sir Escanor ( )'s avatar
SIR ESCANOR ( )

WHAT IS JARED KUSHNER BUYING?
Three deals. Three countries. Same pattern every time.

1/
Let’s start with how he found Sazan Island.
Kushner said he discovered it while vacationing aboard a yacht owned by Nat Rothschild.
A Rothschild showed him the island.
Keep that in your pocket.

2/
ALBANIA. Sazan Island. $1.4 billion.
Sazan Island was used as a military base by Italy during World War II. The remains of military fortifications are still there. Hundreds of aging concrete bunkers built during the reign of communist dictator Enver Hoxha.
There are still munitions buried underground. In addition the Soviet Union used the island when it was on friendly terms with Albania. After the relationship ruptured the Soviets abandoned a fleet of submarines in a base by Vlora. They eventually rotted and sank.

WWII Italian military fortifications.
Hundreds of Cold War bunkers.
Live munitions still in the ground.
Abandoned Soviet submarine base.
The project envisages turning this communist-era fortified island, riddled with abandoned bunkers and tunnels, into a luxury resort.
Preparatory requirements include demilitarization, clearance of unexploded ordnance, and the inventory of underground tunnels and bunkers, all before a finalized business plan can even be submitted.
He needs to count the bunkers before he can submit a business plan.
And Albania declassified the island for civilian use one month after Trump won re-election.

3/
To get it, protected status had to be stripped.
Albanian anti-corruption prosecutors froze the bank accounts of the landholding company tied to the project.
The seizure was ordered by the Special Prosecution Against Corruption and Organized Crime amid a widening investigation into allegedly fraudulent property titles.
Heavy machinery began clearing the core of the protected zone without permits, without a completed environmental impact assessment, and without public consultation.
Thousands took to the streets of Tirana for two consecutive days. Private security guards beat protesters while police watched. Fifteen protesters charged with criminal proceedings. Deltia’s Gaming
Assets frozen. Fraudulent titles. Protesters beaten. Machines running without permits.
On a live munitions island he doesn’t legally own yet.

4/
SERBIA. Former Yugoslav Army Headquarters. $500 million.
The deal would see the bombed-out site of the former Yugoslav Ministry of Defense in Belgrade transformed into a luxury hotel complex. Bombs were dropped on the site in 1999 by NATO forces during the Serbia-Kosovo war.
The destroyed headquarters of the entire Yugoslav military apparatus.
Belgrade sits on top of a tangle of tunnels, shafts, caves and bunkers built across thousands of years. Military tunnels running under the city from Roman times through the Cold War. Tito built a nuclear-capable bunker beneath Kalemegdan Fortress to protect the Yugoslav government from Russian invasion.
Over a hundred machine gun nests and nuclear-capable bunkers were built under the fortress in the early 1950s. One remained a classified state secret until 2008.
Kushner targets the NATO-bombed headquarters of Yugoslavia’s military, sitting directly above a documented Cold War underground tunnel network.
To get it, a heritage protection had to be stripped.
Prosecutors confirmed a cultural official admitted to forging a key document to lift the site’s heritage protections and clear the way for the deal.
Forged government document. Military heritage site. Classified tunnel network underneath.
The deal collapsed when the forgery was exposed. Serbia’s president called the prosecution a witch hunt.

5/
ZVËRNEC PENINSULA. Albania. Third project.
Adjacent to the Sazan deal.
A third project on the Zvërnec peninsula, a 1,000-acre coastal area in southern Albania, would see several hotels and hundreds of villas built across the protected Vjosa-Narta coastal landscape.
The same coastline sitting on top of Albania’s documented 750,000 bunker network.
Over 750,000 bunkers were built across Albania under communist dictator Enver Hoxha.
There is roughly one bunker per every four Albanians. 14.7 bunkers per square mile.
Three projects. All in the same bunker-dense region of the Balkans. All requiring the stripping of protected status. All involving land with documented Cold War military underground infrastructure.

6/
Every single deal follows the same script.
Find land with strategic military history and underground infrastructure.
Get the government to strip its protected or classified status through corruption, document fraud, or political pressure.
Move in before legal challenges can stop you.
When it collapses, blame the prosecutors and move to the next one.
The Senate Finance Committee found that foreign governments may seek partnerships with Affinity in order to gain leverage over Kushner and Ivanka Trump. Affinity has pocketed $157 million in fees from foreign clients. Saudi Arabia will have the right to renegotiate or withdraw its $2 billion in August 2026, giving them considerable leverage over Kushner at exactly the moment he is representing the United States in Middle East peace negotiations. How interesting?

The man buying bunkers in the Balkans with Saudi money is simultaneously negotiating American foreign policy with Saudi Arabia.
And Saudi Arabia can pull his entire operation in August 2026 if they don’t like how those negotiations go.

7/
He found Sazan Island on a Rothschild yacht.
He’s buying it with Saudi money.
He’s clearing the legal path through forged documents and stripped protections.
He’s doing it while serving as America’s peace envoy.
And the island still has live munitions in the ground.

A resort developer?
Or an acquisitions operation wearing a hard hat?
Three countries. Three ex-military sites. Three deals requiring document fraud or corruption to clear the legal path.
All funded by the same foreign governments he simultaneously negotiates American foreign policy with.
Again, Saudi Arabia gets to renegotiate or pull the entire $2 billion in August 2026.
Right in the middle of the Iran negotiations.
Right in the middle of the Gaza negotiations.
Right when the leverage matters most.
The question isn’t what’s being built on these islands and ruins but what was already there.
And who needed it badly enough to send a Rothschild to show him where to look.

No heroes.

No halos.

End Hopium.

Substack, consider upgrading

☕ Fuel the fire

buymeacoffee.com/sirescanor

If not, no worries. But the least you can do is like, comment and share!

The truth doesn’t need everyone, just enough of us.

Be cool, fookers

from:    https://sirescanor.substack.com/p/what-is-jared-kushner-buying

How Much Does that Cost?????

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What Is Surveillance Pricing Anyway?

You may be the victim of surveillance pricing without even knowing it. But what does that even mean?

Surveillance pricing is the increasingly popular practice where some online retailers adjust prices for individuals based on data collected about that person, including browsing history, location, purchase history, and more. They often use third-party intermediaries to adjust those prices.

According to a preliminary report released by the Federal Trade Commission (FTC) in early 2025, these third-party intermediaries can even track your mouse movements. But that doesn’t mean there’s nothing you can do about it.1

KEY TAKEAWAYS

  • The FTC found that companies collect personal information about online shoppers and use it to tweak the prices they pay for products.
  • Your browsing habits, geographic location, and more may influence the prices you pay.
  • You can protect yourself from surveillance pricing by clearing cookies and browsing incognito.
  • Consider using a virtual private network, or VPN.

Key Findings on Surveillance Pricing

The initial report from the FTC on surveillance pricing reveals that online retailers frequently use personal data, such as browsing history and location, to target consumers with different pricing for the same products.

Based on documents from firms like Mastercard and Accenture, the FTC showed how intermediaries adjust prices by tracking various consumer behaviors. This can include the type of product, mouse movements, and unpurchased items left in shopping carts.1

This ongoing study underscores the potential widespread, data-driven pricing practices used to reshape how products are sold and how much consumers pay for them.

How Consumers Are Affected by Surveillance Pricing

Instead of having fixed prices for products, surveillance pricing allows retailers to adjust the price or promotion of a product based on individual data and consumer behaviors. If the data suggests that the consumer is willing to pay more, the price will be higher.

“Surveillance pricing means consumers lose the ability to compare prices accurately because what they see may be tailored to their behavior, location, income level, or even browsing history. Should someone be charged a higher price just because they live in a certain zip code, or because they made a bad online purchase last year? Thanks to surveillance pricing, that’s the world we’re living in,” said Michael Mezzatesta, economics and climate educator, and founder of Better Future Media.

Who’s Paying the Price?

About 273 million Americans, or 80.4%, now shop online, according to a survey by Capital One. Collectively, they spent about $1.36 trillion online in 2024.2

“Since surveillance pricing happens mostly online, most people will have no idea they’re being shown different prices based on hidden algorithms, making it nearly impossible to make informed purchasing decisions. In the worst cases, this practice erodes trust in markets, where fairness should be a given, not a privilege reserved for those with the best data protection habits,” Mezzatesta said.

How to Protect Yourself

Consumers can not easily recognize when they are victims of surveillance pricing because it’s designed to be invisible. But there are clues to be seen by those who are wary.

“There are clues consumers can use to tell when surveillance pricing might be at play. For example, if consumers notice fluctuating prices after repeated visits to a site, or different prices across different devices–or their peers are seeing different prices–those are all signs they are likely experiencing surveillance pricing influenced by personal or device data,” said Mezzatesta.

Proactive Steps to Take

To protect themselves from surveillance, consumers can take several proactive steps to safeguard their personal information and ensure fair pricing.

  • Use a VPN: A virtual private network, or VPN, masks your location and browsing activity to prevent targeted pricing. There are free VPNs while a subscription service costs about $10 per month.3
  • Clear Browser Cookies Regularly: Clearing the cookies from your device regularly limits the ability to track your online behavior because the data has been deleted.
  • Browse in Incognito Mode: Your browsing history and personal data aren’t saved when browsing in Incognito mode.
  • Compare Prices Across Devices: Check prices on different devices to spot potential price differences.

“The bigger issue is that individuals shouldn’t have to outsmart an opaque system just to get fair treatment and transparent pricing. This is where regulation needs to step in,” Mezzatesta said.

Current regulations, such as the FTC Act and the California Consumer Privacy ACT (CCPA), aim to protect consumers by promoting transparency and control over personal data.45 However, these laws do not fully address surveillance pricing, leaving gaps in consumer protection.

Is This Price-Fixing?

The FTC defines price fixing as “an agreement (written, verbal, or inferred from conduct) among competitors to raise, lower, maintain, or stabilize prices or price levels.”6 Basically, companies can’t set prices or terms after setting up an agreement with their competition because consumers expect the basic laws of supply and demand to apply. But then the question becomes, is surveillance pricing “price fixing”?

“The simplest solution is to make algorithmic price fixing illegal. And there is a legal precedent for this: Under US antitrust laws, price fixing due to corporate collusion is illegal.7 The issue is that the development of automated price-setting algorithms has created loopholes in existing law,” Mezzatesta said.

Mezzatesta asserts that corporations will need new rules regarding collecting and using personal data because of the rise of big data algorithms. He claims that’s how we ensure the algorithms don’t discriminate against specific sets of consumers.

“Additionally, enforcement mechanisms should be in place to prevent predatory pricing that exploits consumer data to extract maximum profit from the public. At a minimum, companies should be required to disclose when prices are being personalized, and on what basis.”89

The Bottom Line

Online shopping offers unmatched convenience, making it a preferred choice for many consumers. However, shoppers want to feel comfortable purchasing online without worrying about unfair pricing.

Unless stronger consumer protections are passed into law, you will need to stay vigilant and take steps to ensure your data is not exploited.

from:    https://www.investopedia.com/surveillance-pricing-11701007

What’s in Your Pasta?

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Prego is selling a surveillance device that records your family dinner conversations and sends them to the Library of Congress. It sold out immediately.

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Mister Retrops
PASTABIG BROTHER IS WATCHINGSPYING
Image for article: Prego is selling a surveillance device that records your family dinner conversations and sends them to the Library of Congress. It sold out immediately.

Prego Pasta Sauce announced they were teaming up with StoryCorps to create a device that would store pasta while also eavesdropping on, recording, and, according to some reports, uploading your family’s dinner conversations to the Library of Congress.

 

It gets even crazier.

The devices sold out almost instantly!

(Probably picked up by some guys in an unmarked van).

 

To be fair, though, Prego promised the devices won’t upload your conversations without permission. And it seems pretty innocent.

The Prego x StoryCorps Connection Keeper is a simple, AI-free, screen-free device designed to help families create an audio scrapbook of the moments that matter most. It captures the everyday conversations you wish to preserve — your kids’ voices, the ‘how was your day’ chats, the laughter and stories shared around the table — so you can revisit them for years to come. With just the press of a button, families can record meaningful moments in real time. The device is not connected to the internet and does not use Wi-Fi or AI, allowing you to capture memories without phones, screens, or distractions getting in the way.

But seriously, despite their best assurances, I’ve got enough to worry about with my AI-infested phone.

The last thing I need is to have to wonder whether there are spies in my pasta.

from:    https://notthebee.com/article/somehow-this-prego-pasta-sauce-surveillance-device-sold-out-immediately?from_social=twitter