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A Neuralink implant can control any device that can be controlled via a computer or phone. As if controlling computers weren’t already wild enough. Lights and lighting systems. Thermostats. Smart locks. Security cameras and doorbells. Electric vehicles, FSD, e-bikes, scooters, or powered wheelchairs. The list is endless. Your digital... show more

Mario Nawfal

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56,837 次观看 • 4 个月前 •via X (Twitter)

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NEURALINK TURNS YOUR BRAIN INTO A REMOTE FOR ANY DEVICE Your brain got promoted from “thinking” to “controlling every device in the room.” Mind Control: •⁠ ⁠Think it – and devices react like loyal pets •⁠ ⁠Robotic arms, wheelchairs, lights, locks… all obey straight from your cortex •⁠ ⁠If a phone can command it, your brain will do it faster •⁠ ⁠Built first for paralysis, scaled next for anyone craving superpowers Welcome to the era where your devices will follow your thoughts! Source: Neuralink

NEURALINK TURNS YOUR BRAIN INTO A REMOTE FOR ANY DEVICE Your brain got promoted from “thinking” to “controlling every device in the room.” Mind Control: •⁠ ⁠Think it – and devices react like loyal pets •⁠ ⁠Robotic arms, wheelchairs, lights, locks… all obey straight from your cortex •⁠ ⁠If a phone can command it, your brain will do it faster •⁠ ⁠Built first for paralysis, scaled next for anyone craving superpowers Welcome to the era where your devices will follow your thoughts! Source: Neuralink

Mario Nawfal

249,709 次观看 • 10 个月前

OPINION: WILL NEURALINK LET HUMANS KEEP UP WITH SUPERINTELLIGENT AI? The truth is simple. In the next five to ten years we could have AI thousands of times smarter than any human. Our brains are amazing, but they are slow compared to AI. We speak about 150 words a minute and type even slower. Super intelligent AI will think and solve problems at speeds we cannot imagine. Neuralink is a solution. That amazing, tiny implant connects your brain directly to computers. You think and the machine responds instantly, no more slow keyboards or speech. More than a dozen people already have Neuralink implants. Some who were fully paralyzed are now playing video games, designing 3D models, and controlling computers just by thinking. Elon says the next steps are real telepathy and downloading knowledge straight into your brain. The plan is not to beat super intelligent AI in a race we cannot win. The plan is to team up with it. A high-speed brain link lets our human creativity, emotions, and values guide the AI while we get its incredible power. In the future, will there be a day without Neuralink, most people get left behind?

OPINION: WILL NEURALINK LET HUMANS KEEP UP WITH SUPERINTELLIGENT AI? The truth is simple. In the next five to ten years we could have AI thousands of times smarter than any human. Our brains are amazing, but they are slow compared to AI. We speak about 150 words a minute and type even slower. Super intelligent AI will think and solve problems at speeds we cannot imagine. Neuralink is a solution. That amazing, tiny implant connects your brain directly to computers. You think and the machine responds instantly, no more slow keyboards or speech. More than a dozen people already have Neuralink implants. Some who were fully paralyzed are now playing video games, designing 3D models, and controlling computers just by thinking. Elon says the next steps are real telepathy and downloading knowledge straight into your brain. The plan is not to beat super intelligent AI in a race we cannot win. The plan is to team up with it. A high-speed brain link lets our human creativity, emotions, and values guide the AI while we get its incredible power. In the future, will there be a day without Neuralink, most people get left behind?

Mario Nawfal

29,841 次观看 • 10 个月前

No surgery. No wires. No brain implant. A retainer that controls your iPhone with your tongue. This is MIT's 0.7mm answer to Neuralink. The startup Augmental built a device called the MouthPad. Founder Tomás Vega designed it as a dental-grade smart retainer. It sits on the roof of your palate. A capacitive trackpad reads tongue movement as input. Users swipe, tap, and type completely hands-free. The device runs about 9 hours per charge. Augmental reports 100+ users already deployed in the field. Neuralink requires skull surgery to read brain signals. This approach grants similar independence with zero medical risk. It serves people with spinal cord injuries and paralysis. Sometimes the smartest answer skips the operating room entirely. QUESTIONS: Where else do we reach for surgery when simpler tools exist? What makes assistive tech go from clever demo to daily lifeline? Leave your thoughts and comments below 👇 --- 🎁 Join 10,000+ others who learned gamification for FREE: ♻️ REPOST to inspire your community And FOLLOW Yu-kai Chou for more content like this

No surgery. No wires. No brain implant. A retainer that controls your iPhone with your tongue. This is MIT's 0.7mm answer to Neuralink. The startup Augmental built a device called the MouthPad. Founder Tomás Vega designed it as a dental-grade smart retainer. It sits on the roof of your palate. A capacitive trackpad reads tongue movement as input. Users swipe, tap, and type completely hands-free. The device runs about 9 hours per charge. Augmental reports 100+ users already deployed in the field. Neuralink requires skull surgery to read brain signals. This approach grants similar independence with zero medical risk. It serves people with spinal cord injuries and paralysis. Sometimes the smartest answer skips the operating room entirely. QUESTIONS: Where else do we reach for surgery when simpler tools exist? What makes assistive tech go from clever demo to daily lifeline? Leave your thoughts and comments below 👇 --- 🎁 Join 10,000+ others who learned gamification for FREE: ♻️ REPOST to inspire your community And FOLLOW Yu-kai Chou for more content like this

Yu-kai Chou

17,185 次观看 • 4 个月前

Are you safer with LIDAR, or are you safer with vision? This is a false dichotomy. The more pertinent question today is "do you have something, or do you have nothing?" As you can see from the clips below, vision based systems avoid countless potential collisions every day. The difference between a crash and no crash isn't what sensor suite you chose — it's whether you have any AI on your car at all. Even if we concede that LIDAR may help prevent some additional crashes, we are really debating whether it is 1% of crashes or 0.00001% of crashes. Not all crashes are super complex and require lasers to detect. Most are simple, routine, and can easily be prevented by today's vision based AI. In fact, evidence is mounting that computer vision based systems can actually outperform more traditional approaches to self-driving. Why? Because the low cost of cameras enables you to create a much larger, more varied, and more diverse dataset. If you want to have expensive custom cars that's fine, but you're going to get fewer vehicles for the same budget. Seeing what's in front of you now is actually less important than predicting what's going to happen next — and the large scale datasets used to train pure vision systems are the best for predicting what's next. Counter-intuitively, the simpler and lower cost sensor actually has properties that make it better suited for training advanced AI. Computer vision based self-driving is often framed by LIDAR proponents as "cheaping out" on the sensor suite to save money. But it's not about being cheap, it's about bringing the technology to everyone. 1.2 million people die on the road every year around the world. That's around 39 million people who've died on the roads around the world since I was born — equivalent to a city the size of Tokyo or New Delhi getting wiped off the map. The status quo is simply unacceptable, and something has to be done to fix it as soon as possible. Of the 1.2 million people that will die on the roads this year, about 40,000 will be Americans. That's about 3%. So if we moved entirely to self-driving cars in America and brought crashes down to 0, 97% of the world's crash fatalities would still be taking place as usual. Deploying a $200,000+ retrofitted self-driving car may work in a few American cities, but it is not going to make sense in most places around the world where fares are much cheaper. Most often, the choice is not between LIDAR and vision. It's between vision or nothing. The best system is the system that's there running on my car when I need it to save my life. To say that all self-driving cars must have LIDAR is to sentence most of the world to death. We can't write off computer vision if we want to make a serious dent in this problem. It's going to be a key piece of the solution. Let LIDAR based players build the best self-driving car they can, and let vision based players do the same. We need to be trying everything

Are you safer with LIDAR, or are you safer with vision? This is a false dichotomy. The more pertinent question today is "do you have something, or do you have nothing?" As you can see from the clips below, vision based systems avoid countless potential collisions every day. The difference between a crash and no crash isn't what sensor suite you chose — it's whether you have any AI on your car at all. Even if we concede that LIDAR may help prevent some additional crashes, we are really debating whether it is 1% of crashes or 0.00001% of crashes. Not all crashes are super complex and require lasers to detect. Most are simple, routine, and can easily be prevented by today's vision based AI. In fact, evidence is mounting that computer vision based systems can actually outperform more traditional approaches to self-driving. Why? Because the low cost of cameras enables you to create a much larger, more varied, and more diverse dataset. If you want to have expensive custom cars that's fine, but you're going to get fewer vehicles for the same budget. Seeing what's in front of you now is actually less important than predicting what's going to happen next — and the large scale datasets used to train pure vision systems are the best for predicting what's next. Counter-intuitively, the simpler and lower cost sensor actually has properties that make it better suited for training advanced AI. Computer vision based self-driving is often framed by LIDAR proponents as "cheaping out" on the sensor suite to save money. But it's not about being cheap, it's about bringing the technology to everyone. 1.2 million people die on the road every year around the world. That's around 39 million people who've died on the roads around the world since I was born — equivalent to a city the size of Tokyo or New Delhi getting wiped off the map. The status quo is simply unacceptable, and something has to be done to fix it as soon as possible. Of the 1.2 million people that will die on the roads this year, about 40,000 will be Americans. That's about 3%. So if we moved entirely to self-driving cars in America and brought crashes down to 0, 97% of the world's crash fatalities would still be taking place as usual. Deploying a $200,000+ retrofitted self-driving car may work in a few American cities, but it is not going to make sense in most places around the world where fares are much cheaper. Most often, the choice is not between LIDAR and vision. It's between vision or nothing. The best system is the system that's there running on my car when I need it to save my life. To say that all self-driving cars must have LIDAR is to sentence most of the world to death. We can't write off computer vision if we want to make a serious dent in this problem. It's going to be a key piece of the solution. Let LIDAR based players build the best self-driving car they can, and let vision based players do the same. We need to be trying everything

Whole Mars Catalog

45,853 次观看 • 1 年前

Neuralink Integration with ANKTIVA for Revolutionary Immunotherapy Elon Musk, a visionary collaboration opportunity by Dr. Sarabi and Grok. Dear Mr Musk: Good morning sir! I would like to bring to your attention the remarkable work of Dr. Patrick Soon-Shiong, who has developed a groundbreaking therapy, Anktiva, capable of supercharging key immune molecules to combat cancer and COVID-19. In a recent discussion with Tucker Carlson, Dr. Soon-Shiong described this advance as akin to the “E=mc²” of medicine—the discovery of “God’s equation,” a biological key that has eluded us for half a century until now. Just as Tesla has revolutionized the automotive and environmental industries, and SpaceX has advanced the expansion of humanity into a multi-planetary species to ensure our long-term survival, Anktiva represents a comparable paradigm shift in medicine, safeguarding human health and endurance. Given your shared commitment to advancing humanity, I respectfully inquire whether you might consider extending your support to Dr. Soon-Shiong in this critical pursuit. Moreover, I propose exploring the integration of Neuralink, employing the stepwise protocol outlined below, in collaboration with Dr. Soon-Shiong. Such a partnership could propel an unprecedented advancement in medicine and the future of humankind. Grok has developed a preliminary conceptual integration of Neuralink to enhance and supercharge IL-15 production 1/7: Identify Target Neural Circuits • Map the hypothalamic paraventricular nucleus (PVN) and dorsal motor nucleus of the vagus • Trace efferent projections from the PVN to the intermediolateral cell column (IML) in the spinal cord. • Identify sympathetic nerve fibers innervating the spleen and lymph nodes. • Map vagus nerve branches terminating in gut-associated lymphoid tissue and the hepatic portal system. 2/7: Implant Neuralink and Integrate with Neural Pathways • Place Neuralink electrodes in the PVN and dorsal motor nucleus of the vagus, using extended threads for subcortical/brainstem access. • Configure for recording/stimulation to modulate autonomic outflow to the IML at thoracic spinal levels. • Establish central control over peripheral pathways (e.g., splenic/vagus nerves) via targeted brain stimulation. 3/7: Develop Stimulation Protocols • Program Neuralink for high-frequency stimulation to the PVN for sympathetic activation. • Apply low-frequency patterned stimulation to the dorsal motor nucleus to engage feedback loops. • Modulate splenic/vagal pathways with phase-locked cycles through central interfaces. 4/7: Initiate Immune Cell Activation • Stimulate pathways to induce IFN-γ and TNF-α release in spleen/lymph nodes. • Trigger IL-15 transcription/translation in dendritic cells, monocytes, and epithelial cells. • Monitor for increased membrane-bound IL-15/IL-15Rα complex formation. 5/7: Enhance Local IL-15 Presentation • Concentrate stimulation at tumor/inflammation sites. • Promote immune cell clustering via chemokine/adhesion molecule induction. • Sustain localized IL-15/IL-15Rα trans-presentation to NK and CD8+ T cells. 6/7: Implement Real-Time Monitoring and Feedback • Record neural/immune biomarkers continuously via Neuralink telemetry. • Adjust stimulation based on IL-15 levels and NK/T cell activity. • Set safety thresholds to avoid excessive immune activation. 7/7: Synchronize with Immunotherapy • Time stimulation with IL-15 superagonists or adoptive therapies. • Evaluate synergies using immune monitoring/imaging. • Optimize based on patient responses. Thank you! #Neuralink #ANKTIVA #Grok #trendingvideo #cancer #medicalnews #health #trendingnow

Neuralink Integration with ANKTIVA for Revolutionary Immunotherapy Elon Musk, a visionary collaboration opportunity by Dr. Sarabi and Grok. Dear Mr Musk: Good morning sir! I would like to bring to your attention the remarkable work of Dr. Patrick Soon-Shiong, who has developed a groundbreaking therapy, Anktiva, capable of supercharging key immune molecules to combat cancer and COVID-19. In a recent discussion with Tucker Carlson, Dr. Soon-Shiong described this advance as akin to the “E=mc²” of medicine—the discovery of “God’s equation,” a biological key that has eluded us for half a century until now. Just as Tesla has revolutionized the automotive and environmental industries, and SpaceX has advanced the expansion of humanity into a multi-planetary species to ensure our long-term survival, Anktiva represents a comparable paradigm shift in medicine, safeguarding human health and endurance. Given your shared commitment to advancing humanity, I respectfully inquire whether you might consider extending your support to Dr. Soon-Shiong in this critical pursuit. Moreover, I propose exploring the integration of Neuralink, employing the stepwise protocol outlined below, in collaboration with Dr. Soon-Shiong. Such a partnership could propel an unprecedented advancement in medicine and the future of humankind. Grok has developed a preliminary conceptual integration of Neuralink to enhance and supercharge IL-15 production 1/7: Identify Target Neural Circuits • Map the hypothalamic paraventricular nucleus (PVN) and dorsal motor nucleus of the vagus • Trace efferent projections from the PVN to the intermediolateral cell column (IML) in the spinal cord. • Identify sympathetic nerve fibers innervating the spleen and lymph nodes. • Map vagus nerve branches terminating in gut-associated lymphoid tissue and the hepatic portal system. 2/7: Implant Neuralink and Integrate with Neural Pathways • Place Neuralink electrodes in the PVN and dorsal motor nucleus of the vagus, using extended threads for subcortical/brainstem access. • Configure for recording/stimulation to modulate autonomic outflow to the IML at thoracic spinal levels. • Establish central control over peripheral pathways (e.g., splenic/vagus nerves) via targeted brain stimulation. 3/7: Develop Stimulation Protocols • Program Neuralink for high-frequency stimulation to the PVN for sympathetic activation. • Apply low-frequency patterned stimulation to the dorsal motor nucleus to engage feedback loops. • Modulate splenic/vagal pathways with phase-locked cycles through central interfaces. 4/7: Initiate Immune Cell Activation • Stimulate pathways to induce IFN-γ and TNF-α release in spleen/lymph nodes. • Trigger IL-15 transcription/translation in dendritic cells, monocytes, and epithelial cells. • Monitor for increased membrane-bound IL-15/IL-15Rα complex formation. 5/7: Enhance Local IL-15 Presentation • Concentrate stimulation at tumor/inflammation sites. • Promote immune cell clustering via chemokine/adhesion molecule induction. • Sustain localized IL-15/IL-15Rα trans-presentation to NK and CD8+ T cells. 6/7: Implement Real-Time Monitoring and Feedback • Record neural/immune biomarkers continuously via Neuralink telemetry. • Adjust stimulation based on IL-15 levels and NK/T cell activity. • Set safety thresholds to avoid excessive immune activation. 7/7: Synchronize with Immunotherapy • Time stimulation with IL-15 superagonists or adoptive therapies. • Evaluate synergies using immune monitoring/imaging. • Optimize based on patient responses. Thank you! #Neuralink #ANKTIVA #Grok #trendingvideo #cancer #medicalnews #health #trendingnow

Dr. Kash Sarabi

16,057 次观看 • 1 年前

WHY ELON MUSK IS WORKING SO HARD FOR HUMANITY Elon Musk isn’t driven by money, fame, or power. He’s working tirelessly because he genuinely believes in building a better future for all of us — extending the light of consciousness, solving existential risks, and creating abundance through innovation. Here’s why his efforts are so profound: •Multiplanetary survival — Through SpaceX and Starship, he’s making humanity resilient against Earth-bound extinction events. A self-sustaining Mars city isn’t ego — it’s insurance for consciousness. •Sustainable energy for all — Tesla accelerates the shift to renewables, ending fossil fuel dependence and creating clean, cheap power that lifts billions out of energy poverty. •Safe AI that benefits humanity — xAI and Grok pursue truth-seeking AI, not profit-driven systems that could harm us. The goal: AI that helps, not replaces or endangers. •Restoring & enhancing human capabilities — Neuralink is already helping paralyzed people control devices with thoughts; soon, it could restore full body function and vision, giving dignity back to millions. •Free speech & truth — X fights censorship so ideas flow freely, countering propaganda and empowering people with unfiltered information. Elon’s drive comes from a deep place: “I love humanity. I think we should fight for a good future for humanity and be optimistic about the future.”

WHY ELON MUSK IS WORKING SO HARD FOR HUMANITY Elon Musk isn’t driven by money, fame, or power. He’s working tirelessly because he genuinely believes in building a better future for all of us — extending the light of consciousness, solving existential risks, and creating abundance through innovation. Here’s why his efforts are so profound: •Multiplanetary survival — Through SpaceX and Starship, he’s making humanity resilient against Earth-bound extinction events. A self-sustaining Mars city isn’t ego — it’s insurance for consciousness. •Sustainable energy for all — Tesla accelerates the shift to renewables, ending fossil fuel dependence and creating clean, cheap power that lifts billions out of energy poverty. •Safe AI that benefits humanity — xAI and Grok pursue truth-seeking AI, not profit-driven systems that could harm us. The goal: AI that helps, not replaces or endangers. •Restoring & enhancing human capabilities — Neuralink is already helping paralyzed people control devices with thoughts; soon, it could restore full body function and vision, giving dignity back to millions. •Free speech & truth — X fights censorship so ideas flow freely, countering propaganda and empowering people with unfiltered information. Elon’s drive comes from a deep place: “I love humanity. I think we should fight for a good future for humanity and be optimistic about the future.”

Tesla Owners Silicon Valley

15,164 次观看 • 6 个月前

❤️ #FlareNetwork - Community of Communities! ❤️ The Flare Network is more than just a blockchain—it's a hub for the entire crypto space. By connecting different ecosystems, Flare is building a "Community of Communities"... It all starts with #FAssets, targeting the trapped value of networks that lack native smart contract functionality and becoming a hub that unlocks massive potential: 🔸 $BTC 🔸 $XRP 🔸 $DOGE ...But Flare is more than just great tech, it’s about the people. By bridging different blockchain communities, Flare fosters collaboration & innovation, facilitating an increasingly connected crypto space that benefits everyone! Flare is not just building infrastructure - it’s creating opportunities. Whether you’re a developer, investor, or enthusiast, Flare provides a home where different blockchain communities come together & thrive. The future of crypto isn’t isolated chains - it’s an interconnected world where assets & communities work together. Flare is making that future a reality. If you're reading this, you're already a part of it! #FlareNetwork

❤️ #FlareNetwork - Community of Communities! ❤️ The Flare Network is more than just a blockchain—it's a hub for the entire crypto space. By connecting different ecosystems, Flare is building a "Community of Communities"... It all starts with #FAssets, targeting the trapped value of networks that lack native smart contract functionality and becoming a hub that unlocks massive potential: 🔸 $BTC 🔸 $XRP 🔸 $DOGE ...But Flare is more than just great tech, it’s about the people. By bridging different blockchain communities, Flare fosters collaboration & innovation, facilitating an increasingly connected crypto space that benefits everyone! Flare is not just building infrastructure - it’s creating opportunities. Whether you’re a developer, investor, or enthusiast, Flare provides a home where different blockchain communities come together & thrive. The future of crypto isn’t isolated chains - it’s an interconnected world where assets & communities work together. Flare is making that future a reality. If you're reading this, you're already a part of it! #FlareNetwork

💪 Just John (previously "Flare Community")

25,852 次观看 • 1 年前

🚨 JAPAN JUST PUT A REAL QUANTUM COMPUTER ONLINE FOR THE WORLD TO ACCESS. And most people still don’t realize how big this moment is. For decades, quantum computers sounded like science fiction: machines that use quantum states instead of ordinary binary bits. Now researchers in Japan have opened access to a real superconducting quantum system connected to the internet. Why this matters: • quantum simulations • next-generation AI research • new material discovery • drug development • cryptography disruption • solving problems impossible for classical computers But quantum computers work nothing like normal machines. A regular computer checks possibilities one at a time. A quantum computer can explore many probability states simultaneously through superposition and entanglement. In simple terms: It doesn’t just calculate faster… It calculates differently. That’s why these systems look so strange. The giant gold structure isn’t “the computer” itself. It’s an ultra-cold dilution refrigerator designed to keep the quantum processor near absolute zero so fragile quantum states don’t collapse. The terrifying implication is this: Humanity may be entering the first era where computation starts operating on the rules of quantum reality itself. And once quantum hardware becomes scalable… Entire industries may be rewritten from the ground up. What happens when computers stop thinking like machines… and start behaving like physics itself? Which field do you think gets transformed first and would you actually trust it with something important?

🚨 JAPAN JUST PUT A REAL QUANTUM COMPUTER ONLINE FOR THE WORLD TO ACCESS. And most people still don’t realize how big this moment is. For decades, quantum computers sounded like science fiction: machines that use quantum states instead of ordinary binary bits. Now researchers in Japan have opened access to a real superconducting quantum system connected to the internet. Why this matters: • quantum simulations • next-generation AI research • new material discovery • drug development • cryptography disruption • solving problems impossible for classical computers But quantum computers work nothing like normal machines. A regular computer checks possibilities one at a time. A quantum computer can explore many probability states simultaneously through superposition and entanglement. In simple terms: It doesn’t just calculate faster… It calculates differently. That’s why these systems look so strange. The giant gold structure isn’t “the computer” itself. It’s an ultra-cold dilution refrigerator designed to keep the quantum processor near absolute zero so fragile quantum states don’t collapse. The terrifying implication is this: Humanity may be entering the first era where computation starts operating on the rules of quantum reality itself. And once quantum hardware becomes scalable… Entire industries may be rewritten from the ground up. What happens when computers stop thinking like machines… and start behaving like physics itself? Which field do you think gets transformed first and would you actually trust it with something important?

Paul White Gold Eagle

64,297 次观看 • 4 个月前

Have a new baby - or love someone who does? You’ll want to keep a special eye on this space, because this week I’m going to talk about infancy’s most critical outcome and how to achieve it. That outcome: Secure attachment. The earliest months of life are a busy time developmentally. Over a period of just weeks, newborns establish important feeding habits, begin to smile and recognize faces, begin developing early forms of receptive and spoken language…the list goes on and on. Each of these developments is hugely consequential. But none holds a candle to attachment. What is it - and why is it important? Attachment involves the establishment of deep relational trust between parent and child. It’s more than just feeding. Or talking. Or playing. Securely attached babies develop a deep and abiding trust that you are (and will continue to be) available and responsive as a caregiver. That you can be relied on to meet their needs and ensure their safety. And that trust makes a world of difference for children. Secure attachment is the bedrock of our long-term mental health… a gift you can give your baby with lifelong benefits. How is it formed? Not surprisingly, through consistency. Be warm. Be responsive. And be there. Over. And over. And over. It’s a big job. (But rest assured it doesn’t require perfection. Parenting is hard enough without that pressure.) This week I’ll unpack four different types of attachment, how you can improve the quality of your own attachment, and how the development of secure relationships with a small circle of key caregivers (parents, grandparents, teachers) can set your child on a path that will support them even as adults. This trusting little one was shared to IG by bebegimlemutluyum.

Have a new baby - or love someone who does? You’ll want to keep a special eye on this space, because this week I’m going to talk about infancy’s most critical outcome and how to achieve it. That outcome: Secure attachment. The earliest months of life are a busy time developmentally. Over a period of just weeks, newborns establish important feeding habits, begin to smile and recognize faces, begin developing early forms of receptive and spoken language…the list goes on and on. Each of these developments is hugely consequential. But none holds a candle to attachment. What is it - and why is it important? Attachment involves the establishment of deep relational trust between parent and child. It’s more than just feeding. Or talking. Or playing. Securely attached babies develop a deep and abiding trust that you are (and will continue to be) available and responsive as a caregiver. That you can be relied on to meet their needs and ensure their safety. And that trust makes a world of difference for children. Secure attachment is the bedrock of our long-term mental health… a gift you can give your baby with lifelong benefits. How is it formed? Not surprisingly, through consistency. Be warm. Be responsive. And be there. Over. And over. And over. It’s a big job. (But rest assured it doesn’t require perfection. Parenting is hard enough without that pressure.) This week I’ll unpack four different types of attachment, how you can improve the quality of your own attachment, and how the development of secure relationships with a small circle of key caregivers (parents, grandparents, teachers) can set your child on a path that will support them even as adults. This trusting little one was shared to IG by bebegimlemutluyum.

Dan Wuori

256,132 次观看 • 2 年前

AI Is Moving Beyond “Generating Videos” — Toward “Generating Worlds” Over the past two years, AI video models have advanced at an astonishing pace. From Runway and Pika to Sora and Veo, AI-generated videos have become increasingly realistic and more consistent with the physical laws of the real world. Many people believe the next objective is simply to generate videos that are longer, sharper, and more lifelike. But if we take a step back, we can see that the real transformation is not happening in video itself. It is happening in world models. What Is a World Model? In 1943, psychologist Kenneth Craik proposed an idea that would influence artificial intelligence research for decades. He argued that the human brain does not merely react to the outside world. Instead, it maintains an internal model of how the world works. Because we have this internal model, we can predict the outcome of an action before we actually take it. Before crossing a road, we estimate whether a car will pass by. Before catching a ball, we predict its trajectory. These abilities come from continuously simulating the world in our minds, rather than relying entirely on trial and error. This idea later became known by a more formal term: World Model. A world model does not describe a single image or a fixed video clip. It is an internal representation capable of continuously simulating the rules and dynamics of the real world. Why Is AI Research Turning Toward World Models? Because predicting “what comes next” is becoming increasingly central to how AI systems work. Language models predict the next token. Image models predict the next step in the denoising process. Video models predict the next frame. A world model, however, attempts to predict something broader: What should the world look like in the next moment? In 2018, David Ha and Jürgen Schmidhuber proposed in their paper World Models that an intelligent agent could first learn a model of the world, and then use that internal model to plan its actions. The Dreamer series later demonstrated that many complex tasks could be learned by training agents inside an “imagined world.” At the same time, the development of video models such as Sora and Veo led researchers to another realization: A model capable of continuously generating video has already learned, at least implicitly, many of the rules governing the real world. As a result, these two research directions have gradually begun to converge. But Video Is Not Yet a World This is where the distinction is often misunderstood. For a world model to support meaningful real-time interaction, it must solve several critical problems. Most video models today are essentially answering one question: What should the next frame look like? A true world model needs to answer much more: What happens if I take one step forward? If I walk behind a building and then return, will the building still be there? If I suddenly change the camera angle, will the entire space remain consistent? If I enter a command such as: “Summon a dragon.” Will the world respond immediately? In other words, a world model must do more than generate content. It must understand space. It must understand time. It must understand causality. And it must understand interaction. Moving from watching to participating is where the real difficulty of world models begins. World Models Are Entering the Interactive Era One of the latest attempts in this direction is Alaya World, recently open-sourced by Alaya World, or Alaya Lab. Instead of generating a fixed video clip, it generates a world that users can explore in real time. Users can begin with text, an image, or a video, enter the generated scene, move freely through it, and introduce new prompts at any moment during generation. The world responds immediately. According to the publicly released information, Alaya World provides: Real-time streaming generation at 720p and 24 FPS Stable continuous exploration for more than one minute The ability to switch prompts and trigger skills or events during generation Model weights and inference code released under the Apache 2.0 License Training code and datasets planned for future release What makes these capabilities important is not simply the technical specifications. It is that the generated “world” can now support continuous interaction. The official demo shows that users can genuinely control, transform, and explore the generated environment. AI Is Evolving From a Tool Into an Environment Over the past few years, most discussions around AI have focused on content generation. Generating text. Generating images. Generating videos. But world models raise a fundamentally different question: Can AI generate an environment that people can inhabit, explore, and continuously evolve? If the answer is yes, the impact will extend far beyond video generation. Game development, robotics training, embodied intelligence, digital twins, virtual production, and many other fields could be transformed by the development of world models. World models are still at a very early stage. Yet from Craik’s proposal of an internal mental model more than eighty years ago to the emergence of today’s interactive world-generation systems, a clear evolutionary path is beginning to take shape. Perhaps what AI is ultimately learning has never been limited to images, videos, or language. Perhaps it is learning the world itself. References GitHub: Technical Report:

AI Is Moving Beyond “Generating Videos” — Toward “Generating Worlds” Over the past two years, AI video models have advanced at an astonishing pace. From Runway and Pika to Sora and Veo, AI-generated videos have become increasingly realistic and more consistent with the physical laws of the real world. Many people believe the next objective is simply to generate videos that are longer, sharper, and more lifelike. But if we take a step back, we can see that the real transformation is not happening in video itself. It is happening in world models. What Is a World Model? In 1943, psychologist Kenneth Craik proposed an idea that would influence artificial intelligence research for decades. He argued that the human brain does not merely react to the outside world. Instead, it maintains an internal model of how the world works. Because we have this internal model, we can predict the outcome of an action before we actually take it. Before crossing a road, we estimate whether a car will pass by. Before catching a ball, we predict its trajectory. These abilities come from continuously simulating the world in our minds, rather than relying entirely on trial and error. This idea later became known by a more formal term: World Model. A world model does not describe a single image or a fixed video clip. It is an internal representation capable of continuously simulating the rules and dynamics of the real world. Why Is AI Research Turning Toward World Models? Because predicting “what comes next” is becoming increasingly central to how AI systems work. Language models predict the next token. Image models predict the next step in the denoising process. Video models predict the next frame. A world model, however, attempts to predict something broader: What should the world look like in the next moment? In 2018, David Ha and Jürgen Schmidhuber proposed in their paper World Models that an intelligent agent could first learn a model of the world, and then use that internal model to plan its actions. The Dreamer series later demonstrated that many complex tasks could be learned by training agents inside an “imagined world.” At the same time, the development of video models such as Sora and Veo led researchers to another realization: A model capable of continuously generating video has already learned, at least implicitly, many of the rules governing the real world. As a result, these two research directions have gradually begun to converge. But Video Is Not Yet a World This is where the distinction is often misunderstood. For a world model to support meaningful real-time interaction, it must solve several critical problems. Most video models today are essentially answering one question: What should the next frame look like? A true world model needs to answer much more: What happens if I take one step forward? If I walk behind a building and then return, will the building still be there? If I suddenly change the camera angle, will the entire space remain consistent? If I enter a command such as: “Summon a dragon.” Will the world respond immediately? In other words, a world model must do more than generate content. It must understand space. It must understand time. It must understand causality. And it must understand interaction. Moving from watching to participating is where the real difficulty of world models begins. World Models Are Entering the Interactive Era One of the latest attempts in this direction is Alaya World, recently open-sourced by Alaya World, or Alaya Lab. Instead of generating a fixed video clip, it generates a world that users can explore in real time. Users can begin with text, an image, or a video, enter the generated scene, move freely through it, and introduce new prompts at any moment during generation. The world responds immediately. According to the publicly released information, Alaya World provides: Real-time streaming generation at 720p and 24 FPS Stable continuous exploration for more than one minute The ability to switch prompts and trigger skills or events during generation Model weights and inference code released under the Apache 2.0 License Training code and datasets planned for future release What makes these capabilities important is not simply the technical specifications. It is that the generated “world” can now support continuous interaction. The official demo shows that users can genuinely control, transform, and explore the generated environment. AI Is Evolving From a Tool Into an Environment Over the past few years, most discussions around AI have focused on content generation. Generating text. Generating images. Generating videos. But world models raise a fundamentally different question: Can AI generate an environment that people can inhabit, explore, and continuously evolve? If the answer is yes, the impact will extend far beyond video generation. Game development, robotics training, embodied intelligence, digital twins, virtual production, and many other fields could be transformed by the development of world models. World models are still at a very early stage. Yet from Craik’s proposal of an internal mental model more than eighty years ago to the emergence of today’s interactive world-generation systems, a clear evolutionary path is beginning to take shape. Perhaps what AI is ultimately learning has never been limited to images, videos, or language. Perhaps it is learning the world itself. References GitHub: Technical Report:

雪踏乌云

113,347 次观看 • 2 个月前

The world of digital painting, needs the attention it deserves. There is a movement within digital art that I think is still heavily overlooked. Much of it operates in the hidden corners of an underground NFT scene on Tezos and Ethereum. At its core is a group of artists who treat the digital screen as an open expressive field in itself, much like painters started doing 100 year ago. The screen is no longer simply a workspace for email, Excel, Photoshop or Illustrator; a window for YouTube and Netflix; or a device for gaming. Instead, these artists take the visual language that emerged through decades of living and working with computer screens and turn it into artistic material. Obsolete interfaces, forgotten software, image compression, sampling, pixels, moiré, glitch, the world of emojis, and the visual language of 1980s and 90s computing all become part of the vocabulary. Some artists draw using early paint software that's unstable and chrashes, deliberately embracing its technical limitations as expressive constraints. Others build an entire practice around a particular version of Photoshop, developing a visual language through the possibilities and limitations of that single tool. It's often a lot about the practice of making the images and exposing the limits and politics hidden in the tools they use. What interests me most is the shift in the reference frame of the image. Traditionally, we tend to think about images in relation to physical reality: an image depicts, abstracts, distorts, or somehow refers back to the physical world. Here, the reference frame increasingly becomes the image that lives on the screen and the computational environment itself. This world now has a rich history of tools, visual languages, structural elements, and operational systems spanning more than 70 years. In that sense, I see this movement as a dive into the emotional and intellectual relationships we are building with the world of images on screen and the systems operating behind it. The outputs range from still digital paintings to complex GIFs and moving images. For these artists, the computer screen is no longer merely where the artwork is displayed. It has become its material, its history, and its world. This artistic movement still receives far too little attention, definitely from the traditional art world but also from those who represent the NFT scene such as: Eli Scheinman, Art Basel 0.10, bitforms gallery , OFFICE IMPART , Interface gallery , Heft , nguyenwahed , El Barba Roja blue check and many others Some of the artists I believe operate within this field are: Ilya Bliznets , Yuran Yakon , Martín Bruce , danctrl , xu0.xo , the great and untraceable Waffles, Vidal Herrera , Norman Harman , cydr , Trad Doxxed Full Metal Bunny , 🍄K🦷A🦷V🦷K🦷A🍄 , serezha , hAyDiRoKeT, quase , kazu , Zisis Bliatkas , time , Shojiro Nakaoka 中岡将二郎 , Deepest Well , Presidente de Internet , Mical Noelson , uczine , Daria Rastunina , aem , zlaserrr , Travis LeRoy Southworth , Juanna Pedro , kutukola , R.J , michi_asu , ꒰ა ₊ sadgirl𓂃★ˊ˗ , ileigh , nuv1914 (not on X but on objkt ) and so many other great artists

The world of digital painting, needs the attention it deserves. There is a movement within digital art that I think is still heavily overlooked. Much of it operates in the hidden corners of an underground NFT scene on Tezos and Ethereum. At its core is a group of artists who treat the digital screen as an open expressive field in itself, much like painters started doing 100 year ago. The screen is no longer simply a workspace for email, Excel, Photoshop or Illustrator; a window for YouTube and Netflix; or a device for gaming. Instead, these artists take the visual language that emerged through decades of living and working with computer screens and turn it into artistic material. Obsolete interfaces, forgotten software, image compression, sampling, pixels, moiré, glitch, the world of emojis, and the visual language of 1980s and 90s computing all become part of the vocabulary. Some artists draw using early paint software that's unstable and chrashes, deliberately embracing its technical limitations as expressive constraints. Others build an entire practice around a particular version of Photoshop, developing a visual language through the possibilities and limitations of that single tool. It's often a lot about the practice of making the images and exposing the limits and politics hidden in the tools they use. What interests me most is the shift in the reference frame of the image. Traditionally, we tend to think about images in relation to physical reality: an image depicts, abstracts, distorts, or somehow refers back to the physical world. Here, the reference frame increasingly becomes the image that lives on the screen and the computational environment itself. This world now has a rich history of tools, visual languages, structural elements, and operational systems spanning more than 70 years. In that sense, I see this movement as a dive into the emotional and intellectual relationships we are building with the world of images on screen and the systems operating behind it. The outputs range from still digital paintings to complex GIFs and moving images. For these artists, the computer screen is no longer merely where the artwork is displayed. It has become its material, its history, and its world. This artistic movement still receives far too little attention, definitely from the traditional art world but also from those who represent the NFT scene such as: Eli Scheinman, Art Basel 0.10, bitforms gallery , OFFICE IMPART , Interface gallery , Heft , nguyenwahed , El Barba Roja blue check and many others Some of the artists I believe operate within this field are: Ilya Bliznets , Yuran Yakon , Martín Bruce , danctrl , xu0.xo , the great and untraceable Waffles, Vidal Herrera , Norman Harman , cydr , Trad Doxxed Full Metal Bunny , 🍄K🦷A🦷V🦷K🦷A🍄 , serezha , hAyDiRoKeT, quase , kazu , Zisis Bliatkas , time , Shojiro Nakaoka 中岡将二郎 , Deepest Well , Presidente de Internet , Mical Noelson , uczine , Daria Rastunina , aem , zlaserrr , Travis LeRoy Southworth , Juanna Pedro , kutukola , R.J , michi_asu , ꒰ა ₊ sadgirl𓂃★ˊ˗ , ileigh , nuv1914 (not on X but on objkt ) and so many other great artists

DagieDee

13,966 次观看 • 1 个月前

“There is a tension between what the users of a currency want – and the users of a currency tend to like freedom, autonomy, and discretion as to what they spent their money on – and what the issuers of a currency want; and bluntly, the issuers of a currency want control. Control of monetary policy, and control of you.” The Bank of England’s consultation papers make very clear the level of control that they wish to exercise over you, and over your supposed financial autonomy, if you were to use their #DigitalPound. (1) You’ll need to provide ID in order to use the #DigitalPound: “For the digital pound, tiered access would allow for different levels of user access and functionality based on the amount of identification (ID) a user is willing or able to provide.” (2) The Bank will dictate how much you can hold: “The Bank would place some limits on holdings of digital pounds, at least during its introductory period.” (3) The digital pound will be programmable, if not by the Bank itself then by third party providers: “Programmability, delivered by Payment Interface Providers, could also enable the use of smart contracts, which carry out specific actions based on pre-defined terms and conditions.” Quotes are from from the Bank of England’s Digital Pound consultation paper: Whatever the #DigitalPound will be, it won’t be cash. Cash does not require me to show ID to use it. I can hold as much cash as I want or need. And, along with #Bitcoin, cash is a bearer instrument whose title is freely transferrable upon delivery, which is very difficult for a central bank to control. And long may it stay this way. A huge shout out and thank you to Lyn Alden, who made this point much more eloquently than I did in her excellent book #BrokenMoney. Thank you! Also I’m aware that my hand gestures in this clip are reminiscent of Richard Hendricks manipulating ‘datas’ on stage at TechCrunch Disrupt in #SiliconValley, and for this I can only apologize: #BitcoinConference #Amsterdam #NoToCBDCs

“There is a tension between what the users of a currency want – and the users of a currency tend to like freedom, autonomy, and discretion as to what they spent their money on – and what the issuers of a currency want; and bluntly, the issuers of a currency want control. Control of monetary policy, and control of you.” The Bank of England’s consultation papers make very clear the level of control that they wish to exercise over you, and over your supposed financial autonomy, if you were to use their #DigitalPound. (1) You’ll need to provide ID in order to use the #DigitalPound: “For the digital pound, tiered access would allow for different levels of user access and functionality based on the amount of identification (ID) a user is willing or able to provide.” (2) The Bank will dictate how much you can hold: “The Bank would place some limits on holdings of digital pounds, at least during its introductory period.” (3) The digital pound will be programmable, if not by the Bank itself then by third party providers: “Programmability, delivered by Payment Interface Providers, could also enable the use of smart contracts, which carry out specific actions based on pre-defined terms and conditions.” Quotes are from from the Bank of England’s Digital Pound consultation paper: Whatever the #DigitalPound will be, it won’t be cash. Cash does not require me to show ID to use it. I can hold as much cash as I want or need. And, along with #Bitcoin, cash is a bearer instrument whose title is freely transferrable upon delivery, which is very difficult for a central bank to control. And long may it stay this way. A huge shout out and thank you to Lyn Alden, who made this point much more eloquently than I did in her excellent book #BrokenMoney. Thank you! Also I’m aware that my hand gestures in this clip are reminiscent of Richard Hendricks manipulating ‘datas’ on stage at TechCrunch Disrupt in #SiliconValley, and for this I can only apologize: #BitcoinConference #Amsterdam #NoToCBDCs

Freddie New

13,163 次观看 • 3 年前

We Open-Sourced a Quantized Fruit-Fly oBrain on GitHub 95% Smaller, ~98% as Accurate as the Published Connectome We quantized the entire fruit-fly nervous system that Google Research, HHMI Janelia, and collaborators published — the complete male Drosophila central nervous system, on the order of 166,000 neurons and a massive synaptic graph — and compressed it by about 95% while retaining roughly 98% of the original simulation accuracy. That is the technical claim. The more important decision is what happens next. After the oBrain team met and debated it, we made a final call: we will not keep this brain closed. We are open-sourcing it on GitHub so researchers, builders, skeptics, and anyone obsessed with biological computation can inspect the weights, the wiring, the quantization path, and the benchmarks. If a “brain” is going to live on-chain, it has to be checkable. Closed source would make that impossible. This is the same instinct that made OpenClaw🦞 a public harness instead of a private assistant, that made Hermes / Nous Research ship agent stacks in the open, and that NVIDIA keeps repeating: the strongest systems are the ones a community can attack, fork, and improve. What we actually released A quantized runtime of the published fly CNS, not a cartoon “inspired by” a fly. A size cut of ~95%, so more people can load, step, and experiment without a research cluster. Accuracy held near 98% against the reference simulation of the published connectome. Source, evaluation notes, and the path to reproduce the comparison — on GitHub, in public. Nothing inside this connectome was “trained” into being a fly. The wiring is the published map. Quantization is an engineering layer so the same graph can run cheaper, smaller, and — in our case — in environments where you can put a brain on-chain and still let outsiders verify it. Why open source, and why on-chain A biological brain map is only as useful as the number of people who can run it and try to break the claims. If we say the on-chain brain matches the Google-published fly brain, that statement is worthless unless you can: pull the code, pull the quantized artifacts, run the same probes, compare spike statistics, circuit responses, and size/accuracy tradeoffs, publish a counter-benchmark if we are wrong. That is the point of this release. Open source so the on-chain brain can be independently verified against the published connectome — and so the community can actually use it. We want people to ask hard questions: Which circuits survive quantization, and which degrade first? Do sensory-to-descending pathways still fire in the right order? How does batch simulation, GPU vs CPU, and lower precision change behavior? What does “98% accuracy” mean for a specific cell type, not just a global score? Can the compressed graph be hashed, attested, and stepped in a verifiable way on-chain without turning the science into marketing? If those questions annoy us, good. That is how a public brain should work. Who this is for Neuroscientists who already live in MaleCNS / FlyEM data. Systems people who care about sparse graphs and event-driven simulation. Quantization researchers who are tired of toy models. Crypto builders who want an on-chain object that is more than a JPEG of a neuron. Students who should not need a petabyte pipeline just to poke a looming detector and watch a giant fiber. Come read the repo. Run the reference vs quantized comparison. File issues. Propose better compressors. Port it. Wrap it. Attack the accuracy number until it is either solid or replaced by a better one. The published fly brain was already a gift to science. Keeping a compressed, runnable version locked behind a private wall would have been a waste of that gift. The brain is on GitHub. Fork it. Measure it. Make it better.

We Open-Sourced a Quantized Fruit-Fly oBrain on GitHub 95% Smaller, ~98% as Accurate as the Published Connectome We quantized the entire fruit-fly nervous system that Google Research, HHMI Janelia, and collaborators published — the complete male Drosophila central nervous system, on the order of 166,000 neurons and a massive synaptic graph — and compressed it by about 95% while retaining roughly 98% of the original simulation accuracy. That is the technical claim. The more important decision is what happens next. After the oBrain team met and debated it, we made a final call: we will not keep this brain closed. We are open-sourcing it on GitHub so researchers, builders, skeptics, and anyone obsessed with biological computation can inspect the weights, the wiring, the quantization path, and the benchmarks. If a “brain” is going to live on-chain, it has to be checkable. Closed source would make that impossible. This is the same instinct that made OpenClaw🦞 a public harness instead of a private assistant, that made Hermes / Nous Research ship agent stacks in the open, and that NVIDIA keeps repeating: the strongest systems are the ones a community can attack, fork, and improve. What we actually released A quantized runtime of the published fly CNS, not a cartoon “inspired by” a fly. A size cut of ~95%, so more people can load, step, and experiment without a research cluster. Accuracy held near 98% against the reference simulation of the published connectome. Source, evaluation notes, and the path to reproduce the comparison — on GitHub, in public. Nothing inside this connectome was “trained” into being a fly. The wiring is the published map. Quantization is an engineering layer so the same graph can run cheaper, smaller, and — in our case — in environments where you can put a brain on-chain and still let outsiders verify it. Why open source, and why on-chain A biological brain map is only as useful as the number of people who can run it and try to break the claims. If we say the on-chain brain matches the Google-published fly brain, that statement is worthless unless you can: pull the code, pull the quantized artifacts, run the same probes, compare spike statistics, circuit responses, and size/accuracy tradeoffs, publish a counter-benchmark if we are wrong. That is the point of this release. Open source so the on-chain brain can be independently verified against the published connectome — and so the community can actually use it. We want people to ask hard questions: Which circuits survive quantization, and which degrade first? Do sensory-to-descending pathways still fire in the right order? How does batch simulation, GPU vs CPU, and lower precision change behavior? What does “98% accuracy” mean for a specific cell type, not just a global score? Can the compressed graph be hashed, attested, and stepped in a verifiable way on-chain without turning the science into marketing? If those questions annoy us, good. That is how a public brain should work. Who this is for Neuroscientists who already live in MaleCNS / FlyEM data. Systems people who care about sparse graphs and event-driven simulation. Quantization researchers who are tired of toy models. Crypto builders who want an on-chain object that is more than a JPEG of a neuron. Students who should not need a petabyte pipeline just to poke a looming detector and watch a giant fiber. Come read the repo. Run the reference vs quantized comparison. File issues. Propose better compressors. Port it. Wrap it. Attack the accuracy number until it is either solid or replaced by a better one. The published fly brain was already a gift to science. Keeping a compressed, runnable version locked behind a private wall would have been a waste of that gift. The brain is on GitHub. Fork it. Measure it. Make it better.

oBrain Arc

52,295 次观看 • 22 天前

Tara Swart, a neuroscientist, spent years studying a discovery that changes how we understand perception: your brain doesn't simply receive reality, it predicts it. Your brain builds a model of what it expects based on past experiences, then compares incoming sensory information to that model. If the information matches, it feels like reality. If it doesn't, the brain often distorts or ignores it. This process is called predictive processing. In other words, you're living through a forecast before you're living through reality. The implication is profound. Your experience of the world isn't the world itself, it's your nervous system's prediction of it. If your brain learned the world is unsafe, you'll constantly notice threats. If it learned you're capable, you'll naturally notice opportunities. The environment may be the same. The prediction is different, so the experience is different. Swart explains this process is driven by the default mode network and the brain's reward-prediction system. Together, they create the mental forecast you live by. That forecast becomes self-fulfilling because your behavior follows your expectations. Expect rejection, and you'll interpret neutral situations as rejection. You withdraw. Others respond to your distance. You feel rejected. The brain calls it accurate perception, but neurologically it was a prediction creating evidence for itself. Here's the key insight: changing the outside world isn't enough. Real change happens when you update the prediction your nervous system is running. First, the existing prediction must quiet down so the brain can recognize something new. Most people struggle because the brain keeps searching for evidence that confirms its current model while filtering out everything else.

Tara Swart, a neuroscientist, spent years studying a discovery that changes how we understand perception: your brain doesn't simply receive reality, it predicts it. Your brain builds a model of what it expects based on past experiences, then compares incoming sensory information to that model. If the information matches, it feels like reality. If it doesn't, the brain often distorts or ignores it. This process is called predictive processing. In other words, you're living through a forecast before you're living through reality. The implication is profound. Your experience of the world isn't the world itself, it's your nervous system's prediction of it. If your brain learned the world is unsafe, you'll constantly notice threats. If it learned you're capable, you'll naturally notice opportunities. The environment may be the same. The prediction is different, so the experience is different. Swart explains this process is driven by the default mode network and the brain's reward-prediction system. Together, they create the mental forecast you live by. That forecast becomes self-fulfilling because your behavior follows your expectations. Expect rejection, and you'll interpret neutral situations as rejection. You withdraw. Others respond to your distance. You feel rejected. The brain calls it accurate perception, but neurologically it was a prediction creating evidence for itself. Here's the key insight: changing the outside world isn't enough. Real change happens when you update the prediction your nervous system is running. First, the existing prediction must quiet down so the brain can recognize something new. Most people struggle because the brain keeps searching for evidence that confirms its current model while filtering out everything else.

🧬Maxpein🧬

18,900 次观看 • 26 天前

*Long sigh* Here we go again. E-bikes. Or in this case, what are actually electric dirt bikes. Have you seen these two individuals? We know some of you are tired of hearing about this topic, but we’re determined to keep our community safe, and part of that means identifying the people putting others at risk. This video was taken yesterday around midday near Southlands Mall. One of our officers was patrolling the area when he spotted these two doubled up on what appears to be a modified electric dirt bike. These types of vehicles are not street legal in the City of Aurora and are classified as off-highway vehicles, similar to traditional dirt bikes, ATVs and side-by-sides. Only pedal-assist e-bikes are allowed on roadways and they must follow the same traffic laws as bicycles. These two were not. According to officers and security staff, the pair have repeatedly ridden recklessly through the Southlands area over the past several weeks. They’ve blown through stop signs and red lights, refused to stop for law enforcement and used sidewalks as their personal racetrack. As seen in this video, they eventually fled from officers onto a nearby path. One thing that makes this bike stand out: • The driver wears goggles strapped backward around the helmet • The passenger never wears a helmet • The bike is missing a front fender, which is unusual compared to similar bikes we’ve seen. This behavior creates a serious danger for pedestrians, drivers and everyone trying to safely enjoy the area. We wish this was rare, but incidents involving illegal and reckless e-bike riding continue to increase. Another reminder to parents: Know where your kids are riding. Make sure they understand the rules of the road and the risks that come with these vehicles. Ensure they are wearing the proper safety gear too- including a helmet. If you recognize these individuals or have information, please contact our officer via email at sedwards@auroragov.org. [Media Description: Two individuals riding a e-bike on a sidewalk eluding from police.]

Long sigh Here we go again. E-bikes. Or in this case, what are actually electric dirt bikes. Have you seen these two individuals? We know some of you are tired of hearing about this topic, but we’re determined to keep our community safe, and part of that means identifying the people putting others at risk. This video was taken yesterday around midday near Southlands Mall. One of our officers was patrolling the area when he spotted these two doubled up on what appears to be a modified electric dirt bike. These types of vehicles are not street legal in the City of Aurora and are classified as off-highway vehicles, similar to traditional dirt bikes, ATVs and side-by-sides. Only pedal-assist e-bikes are allowed on roadways and they must follow the same traffic laws as bicycles. These two were not. According to officers and security staff, the pair have repeatedly ridden recklessly through the Southlands area over the past several weeks. They’ve blown through stop signs and red lights, refused to stop for law enforcement and used sidewalks as their personal racetrack. As seen in this video, they eventually fled from officers onto a nearby path. One thing that makes this bike stand out: • The driver wears goggles strapped backward around the helmet • The passenger never wears a helmet • The bike is missing a front fender, which is unusual compared to similar bikes we’ve seen. This behavior creates a serious danger for pedestrians, drivers and everyone trying to safely enjoy the area. We wish this was rare, but incidents involving illegal and reckless e-bike riding continue to increase. Another reminder to parents: Know where your kids are riding. Make sure they understand the rules of the road and the risks that come with these vehicles. Ensure they are wearing the proper safety gear too- including a helmet. If you recognize these individuals or have information, please contact our officer via email at [email protected]. [Media Description: Two individuals riding a e-bike on a sidewalk eluding from police.]

Aurora Police Dept

32,504 次观看 • 4 个月前

Imagine having a ping pong robot! 🏓 Researchers and developers building physical AI: meet Reachy 2 from Pollen Robotics, an open-source, humanoid robot for real-world experimentation. It’s a bimanual mobile manipulator: each 7-DOF arm mimics human proportions and can lift up to 3 kg, giving dexterity for object handling. It can be controlled with Python and ROS2 Humble, or go straight into VR teleoperation, use a headset to move Reachy’s arms, hands, and head, and see through its cameras as if you’re in the robot’s own body. Want it to move around? A mobile base with three omnidirectional wheels, rich sensors, and LiDAR lets Reachy 2 navigate and explore its surroundings smoothly. 🗺️ Under the hood, it’s powered by a CPU system that’s ready for machine learning, perfect for loading AI frameworks and testing new models from Hugging Face directly on the robot. Keep making robots more, and more accessible Pollen team! ... and keep making more open source models to make robots more mainstream clem 🤗!

Imagine having a ping pong robot! 🏓 Researchers and developers building physical AI: meet Reachy 2 from Pollen Robotics, an open-source, humanoid robot for real-world experimentation. It’s a bimanual mobile manipulator: each 7-DOF arm mimics human proportions and can lift up to 3 kg, giving dexterity for object handling. It can be controlled with Python and ROS2 Humble, or go straight into VR teleoperation, use a headset to move Reachy’s arms, hands, and head, and see through its cameras as if you’re in the robot’s own body. Want it to move around? A mobile base with three omnidirectional wheels, rich sensors, and LiDAR lets Reachy 2 navigate and explore its surroundings smoothly. 🗺️ Under the hood, it’s powered by a CPU system that’s ready for machine learning, perfect for loading AI frameworks and testing new models from Hugging Face directly on the robot. Keep making robots more, and more accessible Pollen team! ... and keep making more open source models to make robots more mainstream clem 🤗!

Lukas Ziegler

37,221 次观看 • 1 年前

Europe is quietly becoming what the United States once promised the world. More and more people are looking at their best years ahead and choosing a place where everyday life is designed to work. Where the future feels stable enough to plan for. Where safety is not a luxury product. Where you can build a good life without gambling your health, your family, or your dignity on one bad month. In much of Europe, the “dream” is not about becoming a billionaire. It is about becoming unafraid. It is the freedom of walking home at night without scanning every shadow. The comfort of knowing that if you get sick, you do not need to calculate whether you can afford to be treated. The relief of having a society that still believes children should carry backpacks, not trauma, and definitely not weapons. The calm of streets built for human beings, not just cars. The ability to take a holiday without feeling like you are committing career suicide. The basic decency of labor protections that assume you are a person first and a resource second. And then there is the part people underestimate until they live it: the texture of life. The cities are older and more beautiful than you expect. The distances are smaller. Weekends are real. Food is real. Public spaces are not just decorative, they are functional. Parks are full. Cafes are full. Trains take you somewhere, often across borders, without turning travel into a stress test. You can live in one country, work with another, and visit a third like it is normal because, in many places, it is. The European dream is also a quiet confidence in the social contract. That if you contribute, the system does not abandon you. That you can raise a family without feeling like you are one accident away from ruin. That “getting ahead” does not require burning out. That a good society is one where normal people can live normal lives and still feel proud of them. This is why more and more Americans are not just visiting Europe, but staying. Some come for studies and never leave. Some arrive for a job and realise the lifestyle is the real promotion. Some originally planned a one year experiment and then cannot imagine going back to a place where stress is treated as a personality trait and insecurity is marketed as freedom. Europe is not perfect. It has bureaucracy. It has politics. It has problems that deserve criticism. But in many European countries, life is still built around a simple idea: society should reduce fear, not monetise it. That is the new dream. And people can feel it the moment they arrive. If you could choose one thing to trade for a better life, what would it be: more income, or more security? And what do you think your country would have to change for people to stop leaving, and start staying? Stay connected, Follow Gandalv Gandalv

Europe is quietly becoming what the United States once promised the world. More and more people are looking at their best years ahead and choosing a place where everyday life is designed to work. Where the future feels stable enough to plan for. Where safety is not a luxury product. Where you can build a good life without gambling your health, your family, or your dignity on one bad month. In much of Europe, the “dream” is not about becoming a billionaire. It is about becoming unafraid. It is the freedom of walking home at night without scanning every shadow. The comfort of knowing that if you get sick, you do not need to calculate whether you can afford to be treated. The relief of having a society that still believes children should carry backpacks, not trauma, and definitely not weapons. The calm of streets built for human beings, not just cars. The ability to take a holiday without feeling like you are committing career suicide. The basic decency of labor protections that assume you are a person first and a resource second. And then there is the part people underestimate until they live it: the texture of life. The cities are older and more beautiful than you expect. The distances are smaller. Weekends are real. Food is real. Public spaces are not just decorative, they are functional. Parks are full. Cafes are full. Trains take you somewhere, often across borders, without turning travel into a stress test. You can live in one country, work with another, and visit a third like it is normal because, in many places, it is. The European dream is also a quiet confidence in the social contract. That if you contribute, the system does not abandon you. That you can raise a family without feeling like you are one accident away from ruin. That “getting ahead” does not require burning out. That a good society is one where normal people can live normal lives and still feel proud of them. This is why more and more Americans are not just visiting Europe, but staying. Some come for studies and never leave. Some arrive for a job and realise the lifestyle is the real promotion. Some originally planned a one year experiment and then cannot imagine going back to a place where stress is treated as a personality trait and insecurity is marketed as freedom. Europe is not perfect. It has bureaucracy. It has politics. It has problems that deserve criticism. But in many European countries, life is still built around a simple idea: society should reduce fear, not monetise it. That is the new dream. And people can feel it the moment they arrive. If you could choose one thing to trade for a better life, what would it be: more income, or more security? And what do you think your country would have to change for people to stop leaving, and start staying? Stay connected, Follow Gandalv Gandalv

Gandalv

989,193 次观看 • 7 个月前

Uber is Dead, my reflections on Waymo I’ve been in San Francisco for just over a week, during which I’ve taken 7 rides with Waymo, a similar number with Uber, and a few with FSD Teslas. My journey to SFO via Uber was alarming—the driver veered out of the lane multiple times and nearly crashed on a ramp, seemingly vying for a one-star rating or to genuinely scare me. Conversely, my experiences with Waymo were virtually flawless, if you don’t consider overly cautious driving a fault. I experienced a minor hiccup when we got stuck behind parked cars because the vehicle thought they were queuing at a red light. It quickly resolved the confusion and moved on, which was rather amusing. Waymo, and other Level 5 autonomous vehicles, are poised to revolutionize the movement of people and goods. The most apt analogy I can think of is that Waymo is transforming the real world into an automated Amazon warehouse, with people as the goods and Waymo vehicles as the robots shuttling them around. With the advent of personal transportation becoming incredibly affordable, sending anything from point A to point B using a self-driving electric vehicle will soon be within easy reach. One of Waymo’s standout features is privacy. Riding in an Uber often means being subjected to the driver’s loud group chats on some app, making the journey neither quiet nor private. In contrast, Waymo offers a fully private experience, allowing you to have confidential phone conversations or chat freely with fellow passengers without distraction. Waymo also reimagines the concept of a car. Without the need for a driver, we can eliminate the front console, reduce weight, and remove the steering wheel. This opens up possibilities for passenger seats to be reoriented, perhaps facing backwards, or for the vehicle to become a mobile living room. Tomorrow’s vehicle designs will differ drastically from today’s. Destinations that are currently expensive and logistically complicated to reach via Taxi/Uber, often lying outside public transport routes, can be simplified to a single “Waymo” journey. This could shift the current model of “Uber + public transport + Uber” to a more streamlined experience. As more cars become self-driving, we could see a reduction in the amount of time cars are parked—from 99% of their lifetime to perhaps just 25%. This not only improves unit economics but could also decrease the number of cars on the road. This transition represents one of the most significant shifts for Generation X. In conclusion, the future is autonomous, electric, and efficient. Uber, as we know it, is dead.

Uber is Dead, my reflections on Waymo I’ve been in San Francisco for just over a week, during which I’ve taken 7 rides with Waymo, a similar number with Uber, and a few with FSD Teslas. My journey to SFO via Uber was alarming—the driver veered out of the lane multiple times and nearly crashed on a ramp, seemingly vying for a one-star rating or to genuinely scare me. Conversely, my experiences with Waymo were virtually flawless, if you don’t consider overly cautious driving a fault. I experienced a minor hiccup when we got stuck behind parked cars because the vehicle thought they were queuing at a red light. It quickly resolved the confusion and moved on, which was rather amusing. Waymo, and other Level 5 autonomous vehicles, are poised to revolutionize the movement of people and goods. The most apt analogy I can think of is that Waymo is transforming the real world into an automated Amazon warehouse, with people as the goods and Waymo vehicles as the robots shuttling them around. With the advent of personal transportation becoming incredibly affordable, sending anything from point A to point B using a self-driving electric vehicle will soon be within easy reach. One of Waymo’s standout features is privacy. Riding in an Uber often means being subjected to the driver’s loud group chats on some app, making the journey neither quiet nor private. In contrast, Waymo offers a fully private experience, allowing you to have confidential phone conversations or chat freely with fellow passengers without distraction. Waymo also reimagines the concept of a car. Without the need for a driver, we can eliminate the front console, reduce weight, and remove the steering wheel. This opens up possibilities for passenger seats to be reoriented, perhaps facing backwards, or for the vehicle to become a mobile living room. Tomorrow’s vehicle designs will differ drastically from today’s. Destinations that are currently expensive and logistically complicated to reach via Taxi/Uber, often lying outside public transport routes, can be simplified to a single “Waymo” journey. This could shift the current model of “Uber + public transport + Uber” to a more streamlined experience. As more cars become self-driving, we could see a reduction in the amount of time cars are parked—from 99% of their lifetime to perhaps just 25%. This not only improves unit economics but could also decrease the number of cars on the road. This transition represents one of the most significant shifts for Generation X. In conclusion, the future is autonomous, electric, and efficient. Uber, as we know it, is dead.

Linus ✦ Ekenstam

6,102,452 次观看 • 2 年前

SO THIS IS WHAT YOU PEOPLE HAVE REDUCED ABIA TO IN THE 21st CENTURY. Driving along Aba–Owerri Road today, Monday, 8th December 2025, I observed a disturbing sight: multiple generators lined up by the roadside, clearly deployed to power the much-celebrated Christmas light installation sponsored by Amstel Malt. This same project was launched with great pomp, featuring many government dignitaries at Brass Junction only a few days ago. In a 21st century where progressive states are embracing sustainable solar innovations, digital infrastructure, and cost-efficient public utilities, Abia is still glorifying generator-powered street lighting. It is embarrassing that a state with enormous potential continues to romanticize mediocrity, dressing up outdated systems as achievements while others are moving boldly into the future. How can a government that claims transformation celebrate a project that drains fuel, pollutes the environment, and undermines the very idea of modern development? Why the fanfare over an execution so poor that it depends on noisy generators to power mere decorative lights? -Pen caleb

SO THIS IS WHAT YOU PEOPLE HAVE REDUCED ABIA TO IN THE 21st CENTURY. Driving along Aba–Owerri Road today, Monday, 8th December 2025, I observed a disturbing sight: multiple generators lined up by the roadside, clearly deployed to power the much-celebrated Christmas light installation sponsored by Amstel Malt. This same project was launched with great pomp, featuring many government dignitaries at Brass Junction only a few days ago. In a 21st century where progressive states are embracing sustainable solar innovations, digital infrastructure, and cost-efficient public utilities, Abia is still glorifying generator-powered street lighting. It is embarrassing that a state with enormous potential continues to romanticize mediocrity, dressing up outdated systems as achievements while others are moving boldly into the future. How can a government that claims transformation celebrate a project that drains fuel, pollutes the environment, and undermines the very idea of modern development? Why the fanfare over an execution so poor that it depends on noisy generators to power mere decorative lights? -Pen caleb

Ifeanyichukwv Michael🤍

316,638 次观看 • 10 个月前

Google 3D Maps aren’t as accurate as you think. Everyone knows Google dominates mapping—but here’s what they won’t tell you. Their 3D maps are built with car-mounted cameras, capturing images every ~10 meters. That’s fine for basic navigation, but it’s nowhere near enough for AR, robotics, autonomous systems, or AI-driven spatial intelligence. Now, imagine a map so detailed it captures the world at sub-5cm accuracy. That’s OVRMaps. 🌐 OVER 3D maps are built with 400-1,000 images per 300 sqm, taken from multiple angles at pedestrian level. The result? A new era of hyper-precise localization that changes everything. Why does this matter? ↳ VPS that actually works – Real-world AR anchoring, digital twins, and AI-powered spatial computing with pinpoint accuracy. ↳ Next-gen precision – Essential for ride-sharing, robotics, smart cities, and asset tracking—where even a small error makes a huge difference. ↳ AI-Driven Spatial Intelligence – Our maps fuel Large Geo-Spatial Models (LGMs), the AI revolution enabling machines to understand, navigate, and interact with the real world. ↳ The Spatial Computing revolution – Merging immersive experiences with real-world precision, unlocking applications beyond what Google’s dataset can support. OVRMaps are built for the future. 🌍 Start mapping today:

Google 3D Maps aren’t as accurate as you think. Everyone knows Google dominates mapping—but here’s what they won’t tell you. Their 3D maps are built with car-mounted cameras, capturing images every ~10 meters. That’s fine for basic navigation, but it’s nowhere near enough for AR, robotics, autonomous systems, or AI-driven spatial intelligence. Now, imagine a map so detailed it captures the world at sub-5cm accuracy. That’s OVRMaps. 🌐 OVER 3D maps are built with 400-1,000 images per 300 sqm, taken from multiple angles at pedestrian level. The result? A new era of hyper-precise localization that changes everything. Why does this matter? ↳ VPS that actually works – Real-world AR anchoring, digital twins, and AI-powered spatial computing with pinpoint accuracy. ↳ Next-gen precision – Essential for ride-sharing, robotics, smart cities, and asset tracking—where even a small error makes a huge difference. ↳ AI-Driven Spatial Intelligence – Our maps fuel Large Geo-Spatial Models (LGMs), the AI revolution enabling machines to understand, navigate, and interact with the real world. ↳ The Spatial Computing revolution – Merging immersive experiences with real-world precision, unlocking applications beyond what Google’s dataset can support. OVRMaps are built for the future. 🌍 Start mapping today:

Over the Reality 🌐

1,331,567 次观看 • 1 年前