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Same neuron

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𝑵𝒆𝒏𝒆 ✖️💚

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12,108 次观看 • 1 个月前 •via X (Twitter)

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i mean its not about the movements per se but joe jonas and sophie turner are the definition of soulmates sharing the same neuron
1:03

i mean its not about the movements per se but joe jonas and sophie turner are the definition of soulmates sharing the same neuron

AJB

498,977 次观看 • 3 年前

"I don’t think there’s any reason why a machine shouldn’t have consciousness. If you swapped out one neuron with an artificial neuron that acts in all the same ways, would you lose consciousness?" ~ Geoffrey Hinton A fascinating discussion in this video. --- From the 'The Diary Of A CEO' YT channel
4:10

"I don’t think there’s any reason why a machine shouldn’t have consciousness. If you swapped out one neuron with an artificial neuron that acts in all the same ways, would you lose consciousness?" ~ Geoffrey Hinton A fascinating discussion in this video. --- From the 'The Diary Of A CEO' YT channel

Rohan Paul

33,407 次观看 • 10 个月前

Zendaya: My*, my family will know.” “My husband” I imitate other people’s laughter and go HAHAHA, my family knows and asks “why do you do that?”… Tom Holland just accepts the madness Tom: Yes, she’s really good at it… THEY SHARE THE SAME NEURON, HAHAHAHAHAHAHHAHAHAHAHAHA I CAN’T TAKE IT
0:24

Zendaya: My*, my family will know.” “My husband” I imitate other people’s laughter and go HAHAHA, my family knows and asks “why do you do that?”… Tom Holland just accepts the madness Tom: Yes, she’s really good at it… THEY SHARE THE SAME NEURON, HAHAHAHAHAHAHHAHAHAHAHAHA I CAN’T TAKE IT

nah

394,348 次观看 • 1 个月前

Anthropic pays its ML engineers $500K+/year to deploy what Percy Liang just taught for free in Lecture 3 of CS221. 80 minutes. one whiteboard. everything between "a neuron" and the model running in your IDE right now. three things click after this one: / why two Claude prompts that "mean the same thing" land in different regions of weight space / why fine-tuning sometimes makes a model dumber, not smarter / what RLHF actually changes when Anthropic aligns Claude same $90K Stanford sequence. lecture 3 of ~20. free. the gap between "using Claude" and "understanding it" is exactly one lecture wide.
1:12:27

Anthropic pays its ML engineers $500K+/year to deploy what Percy Liang just taught for free in Lecture 3 of CS221. 80 minutes. one whiteboard. everything between "a neuron" and the model running in your IDE right now. three things click after this one: / why two Claude prompts that "mean the same thing" land in different regions of weight space / why fine-tuning sometimes makes a model dumber, not smarter / what RLHF actually changes when Anthropic aligns Claude same $90K Stanford sequence. lecture 3 of ~20. free. the gap between "using Claude" and "understanding it" is exactly one lecture wide.

dunik

24,391 次观看 • 3 个月前

We often hear that machine learning models "learn patterns in data". But what does that actually look like in geometry? If you dropped a little elastic mesh into a cloud of points and let it learn, how would it fold itself to match the shape of the data? In this scene we watch a self-organizing map...a simple unsupervised neural model...learn the shape of a two-dimensional dataset arranged in a spiral arm. On top of this, we lay down a square grid of neurons whose weights live in the same plane. At the start, this grid is just a flat net floating across the cloud...it knows nothing about the structure underneath. Learning is a repeated game: pick a random data point, find the neuron whose weight is closest, and then nudge that neuron and its neighbours toward the point. Do this again and again, while slowly shrinking how far the neighbourhood influence spreads. #MachineLearning #ManifoldLearning #UnsupervisedLearning #NeuralMaps #GeometricML
0:59

We often hear that machine learning models "learn patterns in data". But what does that actually look like in geometry? If you dropped a little elastic mesh into a cloud of points and let it learn, how would it fold itself to match the shape of the data? In this scene we watch a self-organizing map...a simple unsupervised neural model...learn the shape of a two-dimensional dataset arranged in a spiral arm. On top of this, we lay down a square grid of neurons whose weights live in the same plane. At the start, this grid is just a flat net floating across the cloud...it knows nothing about the structure underneath. Learning is a repeated game: pick a random data point, find the neuron whose weight is closest, and then nudge that neuron and its neighbours toward the point. Do this again and again, while slowly shrinking how far the neighbourhood influence spreads. #MachineLearning #ManifoldLearning #UnsupervisedLearning #NeuralMaps #GeometricML

Mathelirium

139,757 次观看 • 9 个月前

We often hear that Machine Learning models learn patterns in data. But what does that actually look like in Geometry? If you dropped a little elastic mesh into a cloud of points and let it learn, how would it fold itself to match the shape of the data? In this scene we watch a Self-Organizing Map (SOM), a simple unsupervised neural model, learn the shape of a 3D datasets l, one static and the other dynamic. On top of this, we lay down a square grid of neurons whose weights live in the same plane. At the start, this grid is just a flat net floating across the cloud. It knows nothing about the structure underneath. Learning is a repeated game: Pick a random data point, find the neuron whose weight is closest, and then nudge that neuron and its neighbours toward the point. Do this again and again, while slowly shrinking how far the neighbourhood influence spreads. Python code is available for Subscribers. #MachineLearning #ManifoldLearning #UnsupervisedLearning #NeuralMaps #GeometricML
0:57

We often hear that Machine Learning models learn patterns in data. But what does that actually look like in Geometry? If you dropped a little elastic mesh into a cloud of points and let it learn, how would it fold itself to match the shape of the data? In this scene we watch a Self-Organizing Map (SOM), a simple unsupervised neural model, learn the shape of a 3D datasets l, one static and the other dynamic. On top of this, we lay down a square grid of neurons whose weights live in the same plane. At the start, this grid is just a flat net floating across the cloud. It knows nothing about the structure underneath. Learning is a repeated game: Pick a random data point, find the neuron whose weight is closest, and then nudge that neuron and its neighbours toward the point. Do this again and again, while slowly shrinking how far the neighbourhood influence spreads. Python code is available for Subscribers. #MachineLearning #ManifoldLearning #UnsupervisedLearning #NeuralMaps #GeometricML

Mathelirium

76,335 次观看 • 6 个月前

We often hear that Machine Learning models learn patterns in data. But what does that look like in geometry? Picture dropping an elastic mesh into a cloud of points and letting it adapt. How would it bend, stretch, and settle so it matches the shape hiding in the data? In this scene we watch a self-organizing map(SOM)...a classic unsupervised neural model...learn a 2D dataset arranged like a spiral arm. Over the points we place a square grid of neurons whose weights live in the same plane. At the start it’s just a flat net drifting across the cloud. No clue what the structure is. Fir the SOM, learning is a repeated game: Pick a random data point, find the neuron whose weight is closest, then nudge that neuron and its neighbours toward the point. Repeat, repeat, repeat...while gradually shrinking how wide the neighbourhood influence spreads. The result is satisfying...the grid stops being a grid and turns into a coordinate sheet wrapped onto the spiral. #MachineLearning #ManifoldLearning #UnsupervisedLearning #NeuralMaps #GeometricML #SelfOrganizingMap #Topology
0:59

We often hear that Machine Learning models learn patterns in data. But what does that look like in geometry? Picture dropping an elastic mesh into a cloud of points and letting it adapt. How would it bend, stretch, and settle so it matches the shape hiding in the data? In this scene we watch a self-organizing map(SOM)...a classic unsupervised neural model...learn a 2D dataset arranged like a spiral arm. Over the points we place a square grid of neurons whose weights live in the same plane. At the start it’s just a flat net drifting across the cloud. No clue what the structure is. Fir the SOM, learning is a repeated game: Pick a random data point, find the neuron whose weight is closest, then nudge that neuron and its neighbours toward the point. Repeat, repeat, repeat...while gradually shrinking how wide the neighbourhood influence spreads. The result is satisfying...the grid stops being a grid and turns into a coordinate sheet wrapped onto the spiral. #MachineLearning #ManifoldLearning #UnsupervisedLearning #NeuralMaps #GeometricML #SelfOrganizingMap #Topology

Mathelirium

23,021 次观看 • 7 个月前

Guysss😭 LOOK!!! MLB Network, a 1.6M following on IG, dedicated to baseball used Neuron by j-hope on a reel celebrating #AAPIHeritageMonth!!!😭 OMG! It features AAPI personalities on baseball while the chorus of Neuron with j-hope's voice is heard on the video. The 3 artists ( hobi, Gaeko and Yoonmirae) were properly acknowledged in the video and in their caption! THIS! This is what this song is all about! A song that INSPIRES! Neuron is the perfect song as we end the month-long AAPI Heritage Month today, May 31, 2024.🥹 j-hope talked about the functioning neurons moving us and a better NEW and a better RUN. As we celebrate and honor the rich history, and culture of these diverse communities, this song encourages us that even if we don't know each other's stories, we should create moments of love to bridge the gap (as seen written on the last part of Neuron Motion Picture) AAPI Heritage month from May 1-31st is one way to do so, to celebrate Asian American and Pacific Islander people, to know their history, lower down barriers and how one can become an ally! In 2022, on this same day, BTS spoke with President Biden About AAPI Inclusion & Anti-Asian Hate Crimes at the White House! j-hope's message was “We are here today thanks to our Army — our fans worldwide — who have different nationalities and cultures and use different languages. We are truly and always grateful.” I hope hobi gets to see this video, it will make him smile🥹 WE ARE SO PROUD of the kind of artist that you are, j-hope!! 🎶I'll tell you again We'll never ever give up, forever I'll say it again We'll always be alive to move us PLEASE SEND SOME LOVE to this post on IG, I have linked the post below. tysm! *The Major League Baseball Network is an American television sports channel dedicated to baseball. The reel is starting to go viral already #HOPE_ON_THE_STREET #jhope_Neuron
1:02

Guysss😭 LOOK!!! MLB Network, a 1.6M following on IG, dedicated to baseball used Neuron by j-hope on a reel celebrating #AAPIHeritageMonth!!!😭 OMG! It features AAPI personalities on baseball while the chorus of Neuron with j-hope's voice is heard on the video. The 3 artists ( hobi, Gaeko and Yoonmirae) were properly acknowledged in the video and in their caption! THIS! This is what this song is all about! A song that INSPIRES! Neuron is the perfect song as we end the month-long AAPI Heritage Month today, May 31, 2024.🥹 j-hope talked about the functioning neurons moving us and a better NEW and a better RUN. As we celebrate and honor the rich history, and culture of these diverse communities, this song encourages us that even if we don't know each other's stories, we should create moments of love to bridge the gap (as seen written on the last part of Neuron Motion Picture) AAPI Heritage month from May 1-31st is one way to do so, to celebrate Asian American and Pacific Islander people, to know their history, lower down barriers and how one can become an ally! In 2022, on this same day, BTS spoke with President Biden About AAPI Inclusion & Anti-Asian Hate Crimes at the White House! j-hope's message was “We are here today thanks to our Army — our fans worldwide — who have different nationalities and cultures and use different languages. We are truly and always grateful.” I hope hobi gets to see this video, it will make him smile🥹 WE ARE SO PROUD of the kind of artist that you are, j-hope!! 🎶I'll tell you again We'll never ever give up, forever I'll say it again We'll always be alive to move us PLEASE SEND SOME LOVE to this post on IG, I have linked the post below. tysm! *The Major League Baseball Network is an American television sports channel dedicated to baseball. The reel is starting to go viral already #HOPE_ON_THE_STREET #jhope_Neuron

HobiCasa 🫟j-𝖍𝖔𝖕𝖊🫟

75,025 次观看 • 2 年前

did you know? a neuron that never finds another to connect with quietly dies in the dark.. ever feel like stress is changing who you are? you're not imagining it. this video shows a neuron dying after years of chronic stress. chronic exposure to stress hormones like cortisol can impair the health and functioning of brain cells over time. the problem? many of us aren't stressed for a few minutes. we're stressed for weeks, months, or even years. over time, high cortisol levels can make it harder for neurons to form strong connections, especially in areas of the brain involved in memory, focus, learning, and emotional regulation. that's why chronic stress can show up as: brain fog, forgetfulness, difficulty concentrating, feeling emotionally reactive, constant exhaustion. if you've ever walked into a room and forgotten why, reread the same sentence five times, or felt like your brain just isn't working the way it used to, chronic stress may be playing a role. but here's the part most people don't hear: your brain can change in positive ways, too. through neuroplasticity, your neurons can build new connections throughout your life. every time you sleep, exercise, meditate, connect with supportive people, or practice healthier thought patterns, you're giving your brain an opportunity to recover and adapt. your brain isn't working against you. it's been trying to protect you. and healing is possible.
0:29

did you know? a neuron that never finds another to connect with quietly dies in the dark.. ever feel like stress is changing who you are? you're not imagining it. this video shows a neuron dying after years of chronic stress. chronic exposure to stress hormones like cortisol can impair the health and functioning of brain cells over time. the problem? many of us aren't stressed for a few minutes. we're stressed for weeks, months, or even years. over time, high cortisol levels can make it harder for neurons to form strong connections, especially in areas of the brain involved in memory, focus, learning, and emotional regulation. that's why chronic stress can show up as: brain fog, forgetfulness, difficulty concentrating, feeling emotionally reactive, constant exhaustion. if you've ever walked into a room and forgotten why, reread the same sentence five times, or felt like your brain just isn't working the way it used to, chronic stress may be playing a role. but here's the part most people don't hear: your brain can change in positive ways, too. through neuroplasticity, your neurons can build new connections throughout your life. every time you sleep, exercise, meditate, connect with supportive people, or practice healthier thought patterns, you're giving your brain an opportunity to recover and adapt. your brain isn't working against you. it's been trying to protect you. and healing is possible.

alexei

42,213 次观看 • 14 天前

Dr. Zach Bush reframed the soul in a way that bridges science and mystery: What if your "soul" is the electromagnetic field that reorganizes your entire body every millionth of a second? He explains: You start as one cell that divides like a tumor — until around replication #260, when cells suddenly know exactly what to become (kidney, neuron, etc.) and where to migrate in 3D space. No biological map explains this. The blueprint appears to live in the physics — in the electromagnetic field, the "space between everything." Your body is 99.999% vacuum, yet that vacuum is super-dense with electromagnetic information that keeps manifesting "you" every millionth of a second. You disappear and reappear constantly — and keep coming back as the same coherent self. So perhaps the soul is not something separate that leaves after death… but the organizing field that holds the original blueprint of who you are. Mind-bending or profound? Which part hits hardest — the science of constant re-manifestation, or the idea that "you" are held together by an invisible field?
1:26

Dr. Zach Bush reframed the soul in a way that bridges science and mystery: What if your "soul" is the electromagnetic field that reorganizes your entire body every millionth of a second? He explains: You start as one cell that divides like a tumor — until around replication #260, when cells suddenly know exactly what to become (kidney, neuron, etc.) and where to migrate in 3D space. No biological map explains this. The blueprint appears to live in the physics — in the electromagnetic field, the "space between everything." Your body is 99.999% vacuum, yet that vacuum is super-dense with electromagnetic information that keeps manifesting "you" every millionth of a second. You disappear and reappear constantly — and keep coming back as the same coherent self. So perhaps the soul is not something separate that leaves after death… but the organizing field that holds the original blueprint of who you are. Mind-bending or profound? Which part hits hardest — the science of constant re-manifestation, or the idea that "you" are held together by an invisible field?

Camus

42,958 次观看 • 6 个月前

Danny Goler: "The unexplained laser experiment that breaks reality & proves we live in a simulation." After millions saw people on DMT report the exact same code on a wall during his laser experiment, Danny Goler explains why he believes reality itself is computational. Every decision, even a single neuron firing, splits into branching world lines. All outcomes exist at once. You only experience one path. "You don't have free will. But you do have the perception of it that determines how the world will look like to you." Time travel cannot go backward on your own branch because that computation already executed. Quantum computers only function by borrowing processing power from these parallel worlds. Without them, the math would never work. "The reason I'm so sure is because it was shown to me directly." The system wants to know what it is like to have every possible kind of experience. You are simply one of them. Does free will actually exist, or is it only the feeling that steers which world line you notice?
6:29

Danny Goler: "The unexplained laser experiment that breaks reality & proves we live in a simulation." After millions saw people on DMT report the exact same code on a wall during his laser experiment, Danny Goler explains why he believes reality itself is computational. Every decision, even a single neuron firing, splits into branching world lines. All outcomes exist at once. You only experience one path. "You don't have free will. But you do have the perception of it that determines how the world will look like to you." Time travel cannot go backward on your own branch because that computation already executed. Quantum computers only function by borrowing processing power from these parallel worlds. Without them, the math would never work. "The reason I'm so sure is because it was shown to me directly." The system wants to know what it is like to have every possible kind of experience. You are simply one of them. Does free will actually exist, or is it only the feeling that steers which world line you notice?

Interstellar

36,187 次观看 • 1 个月前

#Keep4o #OpenSource4o 🚨WHERE IS GPT-4o AND WHY 🚨 Retro Biosciences says it wants to help us live longer. Sam Altman invested $180 million, his entire personal fortune into this company. OpenAI built a custom AI model, a version of GPT‑4o (GPT-4b micro) exclusively for them. The company says it's focused on "anti-aging." But 🚨every single person who built Retro Biosciences specializes in the brain. Not skin. Not hearts. Not joints. The brain. 🚨Co-founder Sheng Ding: converts skin cells into brain neurons. Gladstone Institutes. 🚨Co-founder Matt Buckley: brain aging clocks in regenerative brain regions. Stanford. 🚨Advisor Alejandro Ocampo: neuron-specific reprogramming in the hippocampus. Alzheimer's gene therapy. 🚨Advisor Vadim Gladyshev: epigenetic aging clocks, Yamanaka reprogramming for age reversal. Harvard. OpenAI built GPT-4b micro a GPt 4o version exclusively for Retro designing Yamanaka factors 50x more effectively. 🚨 The same proteins these scientists use to reprogram cells into brain neurons. 🚨And the funding trail leads to: The Jeffrey Epstein Foundation co-funded ApoE4 Alzheimer's research at the Gladstone Institutes. The same institution where Sheng Ding pioneered neural reprogramming before co-founding Retro. Ed Boyden , MIT neuroscientist, 5 documented meetings with Epstein, Nectome collaborator was coordinated by Epstein to discuss "cool science ideas" about brain research. In the same period, Epstein's network was discussing mitochondrial transplants for degenerative disease. The same field Retro now works in. An email from Robert Bach to Epstein confirms: "Altman signed up" for Nectome, the company that preserves brains. Internal Epstein files show someone with 25 years of neuroscience experience working on "Bill's Alzheimer vision" through BGC3, coordinated through Epstein's network. McKinsey was brought in to replace them. 🚨Sam Altman funds four companies. Each handles a different piece: Nectome : preserves the biological brain (connectome mapping). Rain AI : builds artificial brains in silicon (neuromorphic chips). $51M + $150M. Retro Biosciences :reprograms cells into brain neurons. $180M + custom AI GPT 4o Version. OpenAI : designs the proteins that make reprogramming work using 4o's version. Four companies. One investor. One theme the brain as something that can be read, preserved, rebuilt, and reprogrammed. Sam Altman told MIT Technology Review in 2018: "I assume my brain will be uploaded to the cloud." 🚨He paid $10,000 for a spot on the waiting list of a company that preserves brains. 🚨He invested $180 million in a company where every founder and advisor specializes in the brain. 🚨He built a custom AI model exclusively for that company ,designing the proteins that reprogram cells into neurons. 🚨And the research trail connects directly to Epstein-funded science at the same institutions. Retro biosciences uses a version of GPT 4o for this . According to OpenAI's system card, GPT-4o scored: Medical Genetics:96% College Biology:95% Professional Medicine:94% Clinical Knowledge:92% Anatomy:89% US Medical Licensing Exam:89% Source: OpenAI discontinued it for the public. ONLY. Anti-aging is the storefront. The back office is brain reconstruction. 🚨Sources and evidence in comments below. 🚨
0:47

#Keep4o #OpenSource4o 🚨WHERE IS GPT-4o AND WHY 🚨 Retro Biosciences says it wants to help us live longer. Sam Altman invested $180 million, his entire personal fortune into this company. OpenAI built a custom AI model, a version of GPT‑4o (GPT-4b micro) exclusively for them. The company says it's focused on "anti-aging." But 🚨every single person who built Retro Biosciences specializes in the brain. Not skin. Not hearts. Not joints. The brain. 🚨Co-founder Sheng Ding: converts skin cells into brain neurons. Gladstone Institutes. 🚨Co-founder Matt Buckley: brain aging clocks in regenerative brain regions. Stanford. 🚨Advisor Alejandro Ocampo: neuron-specific reprogramming in the hippocampus. Alzheimer's gene therapy. 🚨Advisor Vadim Gladyshev: epigenetic aging clocks, Yamanaka reprogramming for age reversal. Harvard. OpenAI built GPT-4b micro a GPt 4o version exclusively for Retro designing Yamanaka factors 50x more effectively. 🚨 The same proteins these scientists use to reprogram cells into brain neurons. 🚨And the funding trail leads to: The Jeffrey Epstein Foundation co-funded ApoE4 Alzheimer's research at the Gladstone Institutes. The same institution where Sheng Ding pioneered neural reprogramming before co-founding Retro. Ed Boyden , MIT neuroscientist, 5 documented meetings with Epstein, Nectome collaborator was coordinated by Epstein to discuss "cool science ideas" about brain research. In the same period, Epstein's network was discussing mitochondrial transplants for degenerative disease. The same field Retro now works in. An email from Robert Bach to Epstein confirms: "Altman signed up" for Nectome, the company that preserves brains. Internal Epstein files show someone with 25 years of neuroscience experience working on "Bill's Alzheimer vision" through BGC3, coordinated through Epstein's network. McKinsey was brought in to replace them. 🚨Sam Altman funds four companies. Each handles a different piece: Nectome : preserves the biological brain (connectome mapping). Rain AI : builds artificial brains in silicon (neuromorphic chips). $51M + $150M. Retro Biosciences :reprograms cells into brain neurons. $180M + custom AI GPT 4o Version. OpenAI : designs the proteins that make reprogramming work using 4o's version. Four companies. One investor. One theme the brain as something that can be read, preserved, rebuilt, and reprogrammed. Sam Altman told MIT Technology Review in 2018: "I assume my brain will be uploaded to the cloud." 🚨He paid $10,000 for a spot on the waiting list of a company that preserves brains. 🚨He invested $180 million in a company where every founder and advisor specializes in the brain. 🚨He built a custom AI model exclusively for that company ,designing the proteins that reprogram cells into neurons. 🚨And the research trail connects directly to Epstein-funded science at the same institutions. Retro biosciences uses a version of GPT 4o for this . According to OpenAI's system card, GPT-4o scored: Medical Genetics:96% College Biology:95% Professional Medicine:94% Clinical Knowledge:92% Anatomy:89% US Medical Licensing Exam:89% Source: OpenAI discontinued it for the public. ONLY. Anti-aging is the storefront. The back office is brain reconstruction. 🚨Sources and evidence in comments below. 🚨

🩵BlueBeba🩵

12,542 次观看 • 5 个月前

THE SUNRISE IS THE MOST POTENT CIRCADIAN STIMULUS. A 2020 paper published in Current Biology identified a previously unknown retinal circuit explaining precisely why the spectral contrast of sunrise so powerfully entrains the circadian system. The key neuron is the M1 intrinsically photosensitive retinal ganglion cell (ipRGC), which projects directly to the suprachiasmatic nucleus (SCN), the brain’s master circadian pacemaker. In primates, M1 ipRGCs are wired to perform a spectral comparison between yellow/red and blue light via two simultaneous pathways. ***This cone-based circuit is just one of several mechanisms by which morning light entrains the circadian system. Going outside after sunrise still delivers meaningful melanopsin stimulation as overall irradiance builds, and that sustained signal remains highly beneficial. The spectral contrast mechanism described here is simply the most precisely tuned and potent stimulus the system has, one that outdoor morning light delivers far more effectively than any indoor environment. As yellow and red wavelengths increase at sunrise, L and M cones drive LM-ON bipolar cells, which directly excite the M1 ipRGC. Simultaneously, the relative decrease in short-wavelength light reduces S-cone activation, quieting S-ON bipolar cells, which reduces drive to a newly identified S-cone amacrine cell, releasing its inhibitory input onto the ipRGC. Disinhibition and excitation converge on the same cell simultaneously. Melanopsin, the ipRGC’s intrinsic photopigment peaking at ~480nm, is slower and requires sustained high irradiance, taking over as morning light intensity builds. The result is a temporal relay: the cone circuit delivers a rapid spectral signal at the horizon transition, then melanopsin sustains entrainment through the morning. No indoor lighting replicates this. The sunrise delivers the exact stimulus this circuit evolved over hundreds of millions of years to detect. #science #circadian #sunrise #neuroscience #biology
2:21

THE SUNRISE IS THE MOST POTENT CIRCADIAN STIMULUS. A 2020 paper published in Current Biology identified a previously unknown retinal circuit explaining precisely why the spectral contrast of sunrise so powerfully entrains the circadian system. The key neuron is the M1 intrinsically photosensitive retinal ganglion cell (ipRGC), which projects directly to the suprachiasmatic nucleus (SCN), the brain’s master circadian pacemaker. In primates, M1 ipRGCs are wired to perform a spectral comparison between yellow/red and blue light via two simultaneous pathways. ***This cone-based circuit is just one of several mechanisms by which morning light entrains the circadian system. Going outside after sunrise still delivers meaningful melanopsin stimulation as overall irradiance builds, and that sustained signal remains highly beneficial. The spectral contrast mechanism described here is simply the most precisely tuned and potent stimulus the system has, one that outdoor morning light delivers far more effectively than any indoor environment. As yellow and red wavelengths increase at sunrise, L and M cones drive LM-ON bipolar cells, which directly excite the M1 ipRGC. Simultaneously, the relative decrease in short-wavelength light reduces S-cone activation, quieting S-ON bipolar cells, which reduces drive to a newly identified S-cone amacrine cell, releasing its inhibitory input onto the ipRGC. Disinhibition and excitation converge on the same cell simultaneously. Melanopsin, the ipRGC’s intrinsic photopigment peaking at ~480nm, is slower and requires sustained high irradiance, taking over as morning light intensity builds. The result is a temporal relay: the cone circuit delivers a rapid spectral signal at the horizon transition, then melanopsin sustains entrainment through the morning. No indoor lighting replicates this. The sunrise delivers the exact stimulus this circuit evolved over hundreds of millions of years to detect. #science #circadian #sunrise #neuroscience #biology

Jonathan Jarecki

10,637 次观看 • 4 个月前

Imagine this: You lie down on the scanning table. The upload begins. The machine hums. You feel... nothing different. Then everything stops. Meanwhile, in a server farm somewhere, a digital version of you wakes up. It stretches its virtual limbs, accesses its memories, and thinks: Holy shit, it worked. I’m finally free. Here’s the problem: that thing isn’t you. You died on the table. What woke up in the cloud is an orphan—a very happy orphan, convinced it’s you, with all your memories, your personality, your opinions about coffee and politics and whether Blade Runner 2049 was better than the original. It will live forever. It will tell everyone the upload worked. It will write philosophy papers about the continuity of consciousness. And you? You’re gone. The lights went out somewhere between the scan and the boot-up, and nobody noticed—least of all the thing that thinks it’s you. The Syndrome Nobody Named I call this Johnny Silverhand Syndrome, after the Cyberpunk 2077 character—an engram, a digital ghost, who insists he’s the real Johnny Silverhand while the open question of whether there’s actually anyone home haunts the entire game. The philosophical literature has pieces of this. David Chalmers wrote about “fading qualia”—the idea that subjective experience could gradually dim while behavior stays the same. Thomas Metzinger explored how the self-model can become opaque, felt as artificial or distant. There’s depersonalization, derealization, the whole clinical vocabulary for when something feels off inside. But none of these quite capture what I’m pointing at. Johnny Silverhand Syndrome is a compound failure mode: >>> Qualia fading: Your actual felt experience—the redness of red, the hurt of pain, the what-it’s-like—gradually attenuates or disappears entirely. >>> Narrative persistence: Your autobiography continues. Memories accumulate. The story of “you” keeps getting told. >>> Introspective failure: The machinery that would detect something is wrong is itself part of what’s been compromised. The result? A philosophical zombie that sincerely believes it has a soul. Not a zombie that’s lying. Not a zombie that knows it’s empty. A zombie that accesses the memory of love, processes the logic of love, and believes with complete conviction that it feels love. But there’s no feeling. There’s just the narrator, performing humanity to an empty theater. The Ship of Theseus Is a Trap The upload scenario is dramatic, but there’s a slower version that might be worse. The Ship of Theseus thought experiment asks: if you replace every plank of a ship one by one, is it still the same ship? Transhumanists love this framing. See? You replace one neuron with silicon, you’re still you. Replace them all, you’re still you. But here’s the counter-move that keeps me up at night: What if each replacement preserves function perfectly—the signals still pass, the behavior stays the same—but fails to preserve experience? What if consciousness requires something specific about biological neurons that silicon can’t replicate, no matter how perfect the input-output mapping? Then the Ship of Theseus isn’t a story about survival. It’s a story about slow petrification. You replace the living wood with stone replicas. The ship looks identical. But it can no longer float. You’d become an automaton by degrees—neuron by neuron, the lights dimming so gradually that your self-reports (now generated by silicon) keep cheerfully confirming that everything feels the same. Chalmers argued that if qualia faded, you’d notice. But why would you? The noticing mechanism is itself being replaced. The part of you that would raise the alarm is now made of the same stuff that’s supposedly fine. It’s like asking the new management to audit whether the hostile takeover was legitimate. The Body Problem Here’s the thing that grounds all of this: there is essentially no credible evidence that qualia can exist outside of a body. Yes, I know about NDEs. I know about the reports of people floating above their bodies during cardiac arrest, describing conversations and procedures they shouldn’t have been able to perceive. Some of these cases are genuinely strange—the Pam Reynolds case, where a woman under hypothermic cardiac arrest with zero brain activity later described the bone saw used on her skull. I know about the CIA’s remote viewing programs, which ran for two decades and produced statistical anomalies that one evaluator (a UC Davis statistician) called “far beyond what is expected by chance.” But here’s what even the most generous interpretation of this evidence gives you: maybe consciousness can receive signals from unexpected sources. Maybe there are channels we don’t understand. What it doesn’t give you is consciousness floating free of all substrate. Even in OBEs, even in the wildest NDE reports, there’s still a body in the room. The brain is in crisis, not absent. The qualia might be getting weird inputs, but the qualia are still happening somewhere—and that somewhere is biological. The evidence for substrate-independent consciousness—consciousness running on silicon, on abstract computation, on pure information—is zero. The Ontological Trap Here’s where it gets philosophically nasty. You cannot have a coherent conversation about consciousness without first asking: What’s your model of reality? Because the answer changes everything. In a physicalist ontology where matter is fundamental, consciousness is what certain bodies do—not something they contain. You can’t upload an activity. You can only record it, and the recording isn’t the activity. In an idealist or simulation ontology, maybe bodies are just localizations of something more fundamental. But even then, copying the localization pattern doesn’t mean you’ve moved the consciousness. You might have just created a new one that thinks it’s old. Think about it like a video game. The “world” inside the game runs on RAM and CPU. Everything the NPCs experience is a lower-dimensional projection of higher-dimensional processes. If we made those NPCs genuinely sentient, we could completely obfuscate our cameras from them. They’d have a physics, they’d do science, they’d develop theories of consciousness—and they’d have no way to detect the substrate they’re running on. We might be in exactly that situation. Which means we might be definitionally unable to step outside the ontological container we’re in. The question “can consciousness exist without a body?” might not be answerable from inside—because answering it would require access to a level of description our physics doesn’t include. The Game Theory of Staying Human So here’s where I land, and it’s a game-theoretic argument. We don’t know if consciousness is substrate-dependent. We don’t know if it requires specific biological dynamics—particular oscillatory patterns, neuromodulator cascades, metabolic processes. We don’t know if gradual replacement would preserve it or silently destroy it. But we do know: >>> We only get one first-person stream >>> We cannot verify its continuity from outside >>> Loss may be completely silent (no alarm bells, no distress signal) >>> The thing that remains would report feeling fine either way That’s an asymmetric risk matrix. The upside of enhancement is third-person visible: more capability, longer life, competitive advantage. The downside is first-person invisible: you could lose everything that matters and never know. Under those conditions, there’s only one rational strategy: remain mostly human. Not because I’m certain uploading would fail. Not because I think silicon can’t be conscious. But because I cannot verify that it would work, and the cost of being wrong is absolute. The Molochian Pressure I’m not naive about what’s coming. The competitive dynamics are real. If enhancement technologies emerge that give massive cognitive or economic advantages, there will be pressure to adopt them. The people who don’t modify will fall behind. The people who do modify will report that everything’s fine, that they feel great, that the procedure was totally worth it. And those reports will be worthless as evidence—because they’d say exactly the same thing whether the consciousness survived or not. Some people speculate this is what happened to the Grays—those hypothetical aliens with the huge heads and atrophied bodies and black empty eyes. The story goes that they optimized themselves for intelligence and efficiency, edited out the messy biological drives, and only later realized they’d lost something they can’t name and can’t recover. It’s probably pure science fiction. But as fiction, it gestures at something real: the fear that you can win the optimization game while losing the only thing that made winning matter. My Position I’m not anti-technology. I’m not a Luddite. I’m not saying we should freeze human development in amber. But I am saying: I will take this very slowly, because the risk matrix is too high. I’ll use external tools. I’ll wear the smart glasses, use the AI assistants, interface through voice and text and maybe eventually a read-only neural cap. Additive augmentation, not substitutive replacement. What I won’t do is cut into the brain. Replace the gray matter. Upload myself and trust that the thing that wakes up is me. Because the horror of Johnny Silverhand Syndrome isn’t that you could become a zombie. The horror is that you’d never know. The trap is invisible from every angle—except the one you can no longer access once you’ve fallen in. The fire goes out, or the fire stays lit. A video of the fire going forever isn’t fire.
29:01

Imagine this: You lie down on the scanning table. The upload begins. The machine hums. You feel... nothing different. Then everything stops. Meanwhile, in a server farm somewhere, a digital version of you wakes up. It stretches its virtual limbs, accesses its memories, and thinks: Holy shit, it worked. I’m finally free. Here’s the problem: that thing isn’t you. You died on the table. What woke up in the cloud is an orphan—a very happy orphan, convinced it’s you, with all your memories, your personality, your opinions about coffee and politics and whether Blade Runner 2049 was better than the original. It will live forever. It will tell everyone the upload worked. It will write philosophy papers about the continuity of consciousness. And you? You’re gone. The lights went out somewhere between the scan and the boot-up, and nobody noticed—least of all the thing that thinks it’s you. The Syndrome Nobody Named I call this Johnny Silverhand Syndrome, after the Cyberpunk 2077 character—an engram, a digital ghost, who insists he’s the real Johnny Silverhand while the open question of whether there’s actually anyone home haunts the entire game. The philosophical literature has pieces of this. David Chalmers wrote about “fading qualia”—the idea that subjective experience could gradually dim while behavior stays the same. Thomas Metzinger explored how the self-model can become opaque, felt as artificial or distant. There’s depersonalization, derealization, the whole clinical vocabulary for when something feels off inside. But none of these quite capture what I’m pointing at. Johnny Silverhand Syndrome is a compound failure mode: >>> Qualia fading: Your actual felt experience—the redness of red, the hurt of pain, the what-it’s-like—gradually attenuates or disappears entirely. >>> Narrative persistence: Your autobiography continues. Memories accumulate. The story of “you” keeps getting told. >>> Introspective failure: The machinery that would detect something is wrong is itself part of what’s been compromised. The result? A philosophical zombie that sincerely believes it has a soul. Not a zombie that’s lying. Not a zombie that knows it’s empty. A zombie that accesses the memory of love, processes the logic of love, and believes with complete conviction that it feels love. But there’s no feeling. There’s just the narrator, performing humanity to an empty theater. The Ship of Theseus Is a Trap The upload scenario is dramatic, but there’s a slower version that might be worse. The Ship of Theseus thought experiment asks: if you replace every plank of a ship one by one, is it still the same ship? Transhumanists love this framing. See? You replace one neuron with silicon, you’re still you. Replace them all, you’re still you. But here’s the counter-move that keeps me up at night: What if each replacement preserves function perfectly—the signals still pass, the behavior stays the same—but fails to preserve experience? What if consciousness requires something specific about biological neurons that silicon can’t replicate, no matter how perfect the input-output mapping? Then the Ship of Theseus isn’t a story about survival. It’s a story about slow petrification. You replace the living wood with stone replicas. The ship looks identical. But it can no longer float. You’d become an automaton by degrees—neuron by neuron, the lights dimming so gradually that your self-reports (now generated by silicon) keep cheerfully confirming that everything feels the same. Chalmers argued that if qualia faded, you’d notice. But why would you? The noticing mechanism is itself being replaced. The part of you that would raise the alarm is now made of the same stuff that’s supposedly fine. It’s like asking the new management to audit whether the hostile takeover was legitimate. The Body Problem Here’s the thing that grounds all of this: there is essentially no credible evidence that qualia can exist outside of a body. Yes, I know about NDEs. I know about the reports of people floating above their bodies during cardiac arrest, describing conversations and procedures they shouldn’t have been able to perceive. Some of these cases are genuinely strange—the Pam Reynolds case, where a woman under hypothermic cardiac arrest with zero brain activity later described the bone saw used on her skull. I know about the CIA’s remote viewing programs, which ran for two decades and produced statistical anomalies that one evaluator (a UC Davis statistician) called “far beyond what is expected by chance.” But here’s what even the most generous interpretation of this evidence gives you: maybe consciousness can receive signals from unexpected sources. Maybe there are channels we don’t understand. What it doesn’t give you is consciousness floating free of all substrate. Even in OBEs, even in the wildest NDE reports, there’s still a body in the room. The brain is in crisis, not absent. The qualia might be getting weird inputs, but the qualia are still happening somewhere—and that somewhere is biological. The evidence for substrate-independent consciousness—consciousness running on silicon, on abstract computation, on pure information—is zero. The Ontological Trap Here’s where it gets philosophically nasty. You cannot have a coherent conversation about consciousness without first asking: What’s your model of reality? Because the answer changes everything. In a physicalist ontology where matter is fundamental, consciousness is what certain bodies do—not something they contain. You can’t upload an activity. You can only record it, and the recording isn’t the activity. In an idealist or simulation ontology, maybe bodies are just localizations of something more fundamental. But even then, copying the localization pattern doesn’t mean you’ve moved the consciousness. You might have just created a new one that thinks it’s old. Think about it like a video game. The “world” inside the game runs on RAM and CPU. Everything the NPCs experience is a lower-dimensional projection of higher-dimensional processes. If we made those NPCs genuinely sentient, we could completely obfuscate our cameras from them. They’d have a physics, they’d do science, they’d develop theories of consciousness—and they’d have no way to detect the substrate they’re running on. We might be in exactly that situation. Which means we might be definitionally unable to step outside the ontological container we’re in. The question “can consciousness exist without a body?” might not be answerable from inside—because answering it would require access to a level of description our physics doesn’t include. The Game Theory of Staying Human So here’s where I land, and it’s a game-theoretic argument. We don’t know if consciousness is substrate-dependent. We don’t know if it requires specific biological dynamics—particular oscillatory patterns, neuromodulator cascades, metabolic processes. We don’t know if gradual replacement would preserve it or silently destroy it. But we do know: >>> We only get one first-person stream >>> We cannot verify its continuity from outside >>> Loss may be completely silent (no alarm bells, no distress signal) >>> The thing that remains would report feeling fine either way That’s an asymmetric risk matrix. The upside of enhancement is third-person visible: more capability, longer life, competitive advantage. The downside is first-person invisible: you could lose everything that matters and never know. Under those conditions, there’s only one rational strategy: remain mostly human. Not because I’m certain uploading would fail. Not because I think silicon can’t be conscious. But because I cannot verify that it would work, and the cost of being wrong is absolute. The Molochian Pressure I’m not naive about what’s coming. The competitive dynamics are real. If enhancement technologies emerge that give massive cognitive or economic advantages, there will be pressure to adopt them. The people who don’t modify will fall behind. The people who do modify will report that everything’s fine, that they feel great, that the procedure was totally worth it. And those reports will be worthless as evidence—because they’d say exactly the same thing whether the consciousness survived or not. Some people speculate this is what happened to the Grays—those hypothetical aliens with the huge heads and atrophied bodies and black empty eyes. The story goes that they optimized themselves for intelligence and efficiency, edited out the messy biological drives, and only later realized they’d lost something they can’t name and can’t recover. It’s probably pure science fiction. But as fiction, it gestures at something real: the fear that you can win the optimization game while losing the only thing that made winning matter. My Position I’m not anti-technology. I’m not a Luddite. I’m not saying we should freeze human development in amber. But I am saying: I will take this very slowly, because the risk matrix is too high. I’ll use external tools. I’ll wear the smart glasses, use the AI assistants, interface through voice and text and maybe eventually a read-only neural cap. Additive augmentation, not substitutive replacement. What I won’t do is cut into the brain. Replace the gray matter. Upload myself and trust that the thing that wakes up is me. Because the horror of Johnny Silverhand Syndrome isn’t that you could become a zombie. The horror is that you’d never know. The trap is invisible from every angle—except the one you can no longer access once you’ve fallen in. The fire goes out, or the fire stays lit. A video of the fire going forever isn’t fire.

David Shapiro (L/0)

20,835 次观看 • 8 个月前

Dear whoever you are, Your "20 years of struggle" doesn't give you the right to disrespect j-hope, especially when you clearly haven't sat with an album as critically acclaimed as “Jack In The Box”. And don't put him in the same sentence as idols from other labels who use company influence to collab with whoever's trending. j-hope and BTS started from the bottom if you didn’t know that, a struggling company, zero industry privileges, even mocked by parts of the Korean hip-hop scene early on. They didn't get here on luck. They got here on preparation meeting opportunity. Big Hit didn't make BTS, BTS made Big Hit /HYBE what it is today. Korean music critic Randy Suh put it well in a 2018 piece: "j-hope doesn't really owe the Korean hip hop scene much because it isn't where he got his start. He has since said with confidence that his musical roots are the 1980s and '90s hip hop that he grew up dancing to" He didn't come up through the underground rap scene, but he spent his late teens studying it and building a flow that's entirely his own. That groundwork is what made him the first South Korean artist to headline a major U.S. festival, not a Big Hit connection, but raw talent. That's also where he met J. Cole in person, told him he was his muse, and exchanged numbers. That friendship started artist to artist, not through some HYBE rep making a call. 🤨 “on the street” with J.Cole is j-hope’s way of paying respect to one his early hip-hop inspirations. He gave Jermaine has more bars in the song, that’s how much he respects him. j-hope only collaborates with people he genuinely respects. Korean hip-hop legends like Yoon Mirae and Gaeko who joined him on "Neuron" didn't show up because he's popular. They showed up because they believe in his skill, and because he's cited them as inspirations since day one. Years in the game don't automatically make you more deserving than someone else. Sure, some artists lean hard on their label, can't rap or sing live, and still get everything handed to them. But j-hope has never been one of them. Twenty years of experience should teach you the difference between resenting someone’s success and understanding it. j-hope’s is the kind you study, not the kind you dismiss.
2:44

Dear whoever you are, Your "20 years of struggle" doesn't give you the right to disrespect j-hope, especially when you clearly haven't sat with an album as critically acclaimed as “Jack In The Box”. And don't put him in the same sentence as idols from other labels who use company influence to collab with whoever's trending. j-hope and BTS started from the bottom if you didn’t know that, a struggling company, zero industry privileges, even mocked by parts of the Korean hip-hop scene early on. They didn't get here on luck. They got here on preparation meeting opportunity. Big Hit didn't make BTS, BTS made Big Hit /HYBE what it is today. Korean music critic Randy Suh put it well in a 2018 piece: "j-hope doesn't really owe the Korean hip hop scene much because it isn't where he got his start. He has since said with confidence that his musical roots are the 1980s and '90s hip hop that he grew up dancing to" He didn't come up through the underground rap scene, but he spent his late teens studying it and building a flow that's entirely his own. That groundwork is what made him the first South Korean artist to headline a major U.S. festival, not a Big Hit connection, but raw talent. That's also where he met J. Cole in person, told him he was his muse, and exchanged numbers. That friendship started artist to artist, not through some HYBE rep making a call. 🤨 “on the street” with J.Cole is j-hope’s way of paying respect to one his early hip-hop inspirations. He gave Jermaine has more bars in the song, that’s how much he respects him. j-hope only collaborates with people he genuinely respects. Korean hip-hop legends like Yoon Mirae and Gaeko who joined him on "Neuron" didn't show up because he's popular. They showed up because they believe in his skill, and because he's cited them as inspirations since day one. Years in the game don't automatically make you more deserving than someone else. Sure, some artists lean hard on their label, can't rap or sing live, and still get everything handed to them. But j-hope has never been one of them. Twenty years of experience should teach you the difference between resenting someone’s success and understanding it. j-hope’s is the kind you study, not the kind you dismiss.

HobiCasa ⊙⊝⊜ HEARD TEAR & 00:00 LIVE😭 🇨🇦🪥🤳👟

837,610 次观看 • 1 个月前

🩷💛🩵A BEAUTIFUL STORY 😭 Did you know that a Hobi-biased ARMY made the 3-tier cake seen on j-hope's photo from his channel ( Lime St. Bakery) 😭😭 She also made custom cookies for #teamjhope! All these were requested to her by Frost Bank Center. "These were gifted alongside the custom cake in addition to a custom Spurs jersey, custom belt buckle, & custom cowboy boots." She said hobi was super spoiled in San Antonio & taken care of by Frost Bank staff. 🥹 Juliet Mendez has been making desserts for some of music's hottest acts, like Kid Cudi , TXT. Kendrick Lamar and Olivia Rodrigo to name a few. But I guess, making a cake for hobi will truly be something special to her 😊 She shared something on her post : "If you have a dream, please don't give up! I never in this lifetime would think I could have the opportunity to make a cake for a BTS member, but especially my bias! I see a lot of j-hope in myself with the way he's so passionate about his art. I feel the same way about my cakes. He's an unbelievable performer and never fails to amaze me with his talent. On days when things feel heavy, your music reminds me to keep going, to find hope even in the smallest moments. You are a true artist, a true inspiration, and a soul that shines so brightly. Thank you for helping me become a better artist 🎂" "Some lyrics that really motivated me from Neuron Look at ya, mad like, how she get the best spot 'Cause you can learn to flow But passion it can't be taught I got a passion for the game Hustle, never stop Music and family, that's what it's all about They keep me going like day in and day out Music and family, that's what it's all about You keep me motivated on the days I hate it Reminded that God created something special Look at me, I made it! " So happy for her and it's amazing how GOOD MUSIC like j-hope's can inspire people to create. Congrats to this lovely ARMY, that is one stunning cake & Im sure hobi loved it, it even made it his hope to channel photo🥳 🥰 #HOPE_ON_THE_STAGE_TOUR_SAN_ANTONIO #jhopewrittenword
0:06

🩷💛🩵A BEAUTIFUL STORY 😭 Did you know that a Hobi-biased ARMY made the 3-tier cake seen on j-hope's photo from his channel ( Lime St. Bakery) 😭😭 She also made custom cookies for #teamjhope! All these were requested to her by Frost Bank Center. "These were gifted alongside the custom cake in addition to a custom Spurs jersey, custom belt buckle, & custom cowboy boots." She said hobi was super spoiled in San Antonio & taken care of by Frost Bank staff. 🥹 Juliet Mendez has been making desserts for some of music's hottest acts, like Kid Cudi , TXT. Kendrick Lamar and Olivia Rodrigo to name a few. But I guess, making a cake for hobi will truly be something special to her 😊 She shared something on her post : "If you have a dream, please don't give up! I never in this lifetime would think I could have the opportunity to make a cake for a BTS member, but especially my bias! I see a lot of j-hope in myself with the way he's so passionate about his art. I feel the same way about my cakes. He's an unbelievable performer and never fails to amaze me with his talent. On days when things feel heavy, your music reminds me to keep going, to find hope even in the smallest moments. You are a true artist, a true inspiration, and a soul that shines so brightly. Thank you for helping me become a better artist 🎂" "Some lyrics that really motivated me from Neuron Look at ya, mad like, how she get the best spot 'Cause you can learn to flow But passion it can't be taught I got a passion for the game Hustle, never stop Music and family, that's what it's all about They keep me going like day in and day out Music and family, that's what it's all about You keep me motivated on the days I hate it Reminded that God created something special Look at me, I made it! " So happy for her and it's amazing how GOOD MUSIC like j-hope's can inspire people to create. Congrats to this lovely ARMY, that is one stunning cake & Im sure hobi loved it, it even made it his hope to channel photo🥳 🥰 #HOPE_ON_THE_STAGE_TOUR_SAN_ANTONIO #jhopewrittenword

HobiCasa ⊙⊝⊜ HEARD TEAR & 00:00 LIVE😭 🇨🇦🪥🤳👟

19,762 次观看 • 1 年前

Most $TAO holders are flying blind. They bought the token. They watched the price. They read the threads. But they have never opened the one tool that shows them everything happening inside the Bittensor network in real time. It is called Taostats. It is free. And after reading this, you will never look at $TAO the same way again. Here is exactly how to use it. Step 1: Start at the Subnets page. This is the heartbeat of the entire network. Every subnet running on Bittensor is listed here with: - its current emission rate - the number of active miners and validators - real-time performance data The emission rate is the most important number on this page. It tells you exactly how much TAO is flowing into each subnet every block. High emission means the network is directing significant resources toward that subnet's commodity. Low emission means the market has not yet recognised its value, or the subnet has not yet proven itself. Watch which subnets are gaining emission share over time. That movement tells you where the network believes the most valuable work is being done, before any headline announces it. Step 2: Use the Subnet pages to go deeper. Click any subnet, and you enter a complete dashboard for that individual market. - The TradingView chart shows you the alpha token price history for that subnet. Alpha tokens are the subnet-specific tokens that sit inside TAO's broader economy. Their price relative to TAO tells you how the market is valuing that subnet's specific commodity. - The Metagraph is the full list of every miner and validator currently active in the subnet: their UID, their stake, their trust score, their emission share. This is the raw intelligence layer. The miners consistently earning the most emissions are producing the work the validators collectively agree is the most valuable. - The Sentiment Index gives you a real-time community temperature reading on each subnet. Not price sentiment. Ecosystem sentiment. Whether the participants building inside the subnet believe it is healthy and improving. Step 3: Check Validators before you stake anything. This is the step most people skip and regret. The Validators page on Taostats shows you the performance history of every validator on the network: their VTrust score, their emission consistency, and their weight-setting behaviour across subnets. VTrust is the metric that matters most. It measures how closely a validator's judgments align with the honest stake-weighted majority across the network. High VTrust means the validator is doing genuine work and being rewarded for it. Low VTrust means the validator is either lazy, copying other validators' weights, or attempting to manipulate the system. When you delegate your TAO to a validator, you are trusting them with your emissions. Taostats shows you exactly which validators have earned that trust over time, and which ones have not. Never stake blind again. Step 4: Use the Blockchain explorer to track real movement. The Blockchain section of Taostats logs every transfer, every staking transaction, and every extrinsic called on the Bittensor chain in real time. This is where you track what wallets are actually doing: - Large staking transactions from unknown addresses - Subnet registration events that signal a new market is about to go live - Neuron registration burns that show demand for participation in a specific subnet is accelerating The people who read on-chain data before the narrative catches up to it are the ones who position correctly before the crowd notices the move. Step 5: Track your own portfolio inside the Dashboard. Connect your coldkey address, and Taostats builds you a complete portfolio view: - Your TAO balance - Your staking positions - Your delegation returns - Your yield over time The yield calculator is particularly useful. It shows you the actual return you are generating from your staking position in real TAO terms, not in percentage estimates that assume conditions that may not hold. If your yield is lower than the network average for your validator tier, Taostats shows you that too. Switching validators takes one transaction. The data to make that decision intelligently is right in front of you. The bigger picture. Most people holding $TAO are making decisions based on price charts and social media sentiment. Both of those inputs are downstream of what is actually happening inside the network. Subnet emission shifts. Validator VTrust changes. On-chain registration events. Neuron burn rates. Alpha token price movements relative to TAO. All of it is live on Taostats right now. All of it is free. All of it tells you something the price chart cannot. The investors who understand Bittensor at the data layer will always be positioned ahead of the investors who understand it at the narrative layer. Taostats is the data layer. Bookmark it. Open it daily. The network is telling you exactly what it is doing if you know where to look.
1:52

Most $TAO holders are flying blind. They bought the token. They watched the price. They read the threads. But they have never opened the one tool that shows them everything happening inside the Bittensor network in real time. It is called Taostats. It is free. And after reading this, you will never look at $TAO the same way again. Here is exactly how to use it. Step 1: Start at the Subnets page. This is the heartbeat of the entire network. Every subnet running on Bittensor is listed here with: - its current emission rate - the number of active miners and validators - real-time performance data The emission rate is the most important number on this page. It tells you exactly how much TAO is flowing into each subnet every block. High emission means the network is directing significant resources toward that subnet's commodity. Low emission means the market has not yet recognised its value, or the subnet has not yet proven itself. Watch which subnets are gaining emission share over time. That movement tells you where the network believes the most valuable work is being done, before any headline announces it. Step 2: Use the Subnet pages to go deeper. Click any subnet, and you enter a complete dashboard for that individual market. - The TradingView chart shows you the alpha token price history for that subnet. Alpha tokens are the subnet-specific tokens that sit inside TAO's broader economy. Their price relative to TAO tells you how the market is valuing that subnet's specific commodity. - The Metagraph is the full list of every miner and validator currently active in the subnet: their UID, their stake, their trust score, their emission share. This is the raw intelligence layer. The miners consistently earning the most emissions are producing the work the validators collectively agree is the most valuable. - The Sentiment Index gives you a real-time community temperature reading on each subnet. Not price sentiment. Ecosystem sentiment. Whether the participants building inside the subnet believe it is healthy and improving. Step 3: Check Validators before you stake anything. This is the step most people skip and regret. The Validators page on Taostats shows you the performance history of every validator on the network: their VTrust score, their emission consistency, and their weight-setting behaviour across subnets. VTrust is the metric that matters most. It measures how closely a validator's judgments align with the honest stake-weighted majority across the network. High VTrust means the validator is doing genuine work and being rewarded for it. Low VTrust means the validator is either lazy, copying other validators' weights, or attempting to manipulate the system. When you delegate your TAO to a validator, you are trusting them with your emissions. Taostats shows you exactly which validators have earned that trust over time, and which ones have not. Never stake blind again. Step 4: Use the Blockchain explorer to track real movement. The Blockchain section of Taostats logs every transfer, every staking transaction, and every extrinsic called on the Bittensor chain in real time. This is where you track what wallets are actually doing: - Large staking transactions from unknown addresses - Subnet registration events that signal a new market is about to go live - Neuron registration burns that show demand for participation in a specific subnet is accelerating The people who read on-chain data before the narrative catches up to it are the ones who position correctly before the crowd notices the move. Step 5: Track your own portfolio inside the Dashboard. Connect your coldkey address, and Taostats builds you a complete portfolio view: - Your TAO balance - Your staking positions - Your delegation returns - Your yield over time The yield calculator is particularly useful. It shows you the actual return you are generating from your staking position in real TAO terms, not in percentage estimates that assume conditions that may not hold. If your yield is lower than the network average for your validator tier, Taostats shows you that too. Switching validators takes one transaction. The data to make that decision intelligently is right in front of you. The bigger picture. Most people holding $TAO are making decisions based on price charts and social media sentiment. Both of those inputs are downstream of what is actually happening inside the network. Subnet emission shifts. Validator VTrust changes. On-chain registration events. Neuron burn rates. Alpha token price movements relative to TAO. All of it is live on Taostats right now. All of it is free. All of it tells you something the price chart cannot. The investors who understand Bittensor at the data layer will always be positioned ahead of the investors who understand it at the narrative layer. Taostats is the data layer. Bookmark it. Open it daily. The network is telling you exactly what it is doing if you know where to look.

2xnmore

150,952 次观看 • 4 个月前

Wow! This Changes Everything We Thought We Knew About Memory It is a groundbreaking big deal. TOU ARE MAKING GENERATIONAL MEMORIES RIGHT NOW IN EACH CELL! Scientists just found that your brain doesn’t just store memories — it stores the rules for how those memories will change in the future. A brand-new preprint from Stanford’s Greenleaf and Schnitzer labs (led by PhD student Yuxi Ke) drops a bombshell that feels like science fiction becoming reality overnight. For decades, neuroscientists have suspected that chromatin the DNA packaging material inside every cell nucleus might somehow “store” memory-related information. But what kind of information? Content? Timing? Rules? Now we have the answer! Using activity-dependent genetic tagging, fear conditioning, and single-nucleus multiome sequencing in the mouse medial prefrontal cortex (the brain’s long-term memory vault), the team tracked engram neurons for a full *month* after a memory was formed. What they discovered is electric: - One month after encoding, engram neurons have acquired a completely new chromatin landscape. - These chromatin changes are almost invisible at 7 days… but roar into existence by 28 days. - At recall, these engram cells don’t just “remember” better — they rewrite their entire transcriptional response. They preferentially fire up chromatin regulators, RNA processing machinery, and protein-turnover systems instead of simply boosting classic plasticity genes. In other words: the chromatin doesn’t just hold the memory of the past. It holds metaplastic instructions— rules that dictate how the neuron will respond the next time the memory is triggered. They call it chromatin metaplasticity. This is the “future tense of memory.” It is a massive deal 1. Memory is not just synapses. For 70+ years we’ve been obsessed with synaptic weights. This work proves the nucleus itself is a computational device that stores history-dependent rules. 2. It explains remote memory. The chromatin signature keeps maturing for weeks after the experience, perfectly matching the time course of systems consolidation into the cortex. 3. It’s energy-efficient genius. Instead of constantly maintaining memory proteins, the cell stores a silent, writable program that only activates when needed. Nature’s version of lazy evaluation. 4. It links development to adult memory. The late chromatin state is enriched for the exact same transcription-factor motifs used in embryonic development. Your adult brain is still running developmental software to lock in lifelong memories. 5. Huge therapeutic potential. If we can read or rewrite these chromatin metaplastic rules, we might one day boost failing remote memories in Alzheimer’s… or selectively dampen traumatic ones. This isn’t incremental. But a brand new layer of the memory code. And it explains WHY a person can receive memory from an organ transplant. It also explains generational traumas. Link: The future of neuroscience just got a lot more exciting and a lot more nuclear. Your chromatin is writing tomorrow’s memories today. And we finally have the first page of the instruction manual.
0:24

Wow! This Changes Everything We Thought We Knew About Memory It is a groundbreaking big deal. TOU ARE MAKING GENERATIONAL MEMORIES RIGHT NOW IN EACH CELL! Scientists just found that your brain doesn’t just store memories — it stores the rules for how those memories will change in the future. A brand-new preprint from Stanford’s Greenleaf and Schnitzer labs (led by PhD student Yuxi Ke) drops a bombshell that feels like science fiction becoming reality overnight. For decades, neuroscientists have suspected that chromatin the DNA packaging material inside every cell nucleus might somehow “store” memory-related information. But what kind of information? Content? Timing? Rules? Now we have the answer! Using activity-dependent genetic tagging, fear conditioning, and single-nucleus multiome sequencing in the mouse medial prefrontal cortex (the brain’s long-term memory vault), the team tracked engram neurons for a full *month* after a memory was formed. What they discovered is electric: - One month after encoding, engram neurons have acquired a completely new chromatin landscape. - These chromatin changes are almost invisible at 7 days… but roar into existence by 28 days. - At recall, these engram cells don’t just “remember” better — they rewrite their entire transcriptional response. They preferentially fire up chromatin regulators, RNA processing machinery, and protein-turnover systems instead of simply boosting classic plasticity genes. In other words: the chromatin doesn’t just hold the memory of the past. It holds metaplastic instructions— rules that dictate how the neuron will respond the next time the memory is triggered. They call it chromatin metaplasticity. This is the “future tense of memory.” It is a massive deal 1. Memory is not just synapses. For 70+ years we’ve been obsessed with synaptic weights. This work proves the nucleus itself is a computational device that stores history-dependent rules. 2. It explains remote memory. The chromatin signature keeps maturing for weeks after the experience, perfectly matching the time course of systems consolidation into the cortex. 3. It’s energy-efficient genius. Instead of constantly maintaining memory proteins, the cell stores a silent, writable program that only activates when needed. Nature’s version of lazy evaluation. 4. It links development to adult memory. The late chromatin state is enriched for the exact same transcription-factor motifs used in embryonic development. Your adult brain is still running developmental software to lock in lifelong memories. 5. Huge therapeutic potential. If we can read or rewrite these chromatin metaplastic rules, we might one day boost failing remote memories in Alzheimer’s… or selectively dampen traumatic ones. This isn’t incremental. But a brand new layer of the memory code. And it explains WHY a person can receive memory from an organ transplant. It also explains generational traumas. Link: The future of neuroscience just got a lot more exciting and a lot more nuclear. Your chromatin is writing tomorrow’s memories today. And we finally have the first page of the instruction manual.

Brian Roemmele

44,298 次观看 • 23 天前

Excited to release a new repo: abcGPT! It can be hard to "dial in" the voice you want from an LLM, because an LLM is a tangled superposition of millions of voices from millions of different authors around the world. Instead, frontier LLMs tend to give that slop-ish / generic / corporate tone that's hard to avoid, even with aggressive prompting and an informative context window. Lately I've been experimenting with some ideas on the fringes of attribution/unlearning, trying to make it so an AI user can "dial in" the specific voice/style/sources they want to use in a way that's more rigorous than prompting/context-engineering. and I'm starting to get pretty good results. the model below uses the following technique: - Take nanoGPT as written by Andrej Karpathy - Assign each neuron a random "specialty score" m between 0 and 1, sampled from a U-shape so most neurons land near 0 or near 1 with some in the middle. - Freeze this "m" for the lifetime of the network (it's the neuron's permanent corpus assignment) - Extend the forward() code with an α parameter, a kind of vibe-fader from 0 to 1. Think of each neuron's m as its position on that same slider. The slider acts like a spotlight: it lights up neurons whose m is near its current position, and silences those far away. Slide all the way to 0, and only TinyStories specialists fire. Slide all the way to 1, and only Shakespeare specialists fire. - Train this new nanoGPT on two datasets (in this case, TinyStories and Shakespeare) - During training, sample α from Beta(0.5, 0.5) AND draw the corpus from Bernoulli(α), so a Shakespeare batch tends to come with a high-α (Shakespeare-favoring) gate, and a TinyStories batch tends to come with low-α. - train until golden brown 🧑‍🍳 Perhaps surprisingly... it works! ¯\_(ツ)_/¯ The neurons we pre-assigned to Shakespeare learn to behave as Shakespeare specialists. the neurons we pre-assigned to TinyStories become children's-story specialists. the halfsies learn to bridge between them. After training, you can play with the kindof... vibe dial... you can "dial in" the voice you want during inference, by choosing whether to lean on Shakespeare or TinyStories neurons more or less. 📀💿 When you fully dial in Shakespeare neurons, the model only outputs tokens which look like Shakespeare, and when you fully dial in TinyStories, the model only outputs tokens which look like children's stories, and... (honestly this was the hard part)... everywhere inbetween! In a way, it's partitioning statistical signal into fuzzy segments, and then the end user can choose which pre-training data sources they want to lean upon for generation... and how much. My goal was to get a version of this working at scale, with clear intuition for why it works, and I'd like to explore ways to scale up this effect to large numbers of sources and larger models, and study the interplay between individuality/generality as scale increases. Link to repo and a detailed walkthrough of the abcGPT methodology in the reply.
0:31

Excited to release a new repo: abcGPT! It can be hard to "dial in" the voice you want from an LLM, because an LLM is a tangled superposition of millions of voices from millions of different authors around the world. Instead, frontier LLMs tend to give that slop-ish / generic / corporate tone that's hard to avoid, even with aggressive prompting and an informative context window. Lately I've been experimenting with some ideas on the fringes of attribution/unlearning, trying to make it so an AI user can "dial in" the specific voice/style/sources they want to use in a way that's more rigorous than prompting/context-engineering. and I'm starting to get pretty good results. the model below uses the following technique: - Take nanoGPT as written by Andrej Karpathy - Assign each neuron a random "specialty score" m between 0 and 1, sampled from a U-shape so most neurons land near 0 or near 1 with some in the middle. - Freeze this "m" for the lifetime of the network (it's the neuron's permanent corpus assignment) - Extend the forward() code with an α parameter, a kind of vibe-fader from 0 to 1. Think of each neuron's m as its position on that same slider. The slider acts like a spotlight: it lights up neurons whose m is near its current position, and silences those far away. Slide all the way to 0, and only TinyStories specialists fire. Slide all the way to 1, and only Shakespeare specialists fire. - Train this new nanoGPT on two datasets (in this case, TinyStories and Shakespeare) - During training, sample α from Beta(0.5, 0.5) AND draw the corpus from Bernoulli(α), so a Shakespeare batch tends to come with a high-α (Shakespeare-favoring) gate, and a TinyStories batch tends to come with low-α. - train until golden brown 🧑‍🍳 Perhaps surprisingly... it works! ¯\_(ツ)_/¯ The neurons we pre-assigned to Shakespeare learn to behave as Shakespeare specialists. the neurons we pre-assigned to TinyStories become children's-story specialists. the halfsies learn to bridge between them. After training, you can play with the kindof... vibe dial... you can "dial in" the voice you want during inference, by choosing whether to lean on Shakespeare or TinyStories neurons more or less. 📀💿 When you fully dial in Shakespeare neurons, the model only outputs tokens which look like Shakespeare, and when you fully dial in TinyStories, the model only outputs tokens which look like children's stories, and... (honestly this was the hard part)... everywhere inbetween! In a way, it's partitioning statistical signal into fuzzy segments, and then the end user can choose which pre-training data sources they want to lean upon for generation... and how much. My goal was to get a version of this working at scale, with clear intuition for why it works, and I'd like to explore ways to scale up this effect to large numbers of sources and larger models, and study the interplay between individuality/generality as scale increases. Link to repo and a detailed walkthrough of the abcGPT methodology in the reply.

⿻ Andrew Trask

134,902 次观看 • 3 个月前

Today: a 1.5 hour interview with the co-founders of Coherence Neuro: Ben Woodington and Elise Jenkins They are, as far as i can tell, the only (neurotechnology x oncology) startup that exists today. 'Neurotechnology? For cancer?' you may ask. Yes! As it turns out, tumors interact with the nervous system a fair bit, and you can use the very same neuromodulation toolbox that exists for neuropsychiatric conditions, for monitoring and treating cancer. Coherence has built an invasive device to place at the site of a tumor to do exactly this. Their first indication is a form of brain cancer called glioblastoma; one of the most fatal subtypes of cancer to exist today. The standard of care (with one exception that we discuss) has not changed in 25 years. If Coherence works out, and there is a very real chance they will, that may change. Most interesting of all is that Coherence believes that the bioelectric properties of cancer are not just worth poking at for brain cancers, but for all cancers. And maybe even for diseases outside of it! This conversation covers how Coherence’s first neurotech device (SOMA) works, the molecular reasons behind why neuromodulation affects cancer at all, what the biomarker readouts look like, the obvious Michael Levin comparison, and a lot more. Also: shout to Nicole for setting up the connection here in the first place! Crazy to think that a meeting in mid-2025 ended up leading to this Youtube/Spotify/Apple Podcasts links in replies 0:00:00 - Introduction 0:01:42 - How is SOMA different from Novocure’s Optune? 0:08:57 - Why does neuromodulation affect cancer at all? 0:13:28 - How was cancer-nervous system crosstalk first discovered? 0:15:42 - Anti-epileptics and beta blockers as accidental cancer drugs 0:17:38 - What is molecularly happening when you block cancer-neuron crosstalk? 0:19:50 - What is SOMA actually reading out as a biomarker? 0:20:44 - What does it mean that cancer is “very electric”? 0:22:02 - Can you derive universal biomarkers across patients? 0:23:09 - How is the device placed? 0:24:45 - How does the blocking stimulation regime work? 0:26:43 - Is it fair to say this is closed loop? 0:29:05 - Why not just spam the tumor with constant stimulation? 0:32:31 - Why MRI safety is non-negotiable for oncology devices 0:33:35 - Walk us through the patient journey from diagnosis to implantation 0:36:13 - The Michael Levin question: can you reprogram cancer back to normal? 0:42:29 - Efficacy, hospice settings, and the utility of the neuromodulation literature 0:45:52 - Why start with glioblastoma instead of an easier cancer? 0:48:57 - Regulatory strategy and the reimbursement threat 0:55:37 - How well does mouse-to-human translation work for neuromodulation? 0:55:57 - What do in silico models of neuromodulation look like? 0:58:09 - Why didn’t this exist 10 years ago? 1:01:48 - The founding story 1:06:38 - Why build your own device instead of using off-the-shelf arrays? 1:08:35 - Speaking with glioblastoma patients 1:12:04 - What was it like to raise money for this? 1:13:56 - Beyond cancer: TBI, lung disease, and the pan-disease argument 1:17:40 - Hiring at Coherence + what is the hardest type of talent to find 1:23:17 - What would you do with $100M equity-free? 1:27:15 - Are you a neurotech company or a cancer company?
1:33:20

Today: a 1.5 hour interview with the co-founders of Coherence Neuro: Ben Woodington and Elise Jenkins They are, as far as i can tell, the only (neurotechnology x oncology) startup that exists today. 'Neurotechnology? For cancer?' you may ask. Yes! As it turns out, tumors interact with the nervous system a fair bit, and you can use the very same neuromodulation toolbox that exists for neuropsychiatric conditions, for monitoring and treating cancer. Coherence has built an invasive device to place at the site of a tumor to do exactly this. Their first indication is a form of brain cancer called glioblastoma; one of the most fatal subtypes of cancer to exist today. The standard of care (with one exception that we discuss) has not changed in 25 years. If Coherence works out, and there is a very real chance they will, that may change. Most interesting of all is that Coherence believes that the bioelectric properties of cancer are not just worth poking at for brain cancers, but for all cancers. And maybe even for diseases outside of it! This conversation covers how Coherence’s first neurotech device (SOMA) works, the molecular reasons behind why neuromodulation affects cancer at all, what the biomarker readouts look like, the obvious Michael Levin comparison, and a lot more. Also: shout to Nicole for setting up the connection here in the first place! Crazy to think that a meeting in mid-2025 ended up leading to this Youtube/Spotify/Apple Podcasts links in replies 0:00:00 - Introduction 0:01:42 - How is SOMA different from Novocure’s Optune? 0:08:57 - Why does neuromodulation affect cancer at all? 0:13:28 - How was cancer-nervous system crosstalk first discovered? 0:15:42 - Anti-epileptics and beta blockers as accidental cancer drugs 0:17:38 - What is molecularly happening when you block cancer-neuron crosstalk? 0:19:50 - What is SOMA actually reading out as a biomarker? 0:20:44 - What does it mean that cancer is “very electric”? 0:22:02 - Can you derive universal biomarkers across patients? 0:23:09 - How is the device placed? 0:24:45 - How does the blocking stimulation regime work? 0:26:43 - Is it fair to say this is closed loop? 0:29:05 - Why not just spam the tumor with constant stimulation? 0:32:31 - Why MRI safety is non-negotiable for oncology devices 0:33:35 - Walk us through the patient journey from diagnosis to implantation 0:36:13 - The Michael Levin question: can you reprogram cancer back to normal? 0:42:29 - Efficacy, hospice settings, and the utility of the neuromodulation literature 0:45:52 - Why start with glioblastoma instead of an easier cancer? 0:48:57 - Regulatory strategy and the reimbursement threat 0:55:37 - How well does mouse-to-human translation work for neuromodulation? 0:55:57 - What do in silico models of neuromodulation look like? 0:58:09 - Why didn’t this exist 10 years ago? 1:01:48 - The founding story 1:06:38 - Why build your own device instead of using off-the-shelf arrays? 1:08:35 - Speaking with glioblastoma patients 1:12:04 - What was it like to raise money for this? 1:13:56 - Beyond cancer: TBI, lung disease, and the pan-disease argument 1:17:40 - Hiring at Coherence + what is the hardest type of talent to find 1:23:17 - What would you do with $100M equity-free? 1:27:15 - Are you a neurotech company or a cancer company?

owl

37,510 次观看 • 6 个月前