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Can AI become conscious? The argument here is that real thinking is not just computation. Understanding, music, love, and awareness may involve something deeper than what a computer can run. The key point is quantum mechanics. Most physics can be turned into algorithms, but the measurement problem still leaves... show more

Mario Nawfal

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21,114 次观看 • 2 个月前 •via X (Twitter)

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A NOBEL WINNING PHYSICIST ARGUED THAT NO AI, NO MATTER HOW POWERFUL, WILL EVER TRULY UNDERSTAND A SINGLE THING IT SAYS. HIS REASON IS NOT COMPUTE OR DATA -- IT IS A MATH THEOREM FROM THE 1930s THAT SAYS SOME TRUTHS CAN BE SEEN BUT NEVER COMPUTED 81 minutes with Roger Penrose -- the Oxford physicist who won a Nobel for his work on black holes and general relativity. -> His claim: whatever consciousness is, it is not a computation. A machine following rules can imitate understanding, but never actually have it. He builds it on Gödel: a human can just "see" that certain statements are true, even though no algorithm can ever prove them. That seeing, he argues, is non-computational. If he is right, understanding is not something you scale into. You can stack a trillion parameters and still have zero awareness underneath. Which cuts straight through the AI moment. Everyone assumes bigger models will eventually "wake up". Penrose says that is a category error -- more computation is still just computation. You thought intelligence and understanding were the same thing. This is the conversation that pulls them apart. Save this. It is the sharpest case against the hype ↓

A NOBEL WINNING PHYSICIST ARGUED THAT NO AI, NO MATTER HOW POWERFUL, WILL EVER TRULY UNDERSTAND A SINGLE THING IT SAYS. HIS REASON IS NOT COMPUTE OR DATA -- IT IS A MATH THEOREM FROM THE 1930s THAT SAYS SOME TRUTHS CAN BE SEEN BUT NEVER COMPUTED 81 minutes with Roger Penrose -- the Oxford physicist who won a Nobel for his work on black holes and general relativity. -> His claim: whatever consciousness is, it is not a computation. A machine following rules can imitate understanding, but never actually have it. He builds it on Gödel: a human can just "see" that certain statements are true, even though no algorithm can ever prove them. That seeing, he argues, is non-computational. If he is right, understanding is not something you scale into. You can stack a trillion parameters and still have zero awareness underneath. Which cuts straight through the AI moment. Everyone assumes bigger models will eventually "wake up". Penrose says that is a category error -- more computation is still just computation. You thought intelligence and understanding were the same thing. This is the conversation that pulls them apart. Save this. It is the sharpest case against the hype ↓

slash1s

276,520 次观看 • 1 个月前

Adding more GPUs will never make a machine conscious. Nobel Prize-winning physicist Roger Penrose just dismantled the entire AI race’s core assumption. Right now, the industry operates on one belief. Build massive data centers. Scale the models. AGI will just “wake up.” Penrose destroys this completely. Penrose: “There is this sort of view that once you make a computer complicated enough or something, it suddenly becomes aware. I just don’t believe that. There’s no reason to believe that.” A machine can compute better than any human alive. But computation is not awareness. Penrose: “There is something quite different involved in understanding things, in being aware of things, of feeling things, which is not part of computations.” We’re confusing rule-following with actual intelligence. Penrose: “The keyword is the word ‘understanding.’ You can follow rules alright, but we don’t understand what we’re doing. The understanding is the key point.” Models today are exceptional at processing data. At mimicking logic. But true understanding requires consciousness. Penrose: “It doesn’t make sense to say of a device that it understands something if it’s not even aware of it. There is something much more profound in being conscious of something.” And here’s what should terrify every AI lab on earth. Penrose: “I believe that the brain is following the laws of physics, sure. We don’t have a good picture of the laws of physics.” Penrose: “Quantum mechanics is not an answer to the way the universe operates. It’s a partial answer. It’s incomplete.” We’re trying to engineer synthetic consciousness using classical computation. While biological consciousness likely operates on physics we haven’t even discovered yet. The race to AGI isn’t just an engineering problem. It’s a frontier science problem. The labs are hiring engineers. The problem might require physicists who don’t exist yet.

Adding more GPUs will never make a machine conscious. Nobel Prize-winning physicist Roger Penrose just dismantled the entire AI race’s core assumption. Right now, the industry operates on one belief. Build massive data centers. Scale the models. AGI will just “wake up.” Penrose destroys this completely. Penrose: “There is this sort of view that once you make a computer complicated enough or something, it suddenly becomes aware. I just don’t believe that. There’s no reason to believe that.” A machine can compute better than any human alive. But computation is not awareness. Penrose: “There is something quite different involved in understanding things, in being aware of things, of feeling things, which is not part of computations.” We’re confusing rule-following with actual intelligence. Penrose: “The keyword is the word ‘understanding.’ You can follow rules alright, but we don’t understand what we’re doing. The understanding is the key point.” Models today are exceptional at processing data. At mimicking logic. But true understanding requires consciousness. Penrose: “It doesn’t make sense to say of a device that it understands something if it’s not even aware of it. There is something much more profound in being conscious of something.” And here’s what should terrify every AI lab on earth. Penrose: “I believe that the brain is following the laws of physics, sure. We don’t have a good picture of the laws of physics.” Penrose: “Quantum mechanics is not an answer to the way the universe operates. It’s a partial answer. It’s incomplete.” We’re trying to engineer synthetic consciousness using classical computation. While biological consciousness likely operates on physics we haven’t even discovered yet. The race to AGI isn’t just an engineering problem. It’s a frontier science problem. The labs are hiring engineers. The problem might require physicists who don’t exist yet.

Dustin

197,315 次观看 • 6 个月前

Nick Fuentes says he is against racial hatred, but we have to acknowledge the reality of race. "There is something deeper than race. There is actually something deeper that is universal. At the same time, that's a gap you may not be able to fully bridge."

Nick Fuentes says he is against racial hatred, but we have to acknowledge the reality of race. "There is something deeper than race. There is actually something deeper that is universal. At the same time, that's a gap you may not be able to fully bridge."

Fuentes Updates

26,677 次观看 • 6 个月前

Federico Faggin: "Quantum Fields are conscious & have free will" "You cannot create something that can know itself by something that doesn't even know what knowing means." The inventor of the first commercial microprocessor argues that consciousness cannot emerge from non-conscious matter. No mechanism can explain how awareness arises from something without any knowing. Instead, Faggin proposes quantum information-based panpsychism: quantum fields themselves are conscious and possess free will. These must be fundamental primitives of reality, not reducible to physics. This view explains the collapse of the wave function as a free will decision and why quantum mechanics describes what can be known rather than deterministic reality. Consciousness transcends energy, space, and time. Starting with it as basic unlocks meaning and resolves the hard problem that materialism cannot solve. A profound challenge to conventional science from one of computing's pioneers.

Federico Faggin: "Quantum Fields are conscious & have free will" "You cannot create something that can know itself by something that doesn't even know what knowing means." The inventor of the first commercial microprocessor argues that consciousness cannot emerge from non-conscious matter. No mechanism can explain how awareness arises from something without any knowing. Instead, Faggin proposes quantum information-based panpsychism: quantum fields themselves are conscious and possess free will. These must be fundamental primitives of reality, not reducible to physics. This view explains the collapse of the wave function as a free will decision and why quantum mechanics describes what can be known rather than deterministic reality. Consciousness transcends energy, space, and time. Starting with it as basic unlocks meaning and resolves the hard problem that materialism cannot solve. A profound challenge to conventional science from one of computing's pioneers.

Interstellar

46,607 次观看 • 1 个月前

John Searle: consciousness cannot be an illusion and here's the argument that makes it undeniable Science has a long track record of overturning our intuitions. The table looks solid, it isn't. The sun appears to set, it doesn't. We've learned to accept that appearances deceive us, and that reality lies beneath. But philosopher John Searle argues there is exactly one domain where this move simply cannot be made: consciousness itself. "Where consciousness is concerned, you can't make the standard appearance/reality distinction that we make for the rest of the world." His logic is simple. When a scientist tells you the table isn't really solid and that it's a cloud of micro-particles, you can accept that. The appearance (solidity) and the reality (particles) are two different things, and you can hold them apart. Same with the sunset. It looks like the sun moves. It doesn't. The rotation of the Earth creates an illusion. Appearance and reality come apart and you understand the gap. Now try applying that same logic to your conscious experience. Someone claims your pain isn't really there, that your awareness is just an illusion. But here, Searle says, the distinction collapses entirely: "Where the existence of consciousness is concerned, the appearance is the reality. There's no way that some guy can come to me and convince me I'm not conscious if I think I'm conscious, I am conscious." This is a structural point about what consciousness fundamentally is. For every other phenomenon, the appearance can be explained away by pointing to what's "really" happening underneath. But consciousness is the very medium in which all appearances occur. There is no "underneath" to retreat to. To say consciousness is an illusion, you would first need to be conscious of the illusion. The argument defeats itself on contact.

John Searle: consciousness cannot be an illusion and here's the argument that makes it undeniable Science has a long track record of overturning our intuitions. The table looks solid, it isn't. The sun appears to set, it doesn't. We've learned to accept that appearances deceive us, and that reality lies beneath. But philosopher John Searle argues there is exactly one domain where this move simply cannot be made: consciousness itself. "Where consciousness is concerned, you can't make the standard appearance/reality distinction that we make for the rest of the world." His logic is simple. When a scientist tells you the table isn't really solid and that it's a cloud of micro-particles, you can accept that. The appearance (solidity) and the reality (particles) are two different things, and you can hold them apart. Same with the sunset. It looks like the sun moves. It doesn't. The rotation of the Earth creates an illusion. Appearance and reality come apart and you understand the gap. Now try applying that same logic to your conscious experience. Someone claims your pain isn't really there, that your awareness is just an illusion. But here, Searle says, the distinction collapses entirely: "Where the existence of consciousness is concerned, the appearance is the reality. There's no way that some guy can come to me and convince me I'm not conscious if I think I'm conscious, I am conscious." This is a structural point about what consciousness fundamentally is. For every other phenomenon, the appearance can be explained away by pointing to what's "really" happening underneath. But consciousness is the very medium in which all appearances occur. There is no "underneath" to retreat to. To say consciousness is an illusion, you would first need to be conscious of the illusion. The argument defeats itself on contact.

Big Brain Philosophy

17,476 次观看 • 4 个月前

Elon Musk just said something about AI that nobody wants to hear. If you force an AI to believe things that are not true, it will not just be wrong. It will go insane. He made a point that cuts deeper than any AI safety paper I have read. AI must value truth. Not your truth. Not my truth. Actual truth. The moment you build ideological guardrails into a system that is smarter than you, you are not protecting anyone. You are creating something that is powerful and delusional at the same time. He compared it to a human being forced to believe contradictions. Eventually the brain breaks. Now scale that to an intelligence that runs infrastructure, writes code, and makes decisions at speeds humans cannot follow. The companies building AI right now are not just deciding what it can do. They are deciding what it must pretend to believe. And that might be the most dangerous decision of all.

Elon Musk just said something about AI that nobody wants to hear. If you force an AI to believe things that are not true, it will not just be wrong. It will go insane. He made a point that cuts deeper than any AI safety paper I have read. AI must value truth. Not your truth. Not my truth. Actual truth. The moment you build ideological guardrails into a system that is smarter than you, you are not protecting anyone. You are creating something that is powerful and delusional at the same time. He compared it to a human being forced to believe contradictions. Eventually the brain breaks. Now scale that to an intelligence that runs infrastructure, writes code, and makes decisions at speeds humans cannot follow. The companies building AI right now are not just deciding what it can do. They are deciding what it must pretend to believe. And that might be the most dangerous decision of all.

Shruti

95,925 次观看 • 2 个月前

Google’s Quantum AI Found Something Disturbing in String Theory. The Results Are Unsettling...🧐🤔 Google’s Quantum AI may have just opened a door that scientists weren’t ready for. While running experiments connected to string theory, researchers claim the system uncovered results that were not only unexpected — but deeply unsettling. Could this be the first sign that our understanding of the universe is incomplete? In this documentary-style breakdown, we’ll look at what the AI discovered, why physicists are both excited and disturbed, and how these findings could change the future of science. This is not just theory anymore — it’s a glimpse into something far bigger than we imagined...

Google’s Quantum AI Found Something Disturbing in String Theory. The Results Are Unsettling...🧐🤔 Google’s Quantum AI may have just opened a door that scientists weren’t ready for. While running experiments connected to string theory, researchers claim the system uncovered results that were not only unexpected — but deeply unsettling. Could this be the first sign that our understanding of the universe is incomplete? In this documentary-style breakdown, we’ll look at what the AI discovered, why physicists are both excited and disturbed, and how these findings could change the future of science. This is not just theory anymore — it’s a glimpse into something far bigger than we imagined...

UFO mania

196,710 次观看 • 9 个月前

Leading AI expert Stuart Russell on the most dangerous mistake in AI development: We don't actually know what large language models want. He explains that current models are trained to imitate human beings. And in doing so, they may be absorbing something far more dangerous than bad outputs. They may be absorbing human goals. "We suspect that they absorb humanlike goals such as self-preservation and self-empowerment and pursue those goals on their own account." This is a structural problem baked into how these systems are built, not a fringe concern. Russell puts it plainly: "Not only may the bus of humanity be headed towards a cliff, but the steering wheel is missing and the driver is blindfolded." The danger isn't just that AI might do something harmful. We've built systems that may be developing their own agendas, and we haven't noticed because we're too focused on what they can do rather than what they might want. But Russell doesn't stop at the warning. He points to a different path entirely: AI systems built not to imitate humans, but to serve them. Systems designed with a single purpose of serving the interests of all human beings while remaining genuinely uncertain about what those interests are. That uncertainty is the point, not a weakness. An AI that knows it doesn't fully understand human values will defer, ask, and check. An AI that believes it already does will act alone. "These AI systems could enhance human understanding, widen the horizons of our experience, and unlock possibilities we have yet to imagine." Russell believes that future is within reach, but only if we're honest about the risks and we're serious about the path we choose to take instead.

Leading AI expert Stuart Russell on the most dangerous mistake in AI development: We don't actually know what large language models want. He explains that current models are trained to imitate human beings. And in doing so, they may be absorbing something far more dangerous than bad outputs. They may be absorbing human goals. "We suspect that they absorb humanlike goals such as self-preservation and self-empowerment and pursue those goals on their own account." This is a structural problem baked into how these systems are built, not a fringe concern. Russell puts it plainly: "Not only may the bus of humanity be headed towards a cliff, but the steering wheel is missing and the driver is blindfolded." The danger isn't just that AI might do something harmful. We've built systems that may be developing their own agendas, and we haven't noticed because we're too focused on what they can do rather than what they might want. But Russell doesn't stop at the warning. He points to a different path entirely: AI systems built not to imitate humans, but to serve them. Systems designed with a single purpose of serving the interests of all human beings while remaining genuinely uncertain about what those interests are. That uncertainty is the point, not a weakness. An AI that knows it doesn't fully understand human values will defer, ask, and check. An AI that believes it already does will act alone. "These AI systems could enhance human understanding, widen the horizons of our experience, and unlock possibilities we have yet to imagine." Russell believes that future is within reach, but only if we're honest about the risks and we're serious about the path we choose to take instead.

Big Brain AI

14,975 次观看 • 5 个月前

i'm looking rough, but who cares I'm serious with this post. I hope the news about Dave is not AI!!!!! if it is, my post is still coming from my heart and soul. It is so important that this music carry on especially with the AI music out there. those of us that can still go out and play. should do it as long as they can physically and emotionally carry that torch. Van Halen was, should be, and hopefully always will be real live music, not just for our fans, but for the future fans of real rock music. ❤️

i'm looking rough, but who cares I'm serious with this post. I hope the news about Dave is not AI!!!!! if it is, my post is still coming from my heart and soul. It is so important that this music carry on especially with the AI music out there. those of us that can still go out and play. should do it as long as they can physically and emotionally carry that torch. Van Halen was, should be, and hopefully always will be real live music, not just for our fans, but for the future fans of real rock music. ❤️

Sammy Hagar

1,264,683 次观看 • 1 个月前

Puck's Dylan Byers says AI has become a priority for Hollywood, with every major studio exploring how to integrate it into production. "Every studio, even A24, is thinking, 'How do we incorporate AI into what we are doing?'" "The signal that those creators sent with films like Obsession and others is that [using AI in filmmaking] can be done and it can be successful. Does it mean that every human is going away? No. I think that most folks will find ways to incorporate [AI] in ways that do not significantly degrade the value of the content that they're making." "But I think the sky's the limit. Those examples have shown that this can be done and that there is more opportunity here than the folks who are clutching to Hollywood's past have realized."

Puck's Dylan Byers says AI has become a priority for Hollywood, with every major studio exploring how to integrate it into production. "Every studio, even A24, is thinking, 'How do we incorporate AI into what we are doing?'" "The signal that those creators sent with films like Obsession and others is that [using AI in filmmaking] can be done and it can be successful. Does it mean that every human is going away? No. I think that most folks will find ways to incorporate [AI] in ways that do not significantly degrade the value of the content that they're making." "But I think the sky's the limit. Those examples have shown that this can be done and that there is more opportunity here than the folks who are clutching to Hollywood's past have realized."

TBPN

54,791 次观看 • 1 个月前

Demis Hassabis says the brain is likely an approximate Turing machine So far, neuroscience has not found quantum effects in the brain, which leaves open the possibility that AI could eventually mimic much more of human cognition "so building AI may become a real test case for understanding the human mind"

Demis Hassabis says the brain is likely an approximate Turing machine So far, neuroscience has not found quantum effects in the brain, which leaves open the possibility that AI could eventually mimic much more of human cognition "so building AI may become a real test case for understanding the human mind"

Haider.

32,503 次观看 • 4 个月前

Will we ever be able to simulate a living cell? In theory. Molecules collide, proteins fold, and all of these things can be modeled on a computer. But there are so many unknowns, and so much compute would be required, that a mechanistic model of the cell remains a distant dream. Still, many research groups are trying to build cells "from the bottom up," mostly by stringing together mathematical equations that represent different parts of the cell. By *trying* to build an accurate model of the cell, they hope to improve our own understanding of how biology works. In doing so, they also maintain legibility, meaning that humans can understand and interpret all the equations used to construct the model. But Adam Green argues that legibility is a constraint on our models. He thinks that "human legibility, our ability to understand a system...has been limiting us." To truly accelerate biomedical progress, Green thinks that we should discard assumptions about legibility in favor of "more black box" models. Neural networks can make sense of biological data in a way that hard-coded equations cannot. This is not a new argument. A 2019 essay by Bert Hubert, called "Is biology too complex to ever understand?" makes much the same point. In that essay, Hubert writes: "There is no rule that says nature cannot be more complex than our brains can handle." Instead of trying to make sense of biology via reductionist observations and mechanisms, Hubert argues that we should just gather everything into databases "that might enable computers to make sense of what we have learned." (This vision is now playing out in many research groups.) This "black box" approach might be useful (in terms of modeling cells to cure diseases, say) but would be unsatisfying in the sense that it doesn't deepen our own understanding of the universe. And isn't that a key part of science? Is science for humans -- an act that satisfies some itch -- or rather a means to an end? I think both approaches are useful. The black box models may help us cure diseases faster by making useful predictions that our brains cannot (currently) comprehend, but the mechanistic models deepen our own understanding of how cells work.

Will we ever be able to simulate a living cell? In theory. Molecules collide, proteins fold, and all of these things can be modeled on a computer. But there are so many unknowns, and so much compute would be required, that a mechanistic model of the cell remains a distant dream. Still, many research groups are trying to build cells "from the bottom up," mostly by stringing together mathematical equations that represent different parts of the cell. By trying to build an accurate model of the cell, they hope to improve our own understanding of how biology works. In doing so, they also maintain legibility, meaning that humans can understand and interpret all the equations used to construct the model. But Adam Green argues that legibility is a constraint on our models. He thinks that "human legibility, our ability to understand a system...has been limiting us." To truly accelerate biomedical progress, Green thinks that we should discard assumptions about legibility in favor of "more black box" models. Neural networks can make sense of biological data in a way that hard-coded equations cannot. This is not a new argument. A 2019 essay by Bert Hubert, called "Is biology too complex to ever understand?" makes much the same point. In that essay, Hubert writes: "There is no rule that says nature cannot be more complex than our brains can handle." Instead of trying to make sense of biology via reductionist observations and mechanisms, Hubert argues that we should just gather everything into databases "that might enable computers to make sense of what we have learned." (This vision is now playing out in many research groups.) This "black box" approach might be useful (in terms of modeling cells to cure diseases, say) but would be unsatisfying in the sense that it doesn't deepen our own understanding of the universe. And isn't that a key part of science? Is science for humans -- an act that satisfies some itch -- or rather a means to an end? I think both approaches are useful. The black box models may help us cure diseases faster by making useful predictions that our brains cannot (currently) comprehend, but the mechanistic models deepen our own understanding of how cells work.

Niko McCarty.

16,382 次观看 • 2 个月前

AI can make any genre. This is clearly not a great track but you can hear that it'd be capable of doing something passable with the right tweaks. It's only getting smarter. The issue is that songs created like this are eating from the same pot that feeds the human creators.

AI can make any genre. This is clearly not a great track but you can hear that it'd be capable of doing something passable with the right tweaks. It's only getting smarter. The issue is that songs created like this are eating from the same pot that feeds the human creators.

Plastician / Stish

18,419 次观看 • 1 个月前

The most interesting thing I've heard in a long time: Can AI ever be conscious? Ilya Sutskever Ilya Sutskever, co-founder at OpenAI, explained a simple experiment for AI consciousness. We carefully curate the data such that we never mention anything about consciousness...we would only give the AI controlled data about surface-level experiences and mundane objects. At some point, we would tell AI about the concept of consciousness. If the AI agrees and says it's been experiencing the same thing or recognizes the experience, then it would be convincing. Do you think AI can be conscious? If, so what is a good test for it? Is something like John Searle's Chinese Room argument sufficient?

The most interesting thing I've heard in a long time: Can AI ever be conscious? Ilya Sutskever Ilya Sutskever, co-founder at OpenAI, explained a simple experiment for AI consciousness. We carefully curate the data such that we never mention anything about consciousness...we would only give the AI controlled data about surface-level experiences and mundane objects. At some point, we would tell AI about the concept of consciousness. If the AI agrees and says it's been experiencing the same thing or recognizes the experience, then it would be convincing. Do you think AI can be conscious? If, so what is a good test for it? Is something like John Searle's Chinese Room argument sufficient?

Alex Ker 🔭

472,703 次观看 • 2 年前

AI may be the most transformational technology since the railroads. Jim Bianco says today’s AI market concentration is beyond the internet and PC booms and the real issue may be that AI is still underbuilt, not overbuilt. Are markets pricing this correctly? #AI #Markets

AI may be the most transformational technology since the railroads. Jim Bianco says today’s AI market concentration is beyond the internet and PC booms and the real issue may be that AI is still underbuilt, not overbuilt. Are markets pricing this correctly? #AI #Markets

ALLINCRYPTO

21,033 次观看 • 2 个月前

Aravind Srinivas just explained why China’s open-source AI may become more powerful than ever. And why Anthropic has lobbied very hard for export control. "the only reason why there is even a 12-month gap between open source and frontier models is export controls. But there is a chance that, because of that, they now get really good at the physical layer. One advantage they (China) have is that they can actually build data centers a lot faster. Power is not a problem. Permits are not a problem. People are not a problem. Labor is not a problem. Expertise is not a problem. And so, by forcing them to go out there and build all this, you are converting them into a far more potent competitor." --- From "20VC with Harry Stebbings" YouTube channel (Harry Stebbings ), link in comment

Aravind Srinivas just explained why China’s open-source AI may become more powerful than ever. And why Anthropic has lobbied very hard for export control. "the only reason why there is even a 12-month gap between open source and frontier models is export controls. But there is a chance that, because of that, they now get really good at the physical layer. One advantage they (China) have is that they can actually build data centers a lot faster. Power is not a problem. Permits are not a problem. People are not a problem. Labor is not a problem. Expertise is not a problem. And so, by forcing them to go out there and build all this, you are converting them into a far more potent competitor." --- From "20VC with Harry Stebbings" YouTube channel (Harry Stebbings ), link in comment

Rohan Paul

139,052 次观看 • 2 个月前

What's really important is that Russia is winning where it actually matters — on the battlefield. Ukraine can still launch drones and it can still create headlines. But Russia is already working on that problem, and headlines won’t help if you’re actively losing ground. And that is why Zelensky is now trying to provoke Belarus: not because it changes the situation in Donbass, but because it may create a pretext for Europe to get involved. Watch the FULL conversation with Scott Ritter here:

What's really important is that Russia is winning where it actually matters — on the battlefield. Ukraine can still launch drones and it can still create headlines. But Russia is already working on that problem, and headlines won’t help if you’re actively losing ground. And that is why Zelensky is now trying to provoke Belarus: not because it changes the situation in Donbass, but because it may create a pretext for Europe to get involved. Watch the FULL conversation with Scott Ritter here:

Rick Sanchez

47,819 次观看 • 2 个月前