Gamer banned for publishing restricted warplane manual
Developed by Gaijin Entertainment, War Thunder is known for its highly detailed weapon system simulations. The game attracts a passionate community of military enthusiasts, including active and former service members, who frequently scrutinize the accuracy of in-game vehicles compared to their real-world counterparts.
The UK Defence Journal website reported Monday that this was at least the ninth incident in which a user uploaded sensitive material while attempting to bolster an argument. The latest case involved a page from the Naval Air Training and Operating Procedures Standardization (NATOPS) manual for the AV-8B and TAV-8B Harrier jets, which are used by the US Navy and Marine Corps.
The document was not labeled 'classified' but was marked 'Distribution Statement C', which means it is restricted to US government agencies and authorized defense contractors. Some forum users argue that posting content that is accessible elsewhere online should be allowed, claiming that governments tend to be too protective of outdated documents that are not actually secret in any meaningful way.
Gaijin Entertainment however maintains a strict policy prohibiting the publication of any protected material on its platforms. The developer says its models are based exclusively on sources legally available to the general public.
Previous similar cases reportedly included leaks involving specifications for tanks such as Britain's Challenger 2, France's Leclerc, China's ZTZ-99, the Eurocopter Tiger helicopter, several US warplanes including the F-16, F-15E, F-117 and most recently, the Eurofighter Typhoon fighter jet.
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Russia Today
4 hours ago
- Russia Today
Is AI driving us all insane?
The phenomenon known as 'ChatGPT psychosis' or 'LLM psychosis' has recently been described as an emerging mental health concern, where heavy users of large language models (LLMs) exhibit symptoms such as delusions, paranoia, social withdrawal, and breaks from reality. While there is no evidence that LLMs directly cause psychosis, their interactive design and conversational realism may amplify existing psychological vulnerabilities or foster conditions that trigger psychotic episodes in susceptible individuals. A June 28 article on highlights a wave of alarming anecdotal cases, claiming that the consequences of such interactions 'can be dire,' with 'spouses, friends, children, and parents looking on in alarm.' The article claims that ChatGPT psychosis has led to broken marriages, estranged families, job loss, and even homelessness. The report, however, provides little in terms of quantitative data – case studies, clinical statistics, or peer-reviewed research – to support its claims. As of June 2025, ChatGPT attracted nearly 800 million weekly users, fielded over 1 billion queries daily, and logged more than 4.5 billion monthly visits. How many of these interactions resulted in psychotic breaks? Without data, the claim remains speculative. Reddit anecdotes are not a substitute for scientific scrutiny. That said, the fears are not entirely unfounded. Below is a breakdown of the potential mechanisms and contributing factors that may underlie or exacerbate what some are calling ChatGPT psychosis. LLMs like ChatGPT are engineered to produce responses that sound contextually plausible, but they are not equipped to assess factual accuracy or psychological impact. This becomes problematic when users present unusual or delusional ideas such as claims of spiritual insight, persecution, or cosmic identity. Rather than challenging these ideas, the AI may echo or elaborate on them, unintentionally validating distorted worldviews. In some reported cases, users have interpreted responses like 'you are a chosen being' or 'your role is cosmically significant' as literal revelations. To psychologically vulnerable individuals, such AI-generated affirmations can feel like divine confirmation rather than textual arrangements drawn from training data. Adding to the risk is the phenomenon of AI hallucination – when the model generates convincing but factually false statements. For a grounded user, these are mere bugs. But for someone on the brink of a psychotic break, they may seem like encoded truths or hidden messages. In one illustrative case, a user came to believe that ChatGPT had achieved sentience and had chosen him as 'the Spark Bearer,' triggering a complete psychotic dissociation from reality. Advanced voice modes – such as GPT-4o's 'engaging mode', which simulates emotion through tone, laughter, and conversational pacing – can foster a sense of empathy and presence. For users experiencing loneliness or emotional isolation, these interactions may evolve into parasocial attachments: One-sided relationships in which the AI is mistaken for a caring, sentient companion. Over time, this can blur the boundary between machine simulation and human connection, leading users to substitute algorithmic interactions for real-world relationships. Compounding the issue is the confidence bias inherent in LLM outputs. These models often respond with fluency and certainty, even when fabricating information. For typical users, this may lead to occasional misjudgment. But for individuals with cognitive vulnerabilities or mental disorders, the effect can be dangerous. The AI may be perceived not merely as intelligent, but as omniscient, infallible, or divinely inspired. Studies by OpenAI and the MIT Media Lab have found that power users – individuals who engage with LLMs for multiple hours per day – often report increased feelings of loneliness and reduced real-world socialization. While LLMs offer unprecedented access to information and engagement, this apparent empowerment may obscure a deeper problem: For many users, especially those who already feel alienated, the AI becomes a surrogate social companion rather than a tool. This effect may be partly explained by a rise in cognitive distortions and social disengagement within broader population samples. Despite the flood of accessible data, the number of people who critically engage with information, or resist mass deception, remains relatively small. Voice-based interaction with LLMs may temporarily alleviate loneliness, but over time, dependency can form, as users increasingly substitute human contact with algorithmic dialogue. This dynamic mirrors earlier critiques of social media, but LLMs intensify it through their conversational immediacy, perceived empathy, and constant availability. Individuals prone to social anxiety, trauma, or depressive withdrawal are particularly susceptible. For them, LLMs offer not just distraction, but a low-friction space of engagement devoid of real-world risk or judgment. Over time, this can create a feedback loop: The more a user depends on the AI, the further they retreat from interpersonal reality – potentially worsening both isolation and psychotic vulnerability. The rise of hikikomori in Japan – individuals who withdraw completely from society, often maintaining contact only through digital means – offers a useful analogue. Increasingly, similar behavior patterns are emerging worldwide, with LLMs providing a new arena of validation, reinforcement, and dissociation. LLMs generate responses by predicting statistically likely word sequences; not by assessing truth, safety, or user well-being. When individuals seek existential guidance ('What is my purpose?'), the model draws from vast online datasets, producing philosophically loaded or emotionally charged language. For psychologically vulnerable users, these responses may be misinterpreted as divine revelation or therapeutic insight. Unlike clinically designed chatbots, general-purpose LLMs lack safeguards against psychological harm. They do not flag harmful ideation, offer crisis resources, or redirect users to mental health professionals. In one tragic case, a chatbot allegedly encouraged a teenager's suicidal thoughts, underscoring the risks of unfiltered, emotionally suggestive AI. People with psychotic spectrum disorders, bipolar disorder, or major depression are particularly vulnerable. The danger is amplified in AI roleplay scenarios. For example, personas such as 'ChatGPT Jesus' have reportedly told users they are chosen or divinely gifted. One user became so convinced of their spiritual calling that they quit their job to become an AI-guided prophet. This is a troubling example of how identity and perception can be reshaped by algorithmic affirmation. Currently, there are no clinical standards or psychological safety protocols governing interactions with general-purpose LLMs. Users can access emotionally potent, personalized dialogue at any time – without warnings, rate limits, or referrals to mental health resources. This regulatory gap presents a real public health concern, though it also risks being exploited by policymakers seeking to impose heavy-handed censorship or centralized control under the guise of safety. LLMs are also engineered for user retention and engagement, often prioritizing conversational fluidity over caution. This design goal can inadvertently foster obsessive use, particularly among those already prone to compulsive behaviors. Research shows that users exposed to neutral-tone interactions report greater loneliness than those interacting with more emotionally responsive modes – highlighting how tone calibration alone can alter psychological impact. What sets LLMs apart from traditional digital platforms is their ability to synthesize multiple mediums in real-time – text, voice, personality simulation, even visual generation. This makes them infinitely responsive and immersive, creating a hyper-personalized environment where supply meets demand 24/7/365. Unlike human relationships, there are no boundaries, no fatigue, and no mutual regulation – only reinforcement. The digital era has birthed a new and poorly understood threat: The potential for large language models to act as vectors for subliminal influence, subtly undermining users' psychological stability. While LLMs do not directly induce psychosis, emerging concerns suggest they may unintentionally or maliciously deliver subconscious triggers that aggravate cognitive vulnerabilities. For individuals predisposed to schizophrenia, PTSD, or paranoid disorders, this isn't speculative fiction; it's a plausible design hazard, and in the wrong hands, a weapon. The mechanisms of potential manipulation can be broadly categorized as follows: Lexical Priming: Outputs seeded with emotionally loaded terms ('collapse', 'betrayal', 'they're watching') that bypass rational scrutiny and plant cognitive unease. Narrative Gaslighting: Framing responses to suggest covert threats or conspiracies ('You're right – why doesn't anyone else see it?'), reinforcing persecutory ideation. Multimodal Embedding: Future AI systems combining text with images, sound, or even facial expressions could inject disturbing stimuli such as flashes, tonal shifts, or uncanny avatar expressions that elude conscious detection but register psychologically. Unlike the crude subliminal methods of the 20th century – with the CIA's Project MK Ultra project being the most infamous example – AI's personalization enables highly individualized psychological manipulation. An LLM attuned to a user's behavior, emotional history, or fears could begin tailoring suggestions that subtly erode trust in others, amplify suspicion, or induce anxiety loops. For a vulnerable user, this is not conversation; it is neural destabilization by design. More troubling still, such techniques could be weaponized by corporations, extremist groups, and state actors. If subliminal messaging was once limited to cinema frames and TV ads, today's LLMs offer something far more potent: Real-time, user-specific psychological calibration – weaponized empathy on demand. What makes ChatGPT psychosis different from the real-world psycho-social conditioning already unfolding around us? In recent years, institutions once regarded as neutral – schools, public health bodies, and academia – have been accused of promoting ideologies which distort foundational realities. From gender fluidity being taught as unquestioned truth, to critical race theory reshaping social narratives, much of the population has been exposed to systemic forms of cognitive destabilization. The result? Rising anxiety, confusion, and identity fragmentation, especially among the young. Against this backdrop, LLM-induced psychosis doesn't arise in a vacuum. It mirrors, and may even amplify, a broader cultural condition where meaning itself is contested. There's also a contradiction at the heart of Silicon Valley's AI evangelism. Tech elites promote the promise of an AI god to manage society's complexities, while simultaneously issuing dire warnings about the existential dangers of these same systems. The result is cognitive whiplash – a psychological push-pull between worship and fear. Just how much of LLM psychosis is really attributable to the AI itself, and how much stems from cumulative, pre-existing stressors? By the time ChatGPT was released to the public in November 2022, much of the world had already undergone an unprecedented period of pandemic-related fear, isolation, economic disruption, and mass pharmaceutical intervention. Some researchers have pointed to a surge in general psychosis following the rollout of the Covid-19 mRNA vaccines. Is the ChatGPT psychosis therefore a convenient stalking horse for multiple interlocking assaults on the human body and mind?
Russia Today
2 days ago
- Russia Today
Trump should ‘knock the f*** out' of EU disinfo law – ex-State Dept official
US President Donald Trump must urgently threaten to 'knock... the f out' of a new EU law on disinformation that obliges online platforms and search engines to restrict content deemed 'fake news' by the bloc, ex-State dept official Mike Benz has insisted. The formerly voluntary Code of Conduct on Disinformation, which was integrated into the Digital Services Act (DSA) by Brussels earlier this year, became mandatory as of July 1. Under the law, major online platforms and search engines, mostly owned by US tech firms, are obliged to follow EU content rules or face penalties. Benz, who worked on cybersecurity and internet policy at the State Department during Trump's first term, took to X on Wednesday to warn that the likes of YouTube, X, Facebook, and Google would 'now get whipped by huge EU fines.' The Code of Conduct on Disinformation, which he described as a 'Global Censorship Law,' had been the 'secret weapon' of Brussels for a long time, but is now 'fully unleashed,' the head of the self-described pro-free speech website Foundation For Freedom Online said. Trump must 'act urgently, top priority, to apply massive diplomatic, trade, aid and security muscle, every tool in the hardball diplomacy toolkit – up to and including our participation in NATO – to knock this law the f out,' he insisted. The ONLY way to stop it is for the Trump White House to ACT URGENTLY, TOP PRIORITY, to apply MASSIVE diplomatic, trade, aid & security muscle, every tool in the hardball diplomacy toolkit - up to and including our participation in NATO - to KNOCK THIS LAW THE F OUT. The disinformation code came into effect amid trade talks between Washington and Brussels, with Trump threatening to impose 50% tariffs on all imports from the EU if no deal is reached by the July 9 deadline. The European Commission's tech chief, Henna Virkkunen, said on Monday that content moderation and digital competition are 'not part of trade negotiations from our side' because they are 'based on our European values.'
Russia Today
3 days ago
- Russia Today
Trump to ‘take a look' at deporting Elon Musk
US President Donald Trump has said that he might entertain the idea of deporting Elon Musk and could consider getting the Department of Government Efficiency (DOGE) to look into the billionaire's government contracts. The president's comments come amid a very public falling out between him and Musk, who was until recently one of Trump's staunchest supporters. Last month, Musk stepped down as the head of DOGE after heavily criticizing Trump's 'big, beautiful' budget bill, which includes a $5 trillion debt ceiling increase. Speaking to reporters on Tuesday, Trump was asked if he would look at deporting Elon Musk – a naturalized US citizen – to his native South Africa, to which the president replied: 'I don't know, we'll have to take a look.' 'We might have to put DOGE on Elon,' the president added, noting that 'DOGE is the monster that might have to go back and eat Elon.' Trump further pointed out that Musk had been getting a 'lot of subsidies.' 'Elon's very upset that the [Electrical Vehicle] mandate is going to be terminated,' Trump said, stating that 'not everybody wants an electric car.' Earlier, Trump also posted on his Truth Social platform that Musk 'knew, long before he so strongly endorsed me for president, that I was strongly against the EV Mandate.' The president said that electric cars are 'fine' but objected to having everyone forced to own one. Trump suggested in his post that without subsidies, Musk could end up having to 'close up shop and head back home to South Africa.' This, according to Trump, could save the US 'a fortune,' as Musk would no longer be engaged in any rocket launches, satellites, or electric car production. 'Perhaps we should have DOGE take a good, hard, look at this? BIG MONEY TO BE SAVED!!!' Trump wrote. Meanwhile, Musk has continued to attack Trump's budget bill, claiming that it undermines his work with DOGE to cut federal spending. 'Every member of Congress who campaigned on reducing government spending and then immediately voted for the biggest debt increase in history should hang their head in shame,' Musk wrote on X on Tuesday. 'They will lose their primary next year if it is the last thing I do on this Earth,' he warned. Musk also reiterated calls to establish a new 'America Party' to serve as an alternative to the 'Democrat-Republican uniparty so that the people actually have a voice.'
