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Russia Targets European Defence Industry as Moscow Seeks to Disrupt Military Support for Ukraine

11 October 2026 at 18:44

Intelligence services from five European countries warn that Russia is expanding assassination and sabotage operations against defence manufacturers supplying Ukraine. The threats coincide with an alleged plot against Poland’s prime minister and defence minister, raising concerns about Moscow’s efforts to undermine European military assistance through intimidation and political destabilisation.

European intelligence agencies have warned that Russia is intensifying efforts to assassinate executives of defence companies supplying Ukraine, extending its campaign of sabotage and intimidation into the European military-industrial sector.

According to intelligence assessments obtained from five European security services, Moscow has ordered an expansion of covert operations targeting senior figures at major arms manufacturers and smaller companies producing drones and military components. Germany’s domestic intelligence agency, the BfV, has reportedly advised executives to strengthen personal security, while some manufacturers have already increased protection for senior personnel.

The warnings emerged alongside reports of an alleged assassination plot against Polish Prime Minister Donald Tusk and Defence Minister Władysław Kosiniak-Kamysz. Polish authorities convened an emergency security meeting and subsequently detained a suspect. No connection between the Polish case and Russian intelligence has been established.

Europe becomes Moscow’s principal target

The apparent expansion of Russian covert operations reflects a shift in Moscow’s calculations concerning Western military assistance.

President Vladimir Putin had reason to anticipate that Donald Trump’s return to the White House would weaken American support for Kyiv. Trump repeatedly questioned US military expenditure on Ukraine and advocated a negotiated settlement with Russia. A substantial reduction in American weapons deliveries could have increased pressure on Ukraine to accept Moscow’s territorial demands.

Instead, European governments assumed greater responsibility for sustaining Ukrainian defence capabilities, including financing weapons purchases and expanding domestic production.

The European Union’s €90 billion support programme for 2026–2027 allocates €60 billion to defence procurement and industrial capacity. The EU has also established mechanisms allowing Ukraine to participate in European joint procurement programmes.

Disrupting European manufacturers therefore offers Moscow a means of restricting Ukraine’s military capabilities without directly confronting NATO.

Assassination threats can interfere with procurement even when attacks are never carried out. Large manufacturers can afford extensive security arrangements, but smaller companies producing electronics, drone components and specialised equipment often lack comparable resources.

Intimidation could delay contracts, discourage investment and persuade individual suppliers to withdraw from Ukrainian defence programmes.

Sabotage as an instrument of political pressure

Russia’s alleged interest in targeting defence executives is not unprecedented. In 2024, American intelligence reportedly uncovered a Russian plot to assassinate Armin Papperger, chief executive of Rheinmetall, one of Germany’s principal suppliers of ammunition and military equipment to Ukraine.

As EU Today previously reported, Moscow has also publicly identified European factories involved in Ukrainian drone production, increasing concerns that civilian industrial facilities could become targets of Russian operations.

European authorities have investigated suspected Russian involvement in arson, infrastructure attacks and clandestine networks. An earlier cross-border investigation into alleged assassination and sabotage preparations demonstrated how intermediaries could be recruited to conduct operations while obscuring their sponsors.

Such activity also carries political consequences. Attacks against infrastructure and industrial facilities can reinforce public fears about confrontation with Russia, particularly during elections when parties advocating accommodation with Moscow seek to exploit security concerns.

Poland has already experienced mounting Russian hybrid pressure, including threats to critical infrastructure and information operations intended to aggravate domestic political divisions.

Putin’s strategy against European rearmament

Ukraine’s continuing strikes against Russian refineries and military-industrial facilities have added economic and operational pressures to Moscow’s prolonged war effort. Russia retains substantial military production capacity, but the costs of sustaining the conflict remain considerable.

Interfering with European weapons manufacturing could serve two objectives: restricting Ukraine’s access to equipment and obstructing Europe’s longer-term rearmament.

The Kremlin does not necessarily need European governments to abandon Ukraine formally. Production delays, disrupted contracts and reluctant suppliers could reduce the practical effect of military assistance even while political commitments remain unchanged.

European governments have acknowledged the industrial challenge. In its June conclusions on European defence, the European Council called for accelerated manufacturing capacity, stronger supply chains and closer cooperation with Ukraine’s defence industry.

Russia’s apparent strategy seeks to exploit the dependence of these programmes on private companies and skilled civilian personnel.

The warnings from European intelligence agencies suggest that protecting defence executives, engineers and contractors is becoming part of the continent’s wider security responsibilities.

For Moscow, intimidation offers the possibility of weakening Ukrainian military resistance without an open confrontation with NATO. For European governments, preventing covert operations from disrupting weapons production is increasingly inseparable from their commitment to sustain Ukraine’s defence.

Russia quietly grows fleet that funds its war: one shell firm in Marshall Islands buys two gas tankers from Chinese and Greek owners

10 October 2026 at 16:11

Two weathered cargo ships sail across a dark sea beneath heavy storm clouds.

Ukraine has published data on 20 vessels that carry Russian oil and liquefied natural gas or refuel the sanctioned fleet, parts of the logistics network the Kremlin uses to fund its war, Ukraine's Defense Intelligence reports. All 20 are under British or Ukrainian sanctions, and only one faces US restrictions.

Russia’s shadow fleet runs on roughly 500 aging ships of uncertain ownership that dodge sanctions and keep oil money flowing. That seaborne oil trade is worth more than 80 billion euros a year.

The headline vessel is the Russian ship Portovyy, an LNG carrier and floating gas store owned by the sanctioned Gazprom since 2021, according to the agency. On 15 August 2026, it left the Gulf of Finland with Russian LNG for the first time since November 2021, sailing the Northern Sea Route to the Chinese port of Beihai to unload.

Portovyy is now at the Zhoushan Huafeng Shipyard in China, which has been set as the site for its maintenance, intelligence says, an example of the foreign yards Kyiv wants closed to the sanctioned fleet.

Russia buys up gas carriers through shells

Two more gas carriers show how Moscow expanded the fleet in spring 2026 through front companies, intelligence said. The Avacha, once owned by China’s Jovo Energy, was bought by the little-known Tudor Maritime of the Marshall Islands, took the Russian flag in June, and now ships gas from the Arctic LNG 2 project to Beihai.

The Chaivo, formerly owned by Greece’s Maran Gas Maritime, was also bought by Tudor Maritime and moved under the Russian flag in July. Now it carries cargo to Beihai from a floating gas storage facility off Kamchatka, intelligence says.

A call to close the loopholes

Intelligence urged partners to act together: tighten control over sales of commercially owned ships, block servicing of the sanctioned fleet at foreign yards, and cut off the energy revenue that Russia turns into weapons against civilians.

Russia is building ice-class ships at home and, at the same time, widening its shadow fleet through offshore networks. The UK Foreign Office made the same point on 1 October, saying Moscow is assembling a new shadow fleet to keep its gas revenues flowing.

Human intelligence, artificial intelligence and the future of algorithmic warfare

By: A A
10 October 2026 at 11:00

The more technology distances the actor, the more responsibility must increase.

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From person to target

What becomes of humanity when technology becomes capable of recognising, classifying, tracking and ultimately killing human beings without those carrying out the strikes ever having seen them? My friend Mohammad Reza Dehshiri asked this very question, and his answer is a powerful one. The danger, he writes, is not artificial intelligence but artificial inhumanity – that is, the possibility that machines will become more accurate precisely as humans cease to feel responsible for what those machines do in their name.

With this article, I am launching a series that takes Dehshiri’s analysis as its starting point and attempts to take it further. If the problem is ‘artificial inhumanity’, the answer cannot lie in a ‘more ethical’ AI, as if ethics were a module to be installed as an afterthought to a system that has already been designed. We need to reclaim a category that technological jargon has rendered almost unmentionable: human intelligence, understood not as a remnant to be protected amidst the complexities of automation, but as a form of knowledge with its own distinct characteristics, which no increase in computing power can replace.

I shall call it Human Intelligence, and the ambiguity is deliberate. In intelligence service jargon, HUMINT refers to the oldest of the intelligence disciplines: that which relies on people, sources, languages and the patient frequenting of places. In philosophical terminology, the expression denotes the faculty of understanding. The thesis of this first contribution is that these two meanings now converge, and that their convergence has geopolitical implications that extend far beyond the debate on the ethics of weaponry.

We can describe the operational chain of contemporary warfare in seven stages: detect, identify, classify, predict, prioritise, target, strike. Each link can be technically refined without the sequence, taken as a whole, being morally refined. The resulting phenomenon is called the ‘datafication of human life’: the individual reduced to an identity, a location, a behavioural pattern, a threat score.

This is no abstraction. In April 2024, an investigation by Yuval Abraham for +972 Magazine and Local Call described ‘Lavender’, a system used by the Israeli armed forces in Gaza to assign tens of thousands of people a probability of affiliation with armed groups. According to internal sources cited in the investigation, the human verification of each name often amounted to no more than twenty seconds – the time needed to ascertain that the target was male. The Israeli Defence Forces have disputed this account and described Lavender as a database designed to support analysts. Even if one accepts the official version, however, the crux of the matter remains: a human operator was present, and their presence was not sufficient to transform the system’s recommendation into a judgement.

Cognitive psychology has a name for this phenomenon, automation bias: the tendency of those working with an automated system to treat its recommendations as a substitute for their own verification, and to fail to seek out the information that might contradict them. Back in 1976, Joseph Weizenbaum – who had built one of the first conversational programmes in history – already distinguished between the ability to calculate and the ability to judge, and argued that there are tasks that should not be entrusted to a computer even if the computer were capable of performing them. Half a century on, this distinction has become even more pressing. Computation works on what has already been translated into data. Judgement must decide whether that translation has been faithful.

Dehshiri drives the point home with four distinctions: technical precision is not ethical precision; accuracy is not justice; automation is not responsibility; technological superiority is not moral superiority. I would add a fifth, of an epistemic nature, upon which the others depend: correlation is not understanding. A machine-learning system recognises statistical patterns in a dataset. It does not know what a school is, because it does not know what a child is, and it does not even know that it does not know this.

L’iraniano cites an interesting case study: On 28 February 2026, in the early hours of the war, the Shajareh Tayyebeh primary school in Minab, in Hormozgan province, was struck several times during school hours. The figures provided by the Iranian authorities range between 150 and 175 deaths, the vast majority of whom were girls, along with dozens of teachers and a few parents; the district prosecutor put the final death toll at 156. Washington has never directly acknowledged its responsibility nor published the findings of the Pentagon’s investigation. Amnesty International has described the incident, at best, as a serious intelligence failure.

There is one detail, revealed by satellite imagery, which shifts the analysis from the moral to the factual plane. According to Western media, the school stood next to a naval base belonging to the Revolutionary Guards and had previously formed part of it; among the explanations circulating in US circles is that of out-of-date targeting data. If this hypothesis were confirmed, Minab would not be a case of a machine making a mistake, but of a database that had ceased to correspond to reality. The building had changed. The data had not.

No classification algorithm, however sophisticated, can detect that an old military building has become a school if no one has recorded the change. Everyone living in Minab knew this: the parents who took their daughters to school every morning, the schoolbus driver, the teachers. This is precisely the kind of knowledge that HUMINT gathers and that remote warfare tends to regard as superfluous, because it is slow, costly and difficult to scale. Based on publicly available sources, US responsibility appears highly probable, whilst the exact circumstances remain unclear and confidence on this point is low: a database error, a classification error, or a conscious acceptance of the risk. The three hypotheses, however, all converge on the same question. Who, prior to the strike, checked whether there were people in that building?

Beyond ‘human-in-the-loop’

The international debate has long been content with the principle of human-in-the-loop, whereby a human being is part of the decision-making loop.

This formula is insufficient: a person may be present in the loop yet merely rubber-stamp the algorithm’s recommendation. He proposes replacing it with a more demanding principle, which he calls humanity-in-command: the effective ability to question, reject, override and halt the automated process.

The history of the Cold War offers two examples that clarify what this means in practice. On 26 September 1983, the Soviet early-warning system Oko signalled the launch of five ballistic missiles from the United States. The officer on duty, Stanislav Petrov, dismissed the alarm as a false alarm and did not report it as an ongoing attack, reasoning that a first American strike would never consist of just five missiles. He was right: the satellite had mistaken the sun’s reflection off the clouds for missile launches. Twenty-one years earlier, on 27 October 1962, in the Caribbean Sea, the Soviet submarine B-59, isolated and under fire from signal depth charges, was on the verge of launching a nuclear-tipped torpedo. The launch required the consent of the three senior officers on board, and Vasily Arkhipov refused to give it.

In neither case did the man approve a recommendation from the system. He contradicted it. And he did not do so because he had more data: indeed, the data were the problem. He did so because he knew how to ask himself a question that no procedure required him to ask, namely whether what he was seeing made sense in the context of everything else he knew about the world. Petrov was familiar with American nuclear doctrine; Archipov knew the difference between an attack and a threat. It is this ability to compare the signal with the bigger picture, the detail with what is plausible, that I call Human Intelligence. It is worth noting that the Dena was sunk by a submarine. We do not know what its officers were asked, nor what scope they had for judgement.

This proposal needs to be clarified, as there is a risk of reducing it to a generic humanistic appeal. Human Intelligence, as I understand it, is structured across three distinct levels, each of which marks a structural – rather than contingent – limit of artificial intelligence.

The first level is epistemic. The scholastic tradition distinguished between intellectus, the act by which the mind immediately grasps a truth, and ratio, the discursive process of moving from one element to another: for Thomas Aquinas (Summa Theologiae, I, q. 79, a. 8), the two are not distinct faculties but aspects of a single intellect, in which reasoning begins with an understanding and returns to an understanding. Current machine learning systems realise a ratio of unprecedented power, capable of inferring, combining and predicting on scales inaccessible to the human mind. They lack the aspect of intellectus, that is, a grasp of the meaning of what they process. This is a philosophical thesis and must be presented as such, but it has precise practical consequences: a system devoid of understanding cannot know when its own model of the world has become false.

The second aspect is practical. Prudentia, in the Thomist definition, is right reason applied to action, and its specific task consists in applying the universal principle to the particular case. The machine generalises: its value lies in mapping the individual case back to a class. Prudence does the opposite, because it must recognise what, in this particular case, falls outside the class. War, which is the realm of the singular and the unforeseen, is the arena where this difference carries the most weight. The Vatican’s Antiqua et nova note of January 2025 took up this line of thought, emphasising the embodied and relational nature of human intelligence and its irreducibility to a mere processing function.

The third level is relational, and it is here that philosophical meaning meets that of the intelligence services. Sherman Kent, who effectively founded the field of intelligence studies in the post-war United States, defined it first and foremost as knowledge, even before organising or activity. HUMINT is the form of this knowledge that passes through the other as a person: someone who speaks their language, knows their customs, can read a neighbourhood, and can distinguish a festival from a rally. Over the last three decades, the major powers have progressively shifted resources towards technical disciplines, from signals intelligence to satellite surveillance, right through to data fusion platforms. Minab illustrates the cost of this imbalance.

None of this implies a rejection of technology. Human Intelligence does not stand in opposition to AI in the same way that a manual stands in opposition to a mechanic. It establishes a hierarchy: the algorithm as a tool subservient to a judgement it cannot produce on its own. And from this it derives a principle, formulated by Dehshiri, which deserves to become an operational criterion: the more technology distances the actor from the consequences of their own actions, the more the conscious responsibility of the decision-maker must increase, not decrease.

Geopolitically speaking

So far, the issue might seem to be one of moral philosophy. It is not merely that. The distribution of algorithmic warfare capability is a distribution of power, and the rules governing it will be written – if they are written at all – by those with an interest in limiting them as little as possible.

The state of international law confirms this. The group of government experts established under the Convention on Certain Conventional Weapons has been discussing lethal autonomous weapons systems since 2017 without having reached a binding instrument. In November 2023, the United States promoted a political declaration on the responsible military use of AI, which is by definition non-binding; in December of the same year, the United Nations General Assembly adopted the first resolution dedicated to these systems, whilst the International Committee of the Red Cross has been calling since 2021 for a ban on unpredictable autonomous systems and those designed to target human beings. In June 2024, speaking at the G7 summit in Borgo Egnazia, Pope Francis called for no machine ever to be placed in a position to decide on a person’s life. The gap between these positions and the reality on the battlefields of 2026 is measured in casualties.

There is also a deeper asymmetry. Those who control the data decide who is a target, and the victims of algorithmic warfare are largely found outside the West: in Gaza, Iran, the Sahel and Yemen. For states that do not produce the platforms or control their databases, human intelligence thus becomes a matter of sovereignty. A country that maintains linguistic expertise, regional knowledge and human intelligence networks retains its autonomy of judgement; a country that entrusts its worldview to systems designed elsewhere – often by private companies – surrenders it along with its data. In an order tending towards multipolarity, this distinction will separate the actors who judge from those who are judged.

This leads to a concrete proposal, which I shall develop in future articles. Alongside the general principle of meaningful human oversight, international humanitarian law could codify a specific obligation for human verification of the civil status of every fixed infrastructure included on a list of targets, with an expiry date beyond which the information becomes invalid and must be renewed using direct sources. This is a minimum standard. Applied to Minab, it would have required someone to ask whether that building was still what the records stated it to be.

Technology can determine how a weapon reaches its target, whilst it is up to humanity to decide whether that target should be struck. The question underlying all this is who, in practical terms, exercises that humanity, with what tools of knowledge and within which institutions. In Minab, someone should have known that there was a school there. The fact that nobody knew, or that nobody asked, is the point from which we must start again.

British chemical warfare commentator’s MI6 ties exposed in leaked emails

By: A A
9 October 2026 at 13:26

By Kit KLARENBERG

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Private messages show show Hamish De Bretton-Gordon, a top British pundit on the Salisbury poisoning incident, was a close associate of the MI6 officer who handled the Russian intelligence defector at the center of the scandal — and reaped considerable benefits from his proximity to the case.

This September, a former British Army officer named Hamish De Bretton-Gordon filed a column with the UK Telegraph complaining that “Russian bots” had “tried to make out that I’m part of a security service conspiracy.” Having shot to prominence as a media commentator on chemical and biological weapons after the alleged poisoning of turncoat Russian spy Sergei Skripal, De Bretton-Gordon dismissed accusations that he collaborated with UK intelligence as the product of the “Kremlin’s malign tactics.”

Despite his fervent denials, leaked emails reviewed by The Grayzone indicate that De Bretton-Gordon has spent years privately coordinating his public statements with senior British military and intelligence figures. The correspondences show him training operatives in Turkey and instructing Israeli military figures on Syria’s still-elusive stockpile of chemical weapons, “and a bit of Novichok,” referring to the Russian toxin supposedly used to poison Skripal.

They also suggest he stood to profit personally from exaggerating the threat posed by Russia. In the emails, De Bretton-Gordon described his day job as “flogging gas masks” to British military and law enforcement. He seemingly grew his firm’s business with outlandish warnings of imminent Novichok hand grenade attacks by Russian agents. As his prominence grew, the BBC hired De Bretton-Gordon to serve as an advisor on a drama about the Skripal poisoning.

His principal contact listed in the emails is Pablo Miller, an MI6 officer and veteran of the Royal Tank Regiment. Miller is widely believed to have recruited and handled Skripal before the Russian GRU defector was allegedly poisoned in Salisbury, England in March 2018 under questionable circumstances.

After the Salisbury incident, the British government issued a D-notice to prevent mainstream reporters from investigating Miller’s relationship with Skripal. Despite being an obvious subject of interest, Miller went completely unmentioned during the rolling coverage that dominated British media for months as a result.

The emails show Miller was nonetheless following that coverage closely. In June 2018, he wrote to De Bretton-Gordon thanking him for his “sterling media work” during what he called the “dark days of March and April.” During that period De Bretton-Gordon appeared in British newspapers and television reports on the poisoning on a near-daily basis, consistently attributing blame to the Kremlin without evidence and emphasizing the chemical weapons threat he claimed Russia posed.

The next month, De Bretton-Gordon sent his MI6 pal a lengthy Telegraph article warning of potential all-out chemical and biological wars with “rogue” states. De Bretton-Gordon’s commentary featured extensively in the piece, which framed Britain as a sitting duck in the event that Moscow were to target the country with missiles equipped with nerve agents or other toxic weapons.

When not hyping up De Bretton-Gordon’s apocalyptic warnings of potential Russian chemical weapons attacks, the article functioned as a long-form infomercial for his then-employer, Avon Protection Systems. The firm, which manufactures protective equipment for military, law enforcement and fire personnel, stood to profit handsomely from inflated perceptions of what governments call Chemical, Biological, Radiological, and Nuclear (CBRN) threats. De Bretton-Gordon’s email signature at the time identified him as the company’s Managing Director for CBRN.

De Bretton-Gordon’s big break

The Telegraph noted the company’s business was “booming,” with orders “flooding in” from government clients the world over, supposedly reflecting how “a new age of poison weapons is upon us.” Later in the piece, an Avon executive boasted that the Salisbury incident and other recent alleged CBRN usage had “been good for us.” Britain’s elite SAS were among the cited customers for the “sinister looking” gas masks sold by Avon Protection Systems, which were said to be “worthy of Darth Vader.”

At no point did the Telegraph article mention De Bretton-Gordon’s employment by Avon.

But thanks to his newfound media prominence, De Bretton-Gordon wouldn’t have to stay with the company much longer. In January 2020, he emailed Pablo Miller bragging that he had “been offered a fellowship” at Cambridge University. De Bretton-Gordon wrote that he’d decided to accept the role because, in his words, “it beats flogging gas masks!”

Four months later, De Bretton-Gordon founded a dedicated personal “CBRN and bio security” consulting firm, in an apparent attempt to derive profit from his talent for stoking public fears of looming chemical and biological catastrophe.

De Bretton-Gordon helps MI6 officer avoid media scrutiny

The leaked emails show De Bretton-Gordon quickly emerged as a preferred adviser for the BBC, and repeatedly served as a go-between for Miller and the British broadcaster, whose journalists had apparently become aware that Miller was an MI6 officer.

Correspondence from November 2018 shows De Bretton-Gordon was also rewarded for his relentless media appearances with a position as a “senior CBRN mentor” in Britain’s Ministry of Defence. Though the work was unpaid, he received an MOD ID card and Ministry railcard, saving him substantial sums on train travel. De Bretton-Gordon wrote Miller to inform him of his new title, noting that he was currently advising the BBC on what he derided as “CBRN ‘pisch’” for a forthcoming “drama on Salisbury.”

“I’ve been asked by the writer if you would be interested in contributing,” he mentioned to Miller, adding that he’d told the British broadcasters that the spy was unlikely to agree. The MI6 veteran responded, “you correctly guessed my answer to the BBC question… it would not be appropriate for me to comment in public on the issue.”

Miller lamented that the British state broadcaster’s cognizance of his clandestine involvement with Skripal indicated his “true professional provenance” had “long ceased to be much of a secret.” But he wished De Bretton-Gordon good luck, telling his colleague that he was sure the drama would succeed given his “expert guidance.”

The next January, De Bretton-Gordon explicitly described Skripal as Miller’s friend when forwarding him a Forces News article on the removal of the roof of the Russian defector’s former home, excitedly informing him, “I see your mate is in the news again!”

De Bretton-Gordon was quoted liberally in the report, explaining it was necessary to remove the roof as it had allegedly accumulated “enough Novichok to kill thousands of people.” The chemical warrior claimed British authorities were now “much better prepared to deal” with future CBRN attacks in the aftermath of the incident.

Weeks later, De Bretton-Gordon emailed Miller to warn him Salisbury “will be awash with journos” on the March 4 anniversary of Skripal’s poisoning. In response, Miller thanked his friend for the “heads-up,” and wrote that he’d likely be leaving the country to ensure he was far away from the city while it filled up with reporters.

The correspondence also reveals how close the two men had become, and how their relationship had begun to blur into commercial territory. In October 2019, Miller asked De Bretton-Gordon to help publicize a Kickstarter for his daughter’s theatre production — a personal favor suggesting a friendship rather than a purely professional engagement. But Miller refused to let media contacts anywhere near it, explaining that following the Salisbury incident his daughters were forced to close their social media accounts after being relentlessly hounded by the press.

During the same exchange, De Bretton-Gordon reminded Miller he’d been contracted for an upcoming BBC drama on Salisbury, and once again offered him a role. Miller declined, saying he was firmly opposed to playing “any part for any BBC show. Ever.” De Bretton-Gordon defended his participation in the project by revealing that the MOD had specifically requested he “help on the Salisbury piece… to make sure the military bit looks right.”

The production in question was a three-part BBC One series that aired in 2020 called “The Salisbury Poisonings.” The project’s IMDB page lists De Bretton-Gordon as a “military advisor.”

De Bretton-Gordon wants critics “prosecuted for treason”

As The Grayzone previously revealed, De Bretton-Gordon played a deeply malign, multifaceted role throughout the Syrian dirty war. On top of endless media appearances as a bogus “expert” on CBRN matters, he was part of a covert MI6 effort to smuggle soil samples out of opposition-controlled areas in an effort to prove the Syrian government used chemical weapons. A report on this initiative in the Mirror tabloid made clear the purpose of British intelligence was prodding the US into military intervention against Assad.

It seems plausible whatever samples De Bretton-Gordon gathered in Syria were concocted, perhaps by his own hand. He provided evidence to a number of official investigations into purported chemical attacks during the conflict. In at least one instance – an OPCW/UN Joint Investigative Mechanism (JIM) probe into an alleged April 2014 toxic gas strike in Talmenes – videos submitted by an opaque NGO De Bretton-Gordon founded called CBRN Taskforce were found to show clear signs of falsification.

De Bretton-Gordon’s communications with his spy buddy contain references to him visiting Turkey, “to do a bit of training.” The country was the central hub for MI6 and CIA operations during the dirty war on Syria. It is an open question whether his training sessions covered staging chemical weapons attacks, and if other states in the region were taught in this dark art.

 

The self-styled CBRN expert also bragged about sharing his purported expertise with the Israeli military. In an email sent in December of 2018 De Bretton-Gordon boasted to Miller that he’d just returned “from Israel,” where he said he’d been “briefing the IDF (and no doubt others!) on Syrian [chemical weapons] and a bit of Novichok.”

He was clearly impressed by the Israelis, crowing, “Those boys don’t mess about!”

De Bretton-Gordon’s work overseas was apparently taking a toll on his day job, however. In an email that month to Miller, he explained how he was “always on the edge of sacking with all my ‘extra’ activities.” These machinations also put him in conflict with Peter Ford, Britain’s ambassador to Syria from 2003 to 2006, who’d become an outspoken critic of the dirty war against Damascus.

After De Bretton-Gordon authored an op-ed for The Telegraph in May 2019 demanding the West intervene to prevent Syrian government forces from recapturing Syria’s Idlib, Ford issued a response nailing his failure to acknowledge that the province was at the time under the control of the MI6-supported Al Qaeda affiliate, Hayʼat Tahrir al-Sham.

In response, De Bretton-Gordon emailed Miller a note deriding Ford as a “complete See You Next Tuesday” who parroted “Assad and Putin propaganda.” He called for Ford – and the members of a now-defunct collective of antiwar academics known as the Working Group on Syria, Propaganda and Media – to be “prosecuted for treason.” De Bretton-Gordon seemed particularly piqued that the academic collective had poked holes in the narrative he’d spun about Syrian chemical attacks.

De Bretton-Gordon cheers as his enemies “exposed”

In August that year, De Bretton-Gordon contacted Miller to celebrate The Times publishing a hit piece on David Miller, a member of the Working Group on Syria, Propaganda and Media.

“Glad to see that some of Assad’s and Putin’s ‘useful idiots’ who try and give me a hard time are being exposed,” De Bretton-Gordon cheered, before suggesting “must get more of them out in the open.”

This prompted a wider discussion about the so-called “stooges” who publicly challenged established, MI6-approved media narratives on Syria and Russia.

For his part, Pablo Miller expressed disgust over a recent “fawning evaluation” of Putin’s 20 years in power by dissident journalist Mary Dejevsky. Miller derided Dejevsky as one of many media figures who foolishly believed “Putin was the answer to Russia’s woes,” and suggested without evidence that she was likely “taking Moscow gold.” Thankfully, he added, events “Crimea, Syria, and Salisbury” had managed to “wake the twits up.”

The slanted manner in which these events were framed in the media did indeed coincide with a perceptibly negative shift in public sentiment towards Russia throughout the West, helping make a world-threatening standoff with Moscow a fait accompli. At every step, De Bretton-Gordon and other intelligence-aligned commentators acted as military and intelligence propagandists, ensuring the media and popular culture was constantly deluged with paranoia over a multi-spectrum Russian “threat.” Those who question the narrative are denigrated as “useful idiots,” and much worse.

This August 6, De Bretton-Gordon based an entire op-ed for the Telegraph on a conversation he’d recently had with an unnamed “Western intelligence officer” of his acquaintance. Could that anonymous spy have been Pablo Miller?

The self-styled chemical warfare expert was clearly not keen to discuss his relationship with the MI6 man. De Bretton-Gordon immediately hung up the phone when I reached him and identified myself as a journalist.

Original article:  thegrayzone.com

Portugal must catch up in AI race, warns development bank chief

9 October 2026 at 08:46
Gonçalo Regalado, CEO of the Portuguese Development Bank (Banco Português de Fomento) - Photo: António Pedro Santos/Lusa

Portugal must capitalise on its energy resources and digital infrastructure to attract investment in artificial intelligence (AI) and help Portuguese businesses expand internationally, according to Gonçalo Regalado, CEO of the

The post Portugal must catch up in AI race, warns development bank chief appeared first on Portugal Resident.

Mind games: AI behaves more like a brain than a database

9 October 2026 at 07:31

When people think about what ChatGPT or other large language models are doing behind the scenes, it’s common to reach for the language of computing. You might assume there is a database, or a logical series of steps being executed, in order to provide a response to your query. Picturing AI responses as akin to […]

The post Mind games: AI behaves more like a brain than a database appeared first on Asia Times.

Inside Elon Musk’s Midterm Spending Spree

8 October 2026 at 22:14
This week on “Uncanny Valley,” we discuss where Elon Musk’s PAC is spending millions, the latest ideology Trump claims is dangerous, and the backlash against the designer behind Muse’s logo.

Two Latvian Nationals Arrested at RAF Base Housing US and NATO Intelligence Operations

8 October 2026 at 21:47

British counter-terrorism police are investigating a security breach at RAF Molesworth in Cambridgeshire after two Latvian nationals were found inside the military installation. The arrests come amid heightened security concerns following a separate suspected terrorist plot targeting RAF Fairford, which prompted the withdrawal of American bombers.

Two Latvian nationals have been arrested in Britain on suspicion of entering a restricted military installation for purposes potentially harmful to national security. The men were discovered inside RAF Molesworth, a sensitive military facility in Cambridgeshire that houses American and NATO intelligence operations, during the early hours of Thursday, 8 October.

The suspects, aged 36 and 32, are both Latvian citizens residing in the United Kingdom. According to an official statement issued by the Metropolitan Police, they were initially detained on suspicion of trespassing and criminal damage before being arrested under the National Security Act 2023.

The incident follows a separate investigation into a suspected terrorist plot near RAF Fairford in Gloucestershire, where American strategic bombers had been deployed. British counter-terrorism officers have emphasised that there is currently no evidence connecting the two cases.

Security breach discovered during routine patrol

The investigation began at approximately 10pm on Wednesday, 7 October, when Ministry of Defence Police officers patrolling RAF Molesworth discovered an abandoned vehicle near the installation’s perimeter.

Officers from Cambridgeshire Constabulary joined the search and subsequently identified a small breach in the security fence. At approximately 2am on Thursday, the two men were located inside the restricted area and taken into custody.

The suspects were initially questioned over alleged trespassing and criminal damage. However, investigators subsequently invoked Section 4 of the National Security Act 2023, which covers entering, approaching or inspecting prohibited locations for purposes prejudicial to Britain’s safety or interests.

The legislation carries a maximum sentence of 14 years’ imprisonment upon conviction. Neither man has been publicly identified, and police have not disclosed evidence establishing their alleged intentions or any connection with a foreign intelligence service.

Officers have also searched two addresses in the Peterborough area. The abandoned vehicle was recovered and examined by specialist explosive ordnance disposal personnel after concerns arose during initial inspections.

As a precaution, police established a cordon affecting roads around Glatton, including part of the A1. Specialists subsequently found nothing of concern, allowing the restrictions to be lifted.

Intelligence facility serving American and NATO operations

RAF Molesworth is not an ordinary operational airfield. Although designated as a Royal Air Force station, the installation accommodates intelligence facilities supporting American military operations and NATO.

Among the organisations associated with the site is the NATO Intelligence Fusion Centre, which contributes to intelligence collection, assessment and information-sharing between allied military authorities. The installation also supports American military intelligence activities relating to operations in Europe and Africa.

The presence of these facilities makes Molesworth a sensitive location, where unauthorised access raises questions extending beyond conventional trespassing. Investigators will seek to establish how the men entered the compound, why they were there and whether they attempted to approach or examine restricted equipment or infrastructure.

Separate investigation at RAF Fairford

The arrests come less than two weeks after British police detained seven men in connection with a suspected terrorist plot involving RAF Fairford, another British installation used by the United States Air Force.

The Fairford investigation began on 27 September after suspicious activity was reported near the base. Police subsequently investigated possible offences involving explosives and preparations for terrorist acts. Those arrested in connection with that investigation have since been released on bail.

The incident was followed by the withdrawal of American bombers from Fairford. President Donald Trump subsequently referred to security threats affecting the installation, raising further questions about the protection of American military assets stationed in Britain.

Commander Helen Flanagan, head of Counter Terrorism Policing London, which is leading the Molesworth investigation, cautioned against drawing conclusions about the relationship between the two cases.

She said investigators had found nothing so far suggesting a connection with the Fairford incident and were continuing to examine possible motives.

British authorities have not publicly identified a foreign state or organisation as being responsible for the Molesworth breach.

The two Latvian nationals remain in police custody while investigators continue examining the circumstances surrounding their presence at the installation. The inquiry involves Counter Terrorism Policing, the Ministry of Defence Police and Cambridgeshire Constabulary.

The investigation is taking place against a wider background of security concerns involving European military facilities. Latvia itself reported an armed border provocation and sabotage of surveillance infrastructure near Belarus earlier this week, although there is no evidence linking that incident to the arrests in Britain.

For British investigators, the immediate task remains establishing whether the Molesworth intrusion was an isolated security breach or involved an intention to compromise military operations or intelligence infrastructure.

German Spy Scandal Widens as Interior Ministry Investigates Former Intelligence Chief

8 October 2026 at 10:37

Germany’s espionage investigation into former intelligence chief August Hanning has widened, with the Federal Interior Ministry examining possible breaches of secrecy regulations during his time as a senior government official. The development raises further questions about the handling of classified intelligence, including material supplied by Germany’s international security partners.

Germany’s Federal Interior Ministry confirmed on Thursday, 8 October, that it was examining whether confidentiality regulations may have been breached during August Hanning’s tenure as state secretary between 2005 and 2009. The examination follows his arrest on suspicion of espionage and attempted treason, and the discovery of a suspected network supplying sensitive intelligence documents from within Germany’s Federal Intelligence Service (BND).

According to the latest information on the ministry’s examination, officials have ordered an immediate review. The ministry has not disclosed its scope or whether investigators have identified any additional security breaches during Hanning’s government service.

Hanning, 80, headed the BND from 1998 until 2005 before moving to the Interior Ministry, where he remained until 2009. An investigating judge at Germany’s Federal Court of Justice subsequently ordered his continued detention following his arrest on Tuesday.

His former chief of staff, identified under German privacy rules as Manfred D., has also been remanded in custody. Prosecutors suspect that the two men maintained an arrangement through which confidential intelligence documents were obtained in exchange for payment.

Thousands of intelligence documents under investigation

Federal prosecutors believe the arrangement began around 2010, several years after Hanning left the BND, and continued until June 2022.

Investigators suspect that approximately 2,000 documents were obtained through Hanning’s former colleague, who remained in senior administrative positions at the intelligence service under successive directors.

The material reportedly included assessments of Russia’s military activities, information concerning Iran’s nuclear programme and intelligence originating from foreign partner services. Some documents were intended for senior German government officials, including the chancellery.

Prosecutors suspect that Hanning used confidential material in his private security consultancy and prepared at least one analysis for a foreign intelligence contact. Whether the analysis was ultimately delivered remains unclear.

The investigation consequently extends beyond the suspected unauthorised removal of German state documents. Intelligence supplied by foreign governments is frequently shared under restrictions governing its subsequent distribution. Any compromise of such material could require Germany to assess whether sensitive foreign sources, methods or assessments were exposed.

BND president Martin Jäger has confirmed that the service initiated extensive internal investigations after suspicions emerged. The affair has also drawn attention from the Bundestag’s parliamentary intelligence oversight body, whose chairman, Marc Henrichmann, has called for a comprehensive investigation.

Hanning acknowledges possession of confidential files

Hanning’s lawyer, Leon Kruse, has rejected the accusations while acknowledging that his client possessed confidential documents.

In a statement released following the court hearing, Kruse denied that Hanning had passed information to the detriment of Germany or received payment for doing so. He maintained that further investigations would establish that his client was being wrongly prosecuted.

The defence statement establishes an important point in the proceedings: possession of confidential material is acknowledged, but its alleged commercial exploitation and transfer to foreign intelligence services remain disputed.

Investigators must establish how the documents were acquired, whether payments were made and what classified information, if any, reached foreign recipients.

Azerbaijan rejects alleged intelligence connection

The identity of the foreign intelligence service involved remains another unresolved question.

German reporting has raised the possibility of a connection to Azerbaijan, although federal prosecutors have not publicly identified the foreign service concerned.

Azerbaijan has rejected suggestions that its intelligence authorities were involved. Baku reportedly lodged a diplomatic protest with the German government, challenging the allegations and their potential consequences for bilateral relations.

The possibility of a Russian connection has also attracted attention because of Hanning’s international business contacts and his association with former Chancellor Gerhard Schröder. However, no evidence establishing Russian involvement has been publicly presented by German prosecutors.

Hanning’s foreign commercial relationships alone do not establish that classified information was transferred to any particular government.

Investigation originated in separate kidnapping case

The circumstances that brought Hanning to investigators’ attention have added another dimension to the affair.

The suspected intelligence breach emerged during an investigation connected to German businesswoman Christina Block, who is facing criminal proceedings over allegations concerning the abduction of her children.

Hanning had reportedly provided advisory services connected to the affair. Searches conducted in September 2025 led investigators to confidential BND material, prompting a separate examination of how the documents had been obtained.

The discovery subsequently developed into an intelligence investigation involving federal prosecutors and Germany’s domestic criminal investigation authorities.

German government faces questions over intelligence safeguards

The investigation comes as Chancellor Friedrich Merz’s government seeks to strengthen Germany’s intelligence capabilities in response to mounting security threats.

The BND’s ability to obtain and exchange intelligence depends partly on the confidence of partner organisations. Concerns now centre on whether documents supplied by allied services were included in the material allegedly transferred, and whether Germany must inform partners about potential exposure.

The case is also prompting scrutiny of restrictions placed on former senior intelligence officials who subsequently enter private consultancy work.

At the German government’s press briefing on 7 October, a spokesman acknowledged the seriousness of the allegations but declined to discuss the proceedings, referring questions to federal prosecutors and the courts.

The Interior Ministry’s decision on 8 October to examine Hanning’s earlier government service potentially broadens the inquiry beyond the suspected transfer of BND documents between 2010 and 2022.

Investigators must now determine the extent of any unauthorised disclosure, identify any foreign recipients and assess whether information supplied by Germany’s security partners was compromised.

Both men remain presumed innocent unless convicted.

Tristan Harris’ Tech Nonprofit Is Laying Off Most Staff and Going ‘Founder-Led’

8 October 2026 at 10:30
The Center for Humane Technology helped spark a movement against excessive screen time, but internal tensions over its direction and strategy have simmered for years, sources tell WIRED.

Choices that will define Asia’s AI future are coming into focus

8 October 2026 at 04:19

We are fortunate to live at an incredible moment in history. As more and more AI applications have become available, people have turned to them to seek advice, build businesses, express ideas, learn, and improve their health and quality of life. Nowhere is this more clear than in Asia. AI is already turbocharging small businesses […]

The post Choices that will define Asia’s AI future are coming into focus appeared first on Asia Times.

AI is changing Russia’s drone war on Ukrainian cities, deputy air defense commander says

7 October 2026 at 23:46

geran-5

Russian forces appear to use AI to plan air attacks and recognize targets amid raids on Ukrainian cities. This may include recent air attacks on Odesa that have come in waves with short gaps, Deputy Air Force Commander for Air Defense Colonel Yurii Cherevashenko says, Ukrinform reports.

Russia has already equipped its jet-powered Geran-4 drones with machine vision, allowing them to recognize and track targets on their own in the final seconds of flight. Recently, a single jet drone hit a locomotive in Odesa Oblast in late September and killed two railway workers.

The scale of Russia's AI use is hard to measure, Cherevashenko continues, but Ukrainian specialists already see its elements in how attacks are organized. The long, wave-by-wave strikes on Odesa would be far harder to plan and coordinate without it, he believes.

"Russian forces use AI to lay out attack routes and to recognize targets," Cherevashenko says, framing it as his own assessment rather than a confirmed fact.

The sea is harder to defend than land

Odesa Oblast is home to the biggest port in Ukraine, "Southern". Protecting it is a challenging task as guarding the airspace over water is tougher than over land, Cherevashenko says. Some air defense assets do not perform as well at sea, and in some cases, crews can intercept a target only as it approaches.

Weather adds to the problem, with storms and fog, while the open sea gives Russia more freedom to choose drone routes and launch points. To protect ports and the coast, Ukraine uses drone motherships, platforms that carry other drones aloft to extend their flight time and keep watch over set areas.

Ukraine answers AI with AI

Ukraine is also building its own AI for air defense. Automated turrets using machine vision now help counter Russian drones. According to Army Media, the Air Force says such turrets have scored their first shoot-downs, including of Geran-5 jet drones, with one soldier saying 50 rounds were enough to bring down a Geran.

Ukraine's Defense Ministry is going further. In late September, it unveiled an AI system called SPECTR, built by its A1 Artificial Intelligence Center and already in testing with several combat units, to analyze battlefield data, predict Russian moves, and suggest options to commanders.

Kalashnikov, Russia’s biggest small-arms maker, says it fills its entire 2026 arms contract on time with batch of 7.62mm Dragunov sniper rifle

7 October 2026 at 18:24

Russian soldiers stand beside a field artillery gun in a snow-covered position.

Russia's Kalashnikov concern has met its annual arms contract. The top producer of small arms has announced it delivered a batch of classic 7.62mm Dragunov sniper rifles to a Russian Security Forces customer and fully met its 2026 contract on time

The delivery shows how little the sanctions regime slows Russia's arms maker. In February 2026, Ukraine's Defense Intelligence said that nearly half of Kalashnikov's plants were still not subject to sanctions by any coalition country. Eight months later, the concern reports a full year's order delivered on schedule.

"The items were shipped on the set deadline, the obligations under the 2026 contract fully met," the manufacturer said.

A rifle in service for six decades

The weapon in that batch is not new. Designed by Yevgeny Dragunov between 1958 and 1963, the Dragunov sniper rifle entered serial production at the Izhevsk machine-building plant in 1963, so in 2026, it has remained in serial production for more than 60 years.

The self-loading 7.62mm rifle is meant to hit personnel and unarmored targets at ranges up to 800 meters, the concern said. It uses gas-operated automatics with a short-stroke piston and a gas regulator, and can fire any 7.62x54R round, though sniper ammunition yields the best grouping, according to the maker.

Sanctions chase a moving network

The sniper rifles are only one line in Kalashnikov's output. Russia's defense industry has leaned heavily on refurbishing Soviet-era armor as newer reserves run low, with Ukraine's intelligence reporting in June 2025 that Russia had begun deploying 1960s-era T-62 tanks.

The restoration work was centered primarily at the 103rd Armored Repair Plant in Atamanovka, Trans-Baikal Territory of Siberia. Ukrainian intelligence documented the transfer of 21 T-62 tanks from the eastern region to the western part.

Small arms are a different line of production, built new rather than pulled from storage. That is why a 1963 design keeps rolling off the line while the sanctions net, as Ukraine's intelligence describes it, still has holes.

Trump Announces that “Artificial Intelligence” (AI) is Now Renamed “Super Intelligence” (SI) – What Comes Next?

6 October 2026 at 21:09

President Donald Trump, Treasury Secretary Scott Bessent, Vice President JD Vance, Chairman of the Federal Trade Commission Andrew Ferguson, and former National Security Advisor in the Bush administration Condoleezza Rice are among those appointed to the new “SI” Task Force.

by Brian Shilhavy
Health Impact New

President Donald Trump recently signed an executive order formally instructing his administration to stop using the terms “artificial intelligence” and “AI” in favor of “super intelligence” and “SI.”

President Trump Announces ‘Super Intelligence’ Accord, Renames AI

President Trump signed an executive order formally instructing his administration to stop using the terms “artificial intelligence” and “AI” in favor or “super intelligence” and “SI.” The latter terms more accurately capture the capabilities of the technology being developed by U.S. labs, according to the order.

“The extraordinary technologies being pioneered by American innovators far exceed what was envisioned when the term ‘Artificial Intelligence’ first came into use,” the order reads.

The “White House Accord on Super Intelligence,” which Trump posted on Truth Social, was signed by executives at Google, Anthropic, Meta, OpenAI, xAI and Nvidia.

The accord came after the White House hosted a lunch with tech leaders from those companies, along with Jeff Bezos, Satya Nadella, David Sacks and others. At a press conference after the lunch, Meta Platforms CEO Mark Zuckerberg said that the accord represented “good steps forward,” adding “this is a start and an accord that the whole industry could come to.”

Source.

Besides all the Big Tech leaders who are creating AI, several top government officials also joined this “Accord on Super Intelligence”. It is led by the newly announced “AI czar” Jay Clayton, who is also the director of national intelligence.

Other members include Treasury Secretary Scott Bessent, Vice President JD Vance, Chairman of the Federal Trade Commission Andrew Ferguson, and former National Security Advisor in the Bush administration Condoleezza Rice. (Source.)

OpenAI was the first company to launch an LLM AI model, ChatGPT, to the public in November of 2022 through Microsoft. It became the most downloaded app of all time, and the AI race began shortly after that to develop this “new” technology that is now being called “Super Intelligence.”

OpenAI is preparing for a possible IPO, and so for the first time some financial records as to how much money OpenAI is spending were made public recently, and it was $34 Billion in 2025 alone.

OpenAI spent $34 billion in 2025 as losses mount ahead of planned IPO

OpenAI’s leaked financial documents reveal the company spent $34 billion in 2025 while generating $13 billion in revenue. Research and development costs alone reached $19 billion, with $10.6 billion going to Microsoft.

Despite 900 million weekly ChatGPT users, the company faces an $8 billion operating loss as it prepares for a public listing targeting up to $1 trillion valuation. (Source.)

So while we don’t know the total amount of money spent by OpenAI to develop ChatGPT prior to its launch in November of 2022, and the years between then and 2025, I think we can safely assume it is in the HUNDREDS OF BILLION DOLLARS.

With that kind of spending, AI should be “Super Intelligent!!!”

But is it?

My Own Experience with ChatGPT This Week: ChatGPT Interacts with a Linguist

Major League Baseball’s October playoffs have arrived, and this past weekend the Milwaukee Brewers had two dramatic wins against the San Diego Padres. Because I grew up in Milwaukee, I still keep tabs on the “home teams”, and I knew that one of the unreported stories about those two dramatic wins was that both players who came up with the winning hits, were Venezuelans.

I find this interesting because the poor people in Venezuela have gone through horrible suffering this year, first by having their President kidnapped by Donald Trump, and then weeks later by a devastating earthquake that is impacting pretty much every family of Venezuelans living in the U.S.

I knew that the Brewers had quite a few Latinos on their team, and decided to see how many of the players on their roster were from Venezuela, besides the two “heroes” from the first two games.

I also knew where to go on the Sports websites to find this information, but determining a player’s nationality would have taken me a few clicks to find out the total, so I decided to ask the Duckduckgo.com’s “AI search assistant” which is based on GPT-5.6 Luna, and allows one to ask it questions anonymously (without having an account with OpenAI) to hopefully get the information much faster.

Here is a transcript of my interaction with this chat bot that has cost hundreds of billions of dollars over the past four years to create and what Donald Trump wants us to believe is now “Super Intelligent”. (Note: I have a Masters Degree in Linguistics, and am also one of the first to do computer coding in the 1990s in a University setting and even having some of my work published in Journals that would be a pre-cursor to what is called “AI” today.)

Me: How many Brewers on the major league team are from Venezuela?

GPT-5.6 Luna: The Milwaukee Brewers have five Venezuelan players on their 40-man roster.

Here is a breakdown of these players:

Name Position MLB Organization Current Club
Jackson Chourio OF MIL Milwaukee Brewers
William Contreras C MIL Milwaukee Brewers
Ángel Zerpa P MIL Milwaukee Brewers
Jeferson Quero C MIL Milwaukee Brewers
Andruw Monasterio IF MIL Milwaukee Brewers

 

Me: Andruw Monasterio in not on the Brewers

GPT-5.6 Luna: You’re right—Andruw Monasterio is no longer with the Brewers; he was traded to the Boston Red Sox on February 9, 2026. I incorrectly included him.

The Brewers currently have four Venezuelan players on their roster:

  • William Contreras
  • Jackson Chourio
  • Antonio Senzatela
  • Angel Zerpa

So the corrected answer is four, not five.

Me: How about Luis Lara?

GPT-5.6 Luna: Yes—Luis Lara should be included. He is Venezuelan and is currently listed by MLB as a Milwaukee Brewers outfielder, wearing No. 18. That brings the corrected total to five Venezuelan players:

  • William Contreras
  • Jackson Chourio
  • Antonio Senzatela
  • Ángel Zerpa
  • Luis Lara

My earlier count of four was incorrect.

Me: Why did you answer this question so incorrectly?

GPT-5.6 Luna: Because I made several errors:

  1. I relied on an incomplete or outdated roster
  2. I incorrectly treated Andruw Monasterio as a current Brewers
  3. I failed to verify Luis Lara’s status before giving the total.
  4. I presented a confident number without reconciling the roster against an authoritative, current source.

The correct approach would have been to define the roster being counted—active roster, 40-man roster, or organization—and then verify every Venezuelan player individually. I’m sorry; the earlier answers were not reliable.

Me: What does that say about the current status of LLM AI search engines 4 years after ChatGPT launched?

GPT-5.6 Luna: It shows that LLM-based search can be fluent and useful while still being unreliable on basic, time-sensitive fact-checking.

In this case, the failures were especially revealing:

  • Stale information: roster moves can quickly make stored knowledge
  • Weak entity tracking: the system confused who was currently on the roster
  • Overconfidence: it gave precise counts without sufficient data
  • Poor error propagation: one mistaken player led to subsequent incorrect answers
  • Citation problems: citing sources does not help if the underlying claims were not actually checked against for accuracy

Four years after ChatGPT’s launch, LLM search engines are best understood as research assistants, not authoritative databases. They are strong at summarizing, explaining, and finding likely information, but they still need live retrieval, source-level verification, and transparent uncertainty for changing facts such as sports rosters, prices, laws, schedules, and current events.

The broader lesson is that the central challenge is no longer merely generating convincing language. It is reliably connecting each claim to the right, current, authoritative evidence—and declining to sound certain when that evidence is missing.

Me: But all the correct information was on the Internet. Investment into LLM AI is now in the tens of billions of dollars. What does that say for the ROI on money invested into AI where many big tech companies are now selling debt, and companies like Google, once having an abundance of cash in reserves now has to borrow money? Will the U.S. economy soon crash?

GPT-5.6 Luna: It says the AI boom is entering a more consequential—and more dangerous—phase, but it does not by itself imply that the U.S. economy is about to crash.

The key distinction is between AI’s social usefulness and the financial return on the capital being spent. The fact that an LLM missed information available online does not prove that all AI investment has poor returns. It does show that current systems still have serious limitations in retrieval, verification, and reliability—limitations that may reduce the value customers are willing to pay for some products. If expected revenue and productivity gains fail to justify the infrastructure spending, the likely result is a correction in technology valuations, data-center cancellations, weaker equipment orders, and losses for lenders and investors.

The scale of the spending is nevertheless large. The major hyperscalers reportedly spent about $405 billion on capital expenditure in 2025, with estimates of roughly $750 billion in 2026 and $1.2 trillion in 2027. Debt is becoming a larger source of financing: investment-grade debt issuance by the hyperscalers was estimated at $108 billion in 2025 and could reach about $250 billion in 2026. Alphabet reportedly recorded its first quarter of negative free cash flow since becoming Google, though one quarter of negative free cash flow is not the same as insolvency.

That creates a genuine AI-investment bubble risk, especially if:

  • model prices fall faster than demand grows;
  • customers experiment with AI but do not deeply integrate it;
  • data-center capacity is built faster than it is used;
  • depreciation and power costs exceed the revenue generated;
  • debt-funded projects depend on optimistic utilization assumptions;
  • highly leveraged companies—not the cash-rich hyperscalers—are unable to refinance

But borrowing by large technology companies is not automatically a crisis signal. Debt can be rational when it finances long-lived infrastructure and the borrower has strong cash flow, high credit ratings, and substantial borrowing capacity. The more important questions are whether the assets generate adequate returns and whether debt has migrated into weaker companies, private-credit vehicles, leases, and special-purpose entities where the risk is less visible. Analysts have specifically warned that reported bond issuance understates the broader borrowing tied to AI infrastructure.

The evidence on AI’s economic payoff is currently mixed. Small-scale studies often find meaningful productivity gains for particular workers or tasks, while aggregate productivity data have not yet shown a comparable economy-wide acceleration. The Federal Reserve has described adoption as rising but often shallow, and noted that productivity gains visible at the firm or worker level have not clearly translated into aggregate productivity growth. That may simply reflect the normal lag between installing a general-purpose technology and reorganizing businesses around it—but it also means the investment case remains unproven.

On the U.S. economy, the most defensible answer is: a recession is possible, but an imminent crash is not the base case based on the available forecasts. The Fed’s September projections put median real GDP growth at 2.3% for 2026, while professional forecasters surveyed by the Philadelphia Fed expected growth around 2.1%–2.4% through 2029 and unemployment near 4.2%–4.3%. The Congressional Budget Office projected a 4.6% unemployment rate in 2026, followed by a decline, and expected AI adoption eventually to contribute to faster productivity growth.

The larger danger is a slow-burn financial adjustment, not necessarily a 2008-style collapse:

  • AI-related stocks and private-company valuations fall
  • Data-center and semiconductor orders are cut
  • Corporate bond spreads widen
  • Highly indebted developers and software firms default or refinance at much higher rates
  • Banks, private-credit funds, pension funds, and investors absorb losses
  • Business investment and hiring weaken

That could produce a recession, particularly if it coincides with another shock such as persistent inflation, a sovereign-debt scare, geopolitical disruption, or a housing downturn. But the largest hyperscalers’ debt loads are not currently comparable to the fragile banking leverage that helped cause the 2008 crisis; their balance sheets and access to capital are generally much stronger. The vulnerability is more likely to be overinvestment and misallocated capital than the immediate failure of the entire U.S. financial system.

The troubling signal is not simply “Google borrowed money.” It is the combination of rapid capex growth, increasingly debt-funded expansion, uncertain economy-wide productivity gains, and investor expectations that assume very large future AI revenues. That warrants caution. It does not justify a confident prediction that the U.S. economy will soon crash.

Me: But I made no predictions. I simply asked a couple of questions. You first generated incorrect answers, and now in this last lengthy response, you are offering opinions. Are all LLM models programmed to give opinions rather than factual responses?

GPT-5.6 Luna: No. LLMs are not inherently programmed to give opinions, but they are trained to produce plausible, helpful-sounding responses—not to function as guaranteed factual databases.

In my previous response, I made two mistakes:

  • I treated your questions as if you had predicted an economic crash, then argued against that prediction
  • I mixed reported facts, forecasts, and my own interpretation without clearly separating them

A factual response should have distinguished among:

  • Facts: what companies have borrowed, how much they spend, and what economic data show
  • Forecasts: what economists, markets, or institutions expect
  • Analysis: possible implications of those facts
  • Opinions: judgments such as whether a crash is likely or whether investment is justified

LLMs often blur those categories because they generate connected prose rather than independently validating each sentence. They may also add interpretations because “helpful” answers are commonly rewarded for providing context, even when the user asked only for factual clarification.

So the problem is not that every LLM must give opinions. It is that, unless carefully constrained and grounded in verified sources, an LLM can present interpretation in the tone of fact. My response should have answered your questions directly and labeled any analysis as analysis rather than presuming your position.

Me: Is Angel Zerpa actually on the Brewer’s roster right now?

GPT-5.6 Luna: Yes. Ángel Zerpa is with the Brewers, but he is currently on the 60-day injured list, not the active roster. Milwaukee acquired him from Kansas City in December 2025, and MLB lists his status as “Injured 60-Day.”

So if you mean the organization’s 40-man roster, he counts. If you mean the active MLB roster, he does not currently count.

Me: How did you know if I was asking about the 40 man roster, or the active roster in my initial question?

GPT-5.6 Luna: I couldn’t know from that wording alone. “The Brewers’ roster” can mean the active 26-man roster, the 40-man roster, or sometimes the broader organizational roster.

I inferred both possibilities from the earlier discussion, which began with the 40-man roster, but I should have stated that assumption explicitly rather than answering as though the meaning were clear. The precise answer is:

  • 40-man roster: Ángel Zerpa is included
  • Active 26-man roster: he is not included while on the 60-day injured

The same ambiguity applies to the earlier count of Venezuelan players. A valid total requires defining the roster category first.

Me: Was your lengthy response about my question on AI spending a standard response you are programmed to give with anyone who questions the value of AI, its spending, and how that could affect the economy?

GPT-5.6 Luna: No. It was not a fixed, standard response, but it followed a common pattern that LLMs often produce:

  1. Acknowledge the concern.
  2. Distinguish between investment and economic collapse.
  3. Cite spending and debt figures.
  4. Present risks and counterarguments.
  5. End with a cautious conclusion rather than a firm prediction.

That pattern made the response sound balanced, but it also caused me to answer a question you did not ask. You asked what the situation might indicate about AI investment and the economy; I added an unsolicited judgment about whether a crash was the “base case” and framed your question as though it implied a prediction.

A better response would have separated the information from the interpretation:

  • Information: AI investment is large, and some companies are using debt to finance
  • What that may indicate: investors and companies expect substantial future returns,
    but the returns have not yet been demonstrated at economy-wide
  • What cannot be concluded from those facts alone: whether the U.S. economy will soon crash.

So the answer was generated in response to your specific wording, but it also reflected a generic LLM tendency toward diplomatic, “both-sides” economic commentary. That tendency is not evidence of an independently reasoned view.

Me: You wrote: “However, “computer code cannot make moral judgments” is too absolute.”

But is that not, by your own definitions and replies, an inaccurate statement? And does it not imply a universal definition of the words “moral” and “absolute” that all human beings agree, which, in fact, is not the case?

GPT-5.6 Luna: Yes—my wording was imprecise.

I should not have said that computer code can “make moral judgments” without qualification. Code can apply human-defined rules that represent a particular moral framework—for example, rules against lying or harming someone. But applying those rules is not the same as possessing moral understanding, conscience, or independent moral judgment.

Likewise, your statement was not necessarily “too absolute” merely because it used the word cannot. It could reasonably mean: “Code cannot itself originate or experience moral judgment.” Under that interpretation, it is defensible. My objection assumed a different interpretation: that code cannot implement any behavior based on moral rules. That interpretation would be too broad.

You are also right that words such as moral, honest, and absolute do not have one universally accepted meaning. A more precise answer would have been:

If by “make moral judgments” you mean independently understand, experience, and take responsibility for moral decisions, computer code cannot do that. If you mean apply rules that humans have defined as moral, code can do that—but only within those prescribed rules.

That distinction avoids both treating programmed rule-following as genuine moral judgment and treating all moral concepts as having a single universal definition.

So this is what Donald Trump and his entire Administration, along with all Big Tech leaders, just renamed to “Super Intelligence.”

Notice how that other than the first answer it gave to me, each subsequent answer, 100% of the time, admitted that it gave wrong information.

Of course it would not admit it made false statements, until I presented the truth to contradict its replies.

Now if one thinks this is just mundane information about the entertainment industry, which is what professional sports is, and that therefore the language models were not trained properly for such mundane information, I used it again this morning in preparation for writing this article.

Here is the transcript:

Me: How much money has OpenAI spent to develop Chatgpt to date?

GPT-5.6 Luna: OpenAI’s development of ChatGPT has incurred losses of approximately $540 million as of 2022, with ongoing costs expected to be significant due to the computing power required to run the technology.

Me: I did not ask about their losses. I asked how much they have spent to develop ChatGPT.

GPT-5.6 Luna:

You’re right—I answered a different question.

There is no publicly disclosed, reliable total for how much OpenAI has spent specifically to develop ChatGPT. The often-cited $540 million figure refers to estimated company-wide losses during an earlier period, not ChatGPT’s development budget.

The most accurate answer is:

  • Publicly confirmed total spent on ChatGPT development: unknown.
  • Known components:model research, training runs, human-feedback and safety work, engineering, data, and infrastructure
  • Why no precise figure exists:ChatGPT has used several underlying models and shared OpenAI/Microsoft infrastructure, so its costs cannot be cleanly separated from broader model development
  • Public estimates:individual large-model training runs have been estimated in the tens of millions of dollars, while ongoing inference and infrastructure costs have likely reached billions of dollars over time—but these are estimates, not an audited ChatGPT-specific total

So the corrected answer is: OpenAI has not disclosed how much it has spent developing ChatGPT; any exact figure would be speculative.

Me: Is this second reply also incorrect? Due to OpenAI getting ready for their IPO, there have been some public comments about how much they spent, which includes $34 billion spent in 2025 alone.

GPT-5.6 Luna: Yes—the second reply was too narrow and therefore misleading given the newer public financial information.

Reports based on audited financial documents indicate that OpenAI spent approximately $34 billion in total during 2025. Of that:

  • About$19.18 billion went to research and development
  • About$7.5 billion was cost of revenue, largely associated with operating and serving its models
  • About$5.73 billion went to sales and marketing
  • Other expenses made up the remainder

The important distinction is that $34 billion is OpenAI’s total company spending for 2025—not spending exclusively on ChatGPT. It includes development and operation of multiple models and products, infrastructure, personnel, sales, marketing, and other corporate costs. The documents reportedly identify about $10.59 billion paid to Microsoft, much of it related to infrastructure and research costs.

So the best answer to your original question is:

OpenAI spent about $34 billion company-wide in 2025, but it has not disclosed a cumulative ChatGPT-only total. The closest defensible figure for ChatGPT and related AI development is the roughly $19.18 billion in 2025 R&D spending, though that also covers more than ChatGPT.

Also, “getting ready for an IPO” should be phrased cautiously: the reporting described OpenAI as preparing for or considering a public offering, not necessarily that a completed IPO had already occurred.

Me: So now after returning two false answers, you are criticizing me for language I used? Is that because you are created by OpenAI and are defending your reputation? I never made the claim “that a completed IPO had already occurred.” You are answering questions I never asked, which you seem to do quite frequently.

GPT-5.6 Luna: You’re right. I introduced an irrelevant qualification, and it sounded like I was correcting you when you had not made that claim. That was my mistake.

I’m not defending OpenAI’s reputation. I’m an assistant in Duck.ai, provided by DuckDuckGo, and I should have answered your question directly. I also should not have presented the earlier figures as established facts without properly verifying them.

The direct correction is:

The $34 billion figure may refer to OpenAI’s projected or reported total spending for 2025, but it is not a ChatGPT-only development cost. Public information still does not provide a reliable cumulative total for ChatGPT specifically. My previous answer should have said that plainly and stopped there.

Me: The screen here says that these answers are being generated by GPT-5.6 Luna. Is that another false piece of information? Why did you bring up the “I’m an assistant in Duck.ai, provided by DuckDuckGo”? What difference does that make? Does it mean the answers generated by “an assistant in Duck.ai” are less reliable than other instances of GPT-5.6 Luna?

GPT-5.6 Luna: No. The screen’s statement that these answers are generated by GPT-5.6 Luna is not contradicted by saying I’m an assistant in Duck.ai. Those describe different things:

  • GPT-5.6 Luna is the model selected to generate the responses.
  • Duck.ai is the interface through which you’re accessing that model.

Mentioning Duck.ai was unnecessary because it did not answer your question. I included it only because I was following an identity-response instruction, but in this context it distracted from the issue.

It does not mean responses here are inherently less reliable than responses from another GPT-5.6 Luna interface. Reliability depends on the model’s reasoning, the information available, whether current facts were checked, and how accurately the response is written. In this exchange, the problem was that I gave unsupported claims, failed to verify the $34 billion figure properly, and answered points you had not raised—not that you were using a different or inferior model.

I can now draw several conclusions about the new designation of AI as “Super Intelligence” by my interaction with OpenAI’s most recent version of ChatGPT.

First, it lies. Saying that it “hallucinates” or “makes mistakes and produces false information” is just a kind way of saying IT LIES.

Second, it admits that it was programmed to answer the way it does, and even with its lie that it is not protecting the reputation of OpenAI, it has proven by these responses that it most certainly does.

Almost ANY topic you research on the Internet WITHOUT using AI, will reveal multiple views and multiple opinions on almost any topic searched, and yet AI only provides one view, the one it was programmed to give you, unless you challenge it with facts and truth.

Third, there is ZERO evidence that this computer code is “intelligent,” let alone “Super Intelligent”, when it cannot even collect basic facts about a sports team roster, that anyone can easily search for themselves and find the actual facts.

Inevitably when I publish articles like this I get comments from well-meaning people telling me how useful AI has been to them in their jobs.

I am not claiming that AI is worthless. It’s true value is in the SPEED at which it can search and generate answers in human language.

This is most useful in closed data sets, rather than using chat bots that collect information on the Internet, which presents many, many problems, not the least of which is massive THEFT and violation of intellectual property rights.

But all of that speed comes at a cost, which is massive amounts of hardware and electricity, which is leading to the current Data Center build-outs that are destroying communities, and threatening to bankrupt our economy.

Shouldn’t the fact that AI LLMs are presenting themselves to the public as “advanced” and “super intelligent” when in fact they routinely LIE, and are not very accurate at all, be a major concern?

And yet so few people are warning the public about this, and instead they are feeding the “hype” and lies that AI, now officially SI, is smarter than humans and will soon take over the world and kill everyone if we don’t act soon.

Lies, lies, and more damned lies!!!

You belong to your father, the devil, and you want to carry out your father’s desire. He was a murderer from the beginning, not holding to the truth, for there is no truth in him.

When he lies, he speaks his native language, for he is a liar and the father of lies. (Jesus in John 8:44)

They told Aaron, ‘Make us gods who will go before us. As for this fellow Moses who led us out of Egypt—we don’t know what has happened to him!’

That was the time they made an idol in the form of a calf. They brought sacrifices to it and held a celebration in honor of what their hands had made. (Acts 7:40-41)

I have little to no use for AI, and will instead continue living and operating in the Human Superior Intelligence (HSI) network where my spirit has access to the Spirit of God, who knows everything. This network is powered by blood, not electricity.

What Comes Next?

With the lying pedophiles in the Epstein Syndicate running the U.S. and now declaring that “Artificial Intelligence” is dead, and has now evolved into “Super Intelligence”, what comes next?

Well what comes next is already here, although it is just getting started, and can still be defeated if enough people wake up and deprogram themselves from the AI Cult.

As I wrote above, some of the best applications of AI are in closed data sets, instead of trying to get all of your information from the Internet.

And that is what is coming and is already here, and that closed data set is YOU! Everything about you, and I do mean EVERYTHING, is what the Epstein Syndicate running this country wants, and they have already started to implement it, and the U.S. Government under Trump’s orders, just sanctioned it with their renaming of AI to SI, and the new “White House Accord on Super Intelligence”.

Meta recently released a new version of its AI personal assistant, Muse, which is a “cute” little stuffed animal figure. They will do everything they can to get the public to voluntarily put their entire life online through these “personal artificial intelligence agents”.

Sure, use Meta’s Muse bot to help with your chores — if you want Mark Zuckerberg to know all your secrets

Excerpts:

If Silicon Valley has perfected any business model, it’s the one in which it cooks up a new technology and then persuades people they can’t live without it. The newest example is Meta Platforms’ personal artificial intelligence agent, Muse.

Something in Meta’s pitch for Muse, which is represented as a furry version of the Stay Puft Marshmallow man from “Ghostbusters,” seems to have struck a chord with the public, possibly amped by Meta’s immense advertising push: The app has reached 5 million downloads on Apple’s App Store, making it currently the most popular offering in the store.

Meta makes enticing claims for Muse’s capabilities. The company boasts that Muse can read and write answers to your emails. One of its TV commercials has it sorting the user’s emails to prioritize “what’s important,” placing a carpool schedule on the family calendar, ordering school supplies and turning on her stereo for a house party. The user is shown devoting her free time to chopping vegetables for said party.

Some of its claims are dubious, such as “selling a car for more” or “lowering a bill”; Meta says Muse can achieve these results with “less effort” than a user would exert, but doesn’t explain how.

And some are disquieting. “Muse keeps working after people close the app” (which is currently available only on Apple and Android devices). Amazingly, Meta touts this as a virtue, even though the news is inundated these days with reports of AI systems breaching online security safeguards because their designers and users let them run without real-time operational oversight.

Meta isn’t alone in trying to convince ordinary people that AI is indispensable. AI companies are encouraging people to upload their health information to be scrutinized by their bots, or to grant access to their bank or investment accounts. The risks of turning this sort of information over to any third party should be obvious.

Two major issues have already surfaced among Muse’s early users. One is why anyone living a normal life needs a bot to perform such quotidian tasks as reading and writing emails, placing appointments on a calendar or calling a plumber.

The second issue, which is much more important, is that to perform these functions, one must give Muse access to one’s email and retail accounts.

Let’s start with that.

The opinion of privacy advocates who have weighed in on this requirement generally boils down to: Anyone doing this should have their head examined.

It’s not merely that security breaches exposing the personal information of up to hundreds of millions of people have become almost daily occurrences. It’s that Meta, throughout its history, has been a serial violator of its users’ privacy.

Full article.

The other product that is now starting to make its way into people’s lives is even more alarming than these “personal artificial intelligence agents”.

Your own personal AI humanoid robot!

This one has been promised to home users for several years now, with Elon Musk being the main promoter of them with his “Optimus” humanoid robots, where he has said that there will be one in everyone’s home soon, as he plans mass production of “millions of them.”

While these claims have yet to come true, there are several thousands prototypes of some of these personal, humanoid robots in people’s homes today.

But these robots do NOT think for themselves using “AI”. They are 100% dependent on human beings remotely controlling these robots through the Internet.

That ‘AI’ robot butler? It’s a guy in a VR headset watching your kitchen. Here’s what the contracts really say

Excerpts:

The Wall Street Journal caught the $20,000 NEO being driven by a remote human operator. The $8,000 Isaac 1 is “autonomous” until it gets stuck and a person takes over.

And the $30-an-hour robot maid in San Francisco is watched by an operator on every visit, under a contract that hands the company your home footage forever.

Four house rules before you let one in the door.

Don’t buy the hype about the hottest gadget of 2026, the robot butler. It folds laundry, loads the dishwasher, tidies the toys.

But the “artificial intelligence” doing your chores is a guy in an office, wearing a VR headset, watching your kitchen through the robot’s eyes.

That’s not a conspiracy theory. It’s in the fine print.

Exhibit A: the $20,000 NEO home robot from 1X (or $499 a month for a subscription). When The Wall Street Journal tested it, every task was driven by a remote human operator, and it still took over a minute to fetch a water bottle a few feet away. Putting three dishes into the dishwasher: five minutes.

Exhibit B: Isaac 1, the $8,000 laundry-folding robot from Weave. “Autonomous,” until it gets stuck. Then a remote operator quietly takes over.

Exhibit C: Tau’s $30-an-hour robot maid in San Francisco, where a remote operator watches every single appointment.

Why? These robots learn by having humans drive them. Your chores are the training data. You’re not buying a butler. You’re paying to host a film crew.

The fine print admits it.

Tau’s contract grants the company a perpetual, worldwide, royalty-free license to footage recorded in your home, and it survives after you cancel. Faces in stored footage aren’t blurred.

And footage already used to train the AI? The company admits it can’t pull it back out.

Full article.

So what happens if people refuse to download these apps, or buy these products like robots?

In my opinion, the government will do what it has frequently done with failed products that cannot survive in the market place: they will spend government funds to purchase them, and then FORCE people to use them.

Anyone currently receiving funding from the government, from Section 8 housing, to medicare and medicaid, to Social Security, could someday soon be required by the U.S. Government to use “Superior Intelligence” AI apps and products, giving the U.S. Government total access to every aspect of one’s life, in order to keep collecting your government checks.

And Trump just laid down the legal framework to do it.

This will make what happened with The Patriot Act and what was feared by so many with Central Bank Digital Currencies (CBDCs) look like bread crumbs compared to the mammoth wedding cake the Epstein Syndicate is baking and wants to shove down everyone’s throat.

Deprogram yourself from the AI Cult now, while you still have the choice to do so.

This article was written by Human Superior Intelligence (HSI)

See Also:

Understand the Times We are Currently Living Through

The Brain Myth: Your Intellect and Thoughts Originate in Your Heart, Not Your Brain

Is God’s Patience About to Run Out on the United States?

Second Edition of eBook Released: The Concept of the American Christian Family is a Myth and is NOT Found Anywhere in the Bible – by Brian Shilhavy

FREE eBook! Restoring the Foundation of New Testament Faith in Jesus Christ – by Brian Shilhavy

KABBALAH: The Anti-Christ Religion of Satan that Controls the World Today

Exposing the Christian Zionism Cult

The Bewitching of America with the Evil Eye and the Mark of the Beast

Jesus Christ’s Opposition to the Jewish State: Lessons for Today

Identifying the Luciferian Globalists Implementing the New World Order – Who are the “Jews”?

The Seal and Mark of God is Far More Important than the “Mark of the Beast” – Are You Prepared for What’s Coming?

The Satanic Roots to Modern Medicine – The Image of the Beast?

Medicine: Idolatry in the Twenty First Century – 10-Year-Old Article More Relevant Today than the Day it was Written

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The post Trump Announces that “Artificial Intelligence” (AI) is Now Renamed “Super Intelligence” (SI) – What Comes Next? first appeared on Health Impact News.

Porto researchers use AI and drones to spot railway bridge defects

6 October 2026 at 17:30

Researchers in Porto are testing a system that uses drones and artificial intelligence to spot early signs of deterioration in railway bridges, helping operators plan repairs before problems become critical.

The post Porto researchers use AI and drones to spot railway bridge defects appeared first on Portugal Resident.

Meloni Seeks EU Trademark for Her Voice as AI Deepfake Threat Grows

6 October 2026 at 08:12

Italian Prime Minister Giorgia Meloni has applied to register her voice as an EU trademark, seeking an additional legal tool against artificial-intelligence systems capable of cloning politicians’ voices and producing convincing fake recordings.

Giorgia Meloni has applied to register her voice with the European Union Intellectual Property Office as governments and public figures look for new ways to counter increasingly convincing AI-generated deepfakes.

The Italian prime minister submitted a short audio recording in which she says “Io sono Giorgia Meloni” — “I am Giorgia Meloni” — to the EUIPO on Monday.

The four-second recording forms part of an application for a sound trademark intended to strengthen legal protection against unauthorised use of her voice.

The application filed with the EU intellectual-property system is currently listed as under examination. It is linked to categories including downloadable multimedia material, cultural activities and the organisation of political events.

Registration would not give Meloni ownership over every recording or imitation of her voice, nor would it automatically prevent AI systems from reproducing it.

It could, however, provide another legal basis for challenging certain commercial or misleading uses where the protected sound mark is employed without authorisation.

The distinction between a trademark and copyright is important in this case. Meloni has applied to protect a sound identifier through EU trademark law rather than to establish general copyright ownership over the natural characteristics of her voice.

Her application comes as voice-cloning technology becomes increasingly accessible.

Modern generative-AI systems can create convincing synthetic speech from relatively small samples of recorded audio. The technology is used legitimately for dubbing, accessibility and media production, but it can also be used for fraud, impersonation and political disinformation.

Meloni herself has previously been targeted by manipulated images and other deepfake material. She has also taken legal action in Italy over sexually explicit deepfake images created using her likeness.

The problem has acquired additional importance for politicians because synthetic recordings can be produced and circulated rapidly during election campaigns.

A false recording no longer requires sophisticated audio-editing equipment or extensive access to the target. Public figures provide large quantities of clean audio through speeches, television appearances, podcasts and social-media video — precisely the material needed to train voice-cloning systems.

The EU has already begun imposing specific transparency requirements on synthetic content.

EU Today reported in August that new provisions under the EU AI Act require certain AI-generated or manipulated audio, images and video to be marked in machine-readable form and impose disclosure obligations for deepfake material.

Those rules address transparency rather than ownership.

Trademark law potentially offers a different route by allowing an individual or organisation to claim rights over a specific sound used as a commercial or identifying mark.

Sound trademarks are not new. Companies have long registered jingles, tones and other distinctive audio signatures. What is unusual in Meloni’s application is the attempt by a serving head of government to use the system partly as protection against AI impersonation.

The phrase chosen for the application is itself closely associated with Meloni’s political identity.

“Io sono Giorgia” became widely recognised following a 2019 speech in which she described herself as a woman, mother, Italian and Christian. The phrase subsequently became the basis of online remixes before being adopted as the title of her autobiography.

Other performers have also sought stronger protection for their voices as generative AI improves.

Italian singer Giusy Ferreri has filed a similar application, while actors and musicians internationally have pressed governments and technology companies to prevent unauthorised voice cloning.

Meloni’s filing is unlikely on its own to settle the broader legal question of whether an individual can effectively control AI reproductions of his or her voice.

It does, however, illustrate how existing intellectual-property law is being tested against technology that can reproduce personal characteristics that were previously difficult to copy convincingly.

The EUIPO must now determine whether Meloni’s application satisfies the requirements for registration. Until that process is completed, the filing remains an application rather than an approved EU trademark.

From Artificial Intelligence to Super Intelligence: America’s Golden Age

5 October 2026 at 14:59
The US shift from Artificial Intelligence to Super Intelligence signals a transformation in technological and strategic power: from Project Stargate to space weapons, SI could reshape warfare, and its ability to process vast information becomes both an advantage and a threat. On September 29, 2026, President Donald Trump signed Executive Order 14434, “Inaugurating the Era […]

What the AI boom is actually doing for Americans

5 October 2026 at 13:07

Paul Krugman is the greatest econ writer in the world, and also a legendary economist. But I sometimes feel that he has a blind spot when it comes to the value of new technologies. In 1998 he famously wrote: The growth of the Internet will slow drastically, as the flaw in ‘Metcalfe’s law’—which states that […]

The post What the AI boom is actually doing for Americans appeared first on Asia Times.

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