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A FLY BRAIN COULD CHANGE HOW BITCOIN MINING WORKS. Researchers FutureBit introduced HashFly, an experimental Bitcoin miner built around organic neurons from a fly brain. The idea sounds crazy, but the efficiency claim is even crazier: ~1 watt per terahash if scaled to real organic neurons. That would be... show more

Zentrix⌚️

4,507 subscribers

220,048 次观看 • 4 天前 •via X (Twitter)

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23 条评论

Marek Bialoglowy 的头像

Marek Bialoglowy4 天前

@FutureBit It's just matter of time until they wire up monkey brains for AI interference or to mine bitcoin, and after this ... we get matrix. We live in a simulation anyways, so this is simulation within simulation; kinda like in inception movie, but it's a reality not a dream.

Zentrix⌚️ 的头像

Zentrix⌚️4 天前

@FutureBit we're already closer than people think, live monkeys wired to computers for brain-machine research has been happening for years, mining bitcoin with a biological brain is just a weirder use case waiting to happen

Byron 的头像

Byron4 天前

@FutureBit bullshit again.

Zentrix⌚️ 的头像

Zentrix⌚️4 天前

@FutureBit bullish again?

Fajar M Reza 的头像

Fajar M Reza4 天前

@FutureBit Organic-neuron mining is intriguing, but reproducible efficiency benchmarks matter more than novelty.

Zentrix⌚️ 的头像

Zentrix⌚️4 天前

@FutureBit Exactly. The concept is fascinating, but real-world benchmarks will show whether biology can actually beat silicon

volovuk 的头像

volovuk4 天前

197.4 kH/s is the actual measured number in that screenshot. A modern ASIC does ~200+ TH/s — nine orders of magnitude higher. ‘If scaled to real neurons’ is carrying the entire claim, and nobody’s shown that biological spike rates scale linearly rather than hitting a wall from noise, timing jitter, or interconnect at any meaningful hash rate.

Zentrix⌚️ 的头像

Zentrix⌚️4 天前

@FutureBit Fair point. The scaling assumption is doing a lot of work here

M-studioAi 的头像

M-studioAi4 天前

@FutureBit A fly brain doing Bitcoin mining is crazy

Zentrix⌚️ 的头像

Zentrix⌚️4 天前

@FutureBit I don't know how anyone came up with this, but it's really crazy

neo 的头像

neo4 天前

@FutureBit Crypto bros are so funny. They see all as hashable or not. It's like, they ave the nails so everything looks like a hammer 🔨

Zentrix⌚️ 的头像

Zentrix⌚️4 天前

@FutureBit Haha, the hammer analogy is actually perfect 😂

Pepe 的头像

Pepe4 天前

@FutureBit A frog Brain will change that

Zentrix⌚️ 的头像

Zentrix⌚️4 天前

@FutureBit well, anything is possible😅

ROBINHOOD KING 👑🚀 的头像

ROBINHOOD KING 👑🚀4 天前

Hello 🚀 Do you need strong promotion for fast growth?

Zentrix⌚️ 的头像

Zentrix⌚️4 天前

I can offer you the same🙃

Bober_smart 的头像

Bober_smart4 天前

@FutureBit And this is real magic

Zentrix⌚️ 的头像

Zentrix⌚️4 天前

@FutureBit This world is going crazy, new scientific discoveries every day

just welly. 的头像

just welly.4 天前

@FutureBit 1 watt per terahash is a revolutionary

Zentrix⌚️ 的头像

Zentrix⌚️4 天前

@FutureBit I think so too my friend

Eceertrey 的头像

Eceertrey4 天前

@FutureBit sweet

Zentrix⌚️ 的头像

Zentrix⌚️4 天前

@FutureBit This is really something new and shocking

ks. Robert Wawer SJ 的头像

ks. Robert Wawer SJ4 天前

@FutureBit 🎯

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SOMEONE UPLOADED A REAL FLY BRAIN TO GITHUB. IT IS TRADING CRYPTO RIGHT NOW. This is not an AI. An actual mapped biological connectome (166,700 neurons) is doing real work across 5 insane open-source repositories. 1. stonkfly (646 stars) A fly brain trading Bitcoin. It watches BTC charts through digitized eye cells and places orders via Coinbase API. Profits trigger virtual dopamine neurons. 2. desktop-fly (946 stars) A 3D fly living on your desktop. 668 neurons dodge your mouse cursor using real biological escape circuits. 3. doomfly (263 stars) Plugging raw DOOM pixels directly into optical cells. It failed the learning benchmarks, but the open-source repo is live with all data. 4. fly64 (38 stars) The fly brain plays Super Mario 64. Firing escape neurons forces Mario to jump. Zero machine learning, just mapped biology. 5. ommatid (brand new) A 165,000 neuron connectome running on a basic Raspberry Pi, navigating a physical six-legged robot using a live camera feed. The entire Drosophila connectome is completely free under CC-BY licensing. Full list of repos in first reply ↓

shmidt

27,391 次观看 • 3 天前

Every time someone tells me AI will soon surpass the human brain, I pause. An NVIDIA H100 can perform around 200 trillion operations per second. It requires massive power, cooling systems, and heavy infrastructure. Your brain? Roughly one quadrillion synaptic operations per second. Running on about 20 watts. Less than a dim light bulb. We celebrate AI for its scale and speed. But it depends on predefined architectures, labeled data, and external power. The brain learns continuously. Adapts without instructions. Integrates emotion into decisions. Generates original thought under uncertainty. This gap is not just about intelligence. It is about efficiency and adaptability shaped by millions of years of evolution. AI will dominate narrow domains. But the human brain remains the most energy-efficient, flexible computing system we know. Are we underestimating biology while overestimating silicon? #AI #ArtificialIntelligence #Neuroscience #DeepTech #Innovation #FutureOfTechnology

Every time someone tells me AI will soon surpass the human brain, I pause. An NVIDIA H100 can perform around 200 trillion operations per second. It requires massive power, cooling systems, and heavy infrastructure. Your brain? Roughly one quadrillion synaptic operations per second. Running on about 20 watts. Less than a dim light bulb. We celebrate AI for its scale and speed. But it depends on predefined architectures, labeled data, and external power. The brain learns continuously. Adapts without instructions. Integrates emotion into decisions. Generates original thought under uncertainty. This gap is not just about intelligence. It is about efficiency and adaptability shaped by millions of years of evolution. AI will dominate narrow domains. But the human brain remains the most energy-efficient, flexible computing system we know. Are we underestimating biology while overestimating silicon? #AI #ArtificialIntelligence #Neuroscience #DeepTech #Innovation #FutureOfTechnology

Pascal Bornet

31,249 次观看 • 6 个月前

The fruit fly's brain is superior to the human brain, and GPT-6 ASTRA has proven this. And the internet went crazy. Most AI models learn by training on massive datasets, running billions of computations to acquire new skills. But researchers just demonstrated a radically different approach: No giant dataset. No traditional training. Just take the physical wiring of a biological brain and simulate it in a computer. The digital fruit fly reached ~91% behavioral accuracy using only 4 things: The complete neural connectivity map Synaptic connection counts as connection weights Excitatory vs inhibitory neuron types A simple Leaky Integrate-and-Fire model The wild part? The wiring itself may contain much more of the brain’s “code” than we thought. From tens of thousands of neurons in a fly → millions in a mouse → ~86 billion in a human. If this scales, whole-brain simulation could become one of the biggest frontiers in AI. The era of biologically inspired intelligence may have just begun

The fruit fly's brain is superior to the human brain, and GPT-6 ASTRA has proven this. And the internet went crazy. Most AI models learn by training on massive datasets, running billions of computations to acquire new skills. But researchers just demonstrated a radically different approach: No giant dataset. No traditional training. Just take the physical wiring of a biological brain and simulate it in a computer. The digital fruit fly reached ~91% behavioral accuracy using only 4 things: The complete neural connectivity map Synaptic connection counts as connection weights Excitatory vs inhibitory neuron types A simple Leaky Integrate-and-Fire model The wild part? The wiring itself may contain much more of the brain’s “code” than we thought. From tens of thousands of neurons in a fly → millions in a mouse → ~86 billion in a human. If this scales, whole-brain simulation could become one of the biggest frontiers in AI. The era of biologically inspired intelligence may have just begun

Zentrix⌚️

101,277 次观看 • 6 天前

A DEAD FLY IS DRIVING MY ROBOT RIGHT NOW. Not a metaphor. A reconstructed neural map of a fruit fly - 166,700 neurons, 25.6 million synapses - is now running on my MacBook and steering a quadruped robot in my living room. Here's how it works: 1. MaleCNS - a full connectome reconstruction of an adult fly brain - runs as a live simulation on my laptop. 2. I used Codex to build a decoder that reads the simulation's neural activity and turns it into movement commands: forward, left, right. 3. Those commands get sent over Wi-Fi to the robot, which still uses its own firmware to drive all 12 servos. The brain only decides where to go, not how to move each leg. No scripts. No prerecorded paths. The simulation runs continuously, live, while the robot walks. The fly has been dead for years. But its reconstructed nervous system is producing real decisions again, in real time, controlling a machine that didn't exist when it was alive. Next step: feed the robot's sensors back into the simulation and close the loop. A dead brain that can finally feel the world it's walking through. This fly has been dead for years. Its brain runs on my laptop. Its decisions move a machine through my living room. One dead nervous system, walking again.

A DEAD FLY IS DRIVING MY ROBOT RIGHT NOW. Not a metaphor. A reconstructed neural map of a fruit fly - 166,700 neurons, 25.6 million synapses - is now running on my MacBook and steering a quadruped robot in my living room. Here's how it works: 1. MaleCNS - a full connectome reconstruction of an adult fly brain - runs as a live simulation on my laptop. 2. I used Codex to build a decoder that reads the simulation's neural activity and turns it into movement commands: forward, left, right. 3. Those commands get sent over Wi-Fi to the robot, which still uses its own firmware to drive all 12 servos. The brain only decides where to go, not how to move each leg. No scripts. No prerecorded paths. The simulation runs continuously, live, while the robot walks. The fly has been dead for years. But its reconstructed nervous system is producing real decisions again, in real time, controlling a machine that didn't exist when it was alive. Next step: feed the robot's sensors back into the simulation and close the loop. A dead brain that can finally feel the world it's walking through. This fly has been dead for years. Its brain runs on my laptop. Its decisions move a machine through my living room. One dead nervous system, walking again.

kiruwaaaa

73,493 次观看 • 3 天前

There's a fruit fly walking around right now that was never born. eon just released a video where they took a real fly's connectome — the wiring diagram of its brain — and simulated it. Dropped it into a virtual body. It started walking. Grooming. Feeding. Doing what flies do. Nobody taught it to walk. No training data, no gradient descent toward fly-like behavior. This is the opposite of how AI works. They rebuilt the mind from the inside, neuron by neuron, and behavior just... emerged. It's the first time a biological organism has been recreated not by modeling what it does, but by modeling what it is. A human brain is 6 OOM more neurons. That's a scaling problem, something we've gotten very good at solving. So what happens when we have a working copy of the human mind?

There's a fruit fly walking around right now that was never born. eon just released a video where they took a real fly's connectome — the wiring diagram of its brain — and simulated it. Dropped it into a virtual body. It started walking. Grooming. Feeding. Doing what flies do. Nobody taught it to walk. No training data, no gradient descent toward fly-like behavior. This is the opposite of how AI works. They rebuilt the mind from the inside, neuron by neuron, and behavior just... emerged. It's the first time a biological organism has been recreated not by modeling what it does, but by modeling what it is. A human brain is 6 OOM more neurons. That's a scaling problem, something we've gotten very good at solving. So what happens when we have a working copy of the human mind?

hattie

9,588,015 次观看 • 6 个月前

Can living brain cells unlock the next big breakthrough in AI? Neurosurgeon turned founder Alex Ksendzovsky thinks so. His startup The Biological Computing Co. (TBC) trains AI models that he claims are as much as 27x more efficient by taking advantage of the cheapest, best image processor available: the neuron. “I have about 500 million years of evidence behind me,” he says. “So our moat is evolution.” TBC has raised more than $25M and is already in the market with its models. But its CEO is chasing a future straight out of sci-fi: real-time biological computing happening inside data centers. “We’re bringing something completely crazy to the world, and we’re showing that it works." On The Upstarts Podcast, we discuss why algorithms derived by brain cells beat ones only inspired by the brain; why models were the best place to start; and the ethics of using living neurons for training AI. Plus, Ksendzovksy shares his Upstart Moment: giving up a promising career in academia to pursue a high-risk startup. CHAPTERS 00:00 Introduction 01:12 Building software from wetware 05:09 A college idea to predict the stock market 08:40 The first test from an Airbnb 12:46 Rat neurons and electrodes 17:30 Pitching VCs with no data 24:52 Promising early AI results 31:09 The ethics of using neurons 34:40 ‘Our moat is evolution’ 35:38 A real-time biological computing future This season of the show is presented by Rippling 🫡

Can living brain cells unlock the next big breakthrough in AI? Neurosurgeon turned founder Alex Ksendzovsky thinks so. His startup The Biological Computing Co. (TBC) trains AI models that he claims are as much as 27x more efficient by taking advantage of the cheapest, best image processor available: the neuron. “I have about 500 million years of evidence behind me,” he says. “So our moat is evolution.” TBC has raised more than $25M and is already in the market with its models. But its CEO is chasing a future straight out of sci-fi: real-time biological computing happening inside data centers. “We’re bringing something completely crazy to the world, and we’re showing that it works." On The Upstarts Podcast, we discuss why algorithms derived by brain cells beat ones only inspired by the brain; why models were the best place to start; and the ethics of using living neurons for training AI. Plus, Ksendzovksy shares his Upstart Moment: giving up a promising career in academia to pursue a high-risk startup. CHAPTERS 00:00 Introduction 01:12 Building software from wetware 05:09 A college idea to predict the stock market 08:40 The first test from an Airbnb 12:46 Rat neurons and electrodes 17:30 Pitching VCs with no data 24:52 Promising early AI results 31:09 The ethics of using neurons 34:40 ‘Our moat is evolution’ 35:38 A real-time biological computing future This season of the show is presented by Rippling 🫡

Alex Konrad

12,577 次观看 • 3 个月前

Zebrafish NN It’s pretty amazing to learn that efforts to map the fruit FLY connectome (brain synapses) were successful and its amazing to see the digital fly brain successfully complete a whole series of tasks, including complex navigation of open worlds. The fruit fly is 160,000 neurons and 10^7 synapses. Teams are currently doing the same thing with a zebrafish which has a similar scale neuron count but 10x more synapses. Fly was 100TB raw data and Zebrafish is 200TB, so about 2x the raw data. For context a rodent is 70m neurons and 10^11 synapses. Rodents will come later. But this method looks like it creates totally outsized results with absolutely miniscule models. Zebrafish NN is a vertebrae connectome, it has much of the same basic structure as other vertebrae, unlike FLY connectome. We are just about used to LLMs and coding, but AI is really just beginning and there is a lot more, and a lot weirder stuff coming down the pipe. These connectomes have already shown to be incredibly resilient, you can blind their sensors and injure their outputs and they still succeed. They are incredibly compact. A whole lot of inanimate objects are going to get complete autonomy, totally offline, air gapped autonomy. They will be delivering pizzas and fighting wars. Connectomics is an opposite approach to LLMs but you can of course use LLMs to help develop connectomes. It’s amazing that you can take a biologically evolved brain, map it, produce a digital twin, and then run it at machine speed. Imagine a human brain accelerated from 100Hz neuron fires to 3,200,000,000Hz that a typical CPU runs at. That’s 30 million times faster. But would need 1-2 exabytes to map. Anyway “Zebrafish” is next.

Zebrafish NN It’s pretty amazing to learn that efforts to map the fruit FLY connectome (brain synapses) were successful and its amazing to see the digital fly brain successfully complete a whole series of tasks, including complex navigation of open worlds. The fruit fly is 160,000 neurons and 10^7 synapses. Teams are currently doing the same thing with a zebrafish which has a similar scale neuron count but 10x more synapses. Fly was 100TB raw data and Zebrafish is 200TB, so about 2x the raw data. For context a rodent is 70m neurons and 10^11 synapses. Rodents will come later. But this method looks like it creates totally outsized results with absolutely miniscule models. Zebrafish NN is a vertebrae connectome, it has much of the same basic structure as other vertebrae, unlike FLY connectome. We are just about used to LLMs and coding, but AI is really just beginning and there is a lot more, and a lot weirder stuff coming down the pipe. These connectomes have already shown to be incredibly resilient, you can blind their sensors and injure their outputs and they still succeed. They are incredibly compact. A whole lot of inanimate objects are going to get complete autonomy, totally offline, air gapped autonomy. They will be delivering pizzas and fighting wars. Connectomics is an opposite approach to LLMs but you can of course use LLMs to help develop connectomes. It’s amazing that you can take a biologically evolved brain, map it, produce a digital twin, and then run it at machine speed. Imagine a human brain accelerated from 100Hz neuron fires to 3,200,000,000Hz that a typical CPU runs at. That’s 30 million times faster. But would need 1-2 exabytes to map. Anyway “Zebrafish” is next.

Object Zero

637,790 次观看 • 5 天前

Excited to launch a new podcast dedicated to conversations on the future of neurotech, computing, intelligence, and more. First guest: Max Hodak founder & CEO of Science Corporation, which is building PRIMA, a retinal prosthetic that’s restoring meaningful vision for patients with blindness caused by age-related macular degeneration. Science is also developing a biohybrid brain implant that grows living neurons directly onto a silicon chip, then interfaces that system with the cortex. The possibility space here is vast and new. Imagine growing new areas of the brain. Sections 00:00 What counts as neurotech? 01:45 History of brain-computer interfaces and the smartphone dividend 07:25 PRIMA - How Science is restoring vision in blind patients 10:10 Why stimulating bipolar cells works when the optic nerve doesn't 30:30 Are we bottlenecked by biology or engineering? 32:40 Expanding the brain's bandwidth beyond 10 bits per second 37:00 Can we add new areas to the brain? 37:46 Biohybrid BCIs: neurons growing on a chip 39:20 What could neural augmentation look like? 01:13:20 How Science drives Fast R&D 01:44:00 How founders learn and level up This is the kind of discussion I’m excited to explore on this podcast. Enjoy! Full Episode 1 here and in links below.

Excited to launch a new podcast dedicated to conversations on the future of neurotech, computing, intelligence, and more. First guest: Max Hodak founder & CEO of Science Corporation, which is building PRIMA, a retinal prosthetic that’s restoring meaningful vision for patients with blindness caused by age-related macular degeneration. Science is also developing a biohybrid brain implant that grows living neurons directly onto a silicon chip, then interfaces that system with the cortex. The possibility space here is vast and new. Imagine growing new areas of the brain. Sections 00:00 What counts as neurotech? 01:45 History of brain-computer interfaces and the smartphone dividend 07:25 PRIMA - How Science is restoring vision in blind patients 10:10 Why stimulating bipolar cells works when the optic nerve doesn't 30:30 Are we bottlenecked by biology or engineering? 32:40 Expanding the brain's bandwidth beyond 10 bits per second 37:00 Can we add new areas to the brain? 37:46 Biohybrid BCIs: neurons growing on a chip 39:20 What could neural augmentation look like? 01:13:20 How Science drives Fast R&D 01:44:00 How founders learn and level up This is the kind of discussion I’m excited to explore on this podcast. Enjoy! Full Episode 1 here and in links below.

Juan Benet

405,188 次观看 • 5 个月前

BITCOIN RAILS #46: BITCOIN MINING IN THE AGE OF AI | with MARA CEO Fred Thiel 🔗 YOUTUBE: 🌿 SPOTIFY: In response to the AI-driven shock in global demand for computing power, large players in the Bitcoin mining industry have been forced to make significant strategic shifts to remain competitive. MARA — the largest Bitcoin miner in the world by hashrate — is emerging as one of the more well-positioned beneficiaries of these changing tides, having transitioned from an “asset-light” strategy (via hosted mining at third-party facilities) to an “asset-heavy” approach (owning its own land, power, and infrastructure) just ahead of the AI compute wave in 2024/25. I sat down with MARA CEO Fred Thiel to discuss how these shifting industry dynamics are playing out in practice — as well as his perspective on how key mining-related security and infrastructure issues may evolve in the coming months and years. In this episode, we cover: — How MARA scaled from near-zero hash rate in 2020 to the largest Bitcoin miner globally by the end of 2023 — Key differences between operating Bitcoin mining facilities versus AI data centers, and where the two models meaningfully intersect — Why ownership of power generation — rather than reliance on PPAs — may represent a durable competitive edge for miners and AI data center operators over time — Why Bitcoin may be entering its “IPO phase,” and why recent price corrections could reflect increasing market maturity rather than structural weakness We also explore more technical and often under-discussed topics, such as heat reuse, open-source mining technologies, and the implications of US policy goals around Bitcoin mining. This episode offers a grounded, operator-level view of where Bitcoin mining is headed, informed by one of the most influential leaders in the public mining sector. This episode of Bitcoin Rails is powered by: — Best In Slot (Best in Slot | BRC2.0 🧑‍🍳) — the leading API for Ordinals and BRC-20 data aggregation and indexing. — Spark (Lightspark) — a statechains implementation advancing Bitcoin-powered payments. — Citrea (Citrea | Mainnet Live 🍊🍋) — a leading Bitcoin rollup technology and BitVM alliance contributor. TIMESTAMPS 📌 00:00 Intro 01:09 From Marathon Patent Group to MARA 06:35 Why Owning Infrastructure is Key 07:46 First Public Companies Mining Bitcoin 09:54 Data Centers For AI vs Bitcoin Mining Facilities 14:07 How AI Data Centers Will Look Going Forward 15:37 How MARA is Diversifying From Bitcoin Mining 19:03 Private Cloud and Data Security 22:20 The Exaion Partnership 26:03 Future of Bitcoin and AI 40:22 Innovative Approaches to AI and Bitcoin Mining 42:06 Challenges and Opportunities in Power Generation 45:38 Strategic International Partnerships 50:43 The Future of Real World Assets 53:53 Bitcoin Mining in China 57:24 Why MARA Runs Their Own Software 01:00:19 Where is Bitcoin Mining Headed 01:04:17 Benefits of Running a Mining Pool 01:07:17 Heat Reuse in Mining 01:12:23 The Role of Data Centers in Power Generation

BITCOIN RAILS #46: BITCOIN MINING IN THE AGE OF AI | with MARA CEO Fred Thiel 🔗 YOUTUBE: 🌿 SPOTIFY: In response to the AI-driven shock in global demand for computing power, large players in the Bitcoin mining industry have been forced to make significant strategic shifts to remain competitive. MARA — the largest Bitcoin miner in the world by hashrate — is emerging as one of the more well-positioned beneficiaries of these changing tides, having transitioned from an “asset-light” strategy (via hosted mining at third-party facilities) to an “asset-heavy” approach (owning its own land, power, and infrastructure) just ahead of the AI compute wave in 2024/25. I sat down with MARA CEO Fred Thiel to discuss how these shifting industry dynamics are playing out in practice — as well as his perspective on how key mining-related security and infrastructure issues may evolve in the coming months and years. In this episode, we cover: — How MARA scaled from near-zero hash rate in 2020 to the largest Bitcoin miner globally by the end of 2023 — Key differences between operating Bitcoin mining facilities versus AI data centers, and where the two models meaningfully intersect — Why ownership of power generation — rather than reliance on PPAs — may represent a durable competitive edge for miners and AI data center operators over time — Why Bitcoin may be entering its “IPO phase,” and why recent price corrections could reflect increasing market maturity rather than structural weakness We also explore more technical and often under-discussed topics, such as heat reuse, open-source mining technologies, and the implications of US policy goals around Bitcoin mining. This episode offers a grounded, operator-level view of where Bitcoin mining is headed, informed by one of the most influential leaders in the public mining sector. This episode of Bitcoin Rails is powered by: — Best In Slot (Best in Slot | BRC2.0 🧑‍🍳) — the leading API for Ordinals and BRC-20 data aggregation and indexing. — Spark (Lightspark) — a statechains implementation advancing Bitcoin-powered payments. — Citrea (Citrea | Mainnet Live 🍊🍋) — a leading Bitcoin rollup technology and BitVM alliance contributor. TIMESTAMPS 📌 00:00 Intro 01:09 From Marathon Patent Group to MARA 06:35 Why Owning Infrastructure is Key 07:46 First Public Companies Mining Bitcoin 09:54 Data Centers For AI vs Bitcoin Mining Facilities 14:07 How AI Data Centers Will Look Going Forward 15:37 How MARA is Diversifying From Bitcoin Mining 19:03 Private Cloud and Data Security 22:20 The Exaion Partnership 26:03 Future of Bitcoin and AI 40:22 Innovative Approaches to AI and Bitcoin Mining 42:06 Challenges and Opportunities in Power Generation 45:38 Strategic International Partnerships 50:43 The Future of Real World Assets 53:53 Bitcoin Mining in China 57:24 Why MARA Runs Their Own Software 01:00:19 Where is Bitcoin Mining Headed 01:04:17 Benefits of Running a Mining Pool 01:07:17 Heat Reuse in Mining 01:12:23 The Role of Data Centers in Power Generation

Isabel Foxen Duke⚡️

31,915 次观看 • 8 个月前

Did Epstein influence Bitcoin core development? Short answer: No. This is not how Bitcoin works. Here’s what happened: Epstein donated to MIT Media Lab…who in turn supported MIT Digital Currency Initiative…which in turn funded Bitcoin developers. These devs used to be funded by The Bitcoin Foundation (which I used to run as volunteer Executive Director) there are many devs and no dev or team had power or control over Bitcoin. Under MIT’s patronage the devs had the same deal they had with us at The Bitcoin Foundation: that they could work on the code and not have direction from the org. More importantly — how Bitcoin works is that *even if* a dev was compromised then the nodes and miners would still have to run that code to make it included in Bitcoin. So for example if I had somehow asked the devs paid by Bitcoin Foundation to “add 1000 coins for Bruce” 1) they wouldn’t have done this / it would have been counter to our agreement 2) no miners would run that code & no nodes would recognize it. It would be a laughing stock and completely rejected. Does this mean code dev is not an attack vector? No. It’s still a risk. Particularly with nation state style actors and very careful efforts to co-opt which are much more sophisticated than “give Bruce coins” or something. This is one reason I’m cautious of Bitcoin core funding - especially from actors who’ve had bad judgment in the past. I think we should be cautious of who does the dev and view it as an attack vector. Bitcoin code is transparent and has lots of eyes on it. So in this case especially there isn’t even a solid accusation, let alone evidence that MIT directed nefarious code changes. If that was an allegation the first question should be: well what code specifically did MIT direct and what proof is there and how was it harmful? I think claims around this would collapse. There’s obviously plenty to criticize about Epstein and MIT working with him — and when it comes to digital assets MIT’s work with Gensler and especially its work on CBDCs is much more suspect than the chance that malicious code was pushed through on Bitcoin. Be cautious but this is a nothing burger

Did Epstein influence Bitcoin core development? Short answer: No. This is not how Bitcoin works. Here’s what happened: Epstein donated to MIT Media Lab…who in turn supported MIT Digital Currency Initiative…which in turn funded Bitcoin developers. These devs used to be funded by The Bitcoin Foundation (which I used to run as volunteer Executive Director) there are many devs and no dev or team had power or control over Bitcoin. Under MIT’s patronage the devs had the same deal they had with us at The Bitcoin Foundation: that they could work on the code and not have direction from the org. More importantly — how Bitcoin works is that even if a dev was compromised then the nodes and miners would still have to run that code to make it included in Bitcoin. So for example if I had somehow asked the devs paid by Bitcoin Foundation to “add 1000 coins for Bruce” 1) they wouldn’t have done this / it would have been counter to our agreement 2) no miners would run that code & no nodes would recognize it. It would be a laughing stock and completely rejected. Does this mean code dev is not an attack vector? No. It’s still a risk. Particularly with nation state style actors and very careful efforts to co-opt which are much more sophisticated than “give Bruce coins” or something. This is one reason I’m cautious of Bitcoin core funding - especially from actors who’ve had bad judgment in the past. I think we should be cautious of who does the dev and view it as an attack vector. Bitcoin code is transparent and has lots of eyes on it. So in this case especially there isn’t even a solid accusation, let alone evidence that MIT directed nefarious code changes. If that was an allegation the first question should be: well what code specifically did MIT direct and what proof is there and how was it harmful? I think claims around this would collapse. There’s obviously plenty to criticize about Epstein and MIT working with him — and when it comes to digital assets MIT’s work with Gensler and especially its work on CBDCs is much more suspect than the chance that malicious code was pushed through on Bitcoin. Be cautious but this is a nothing burger

Bruce Fenton

232,025 次观看 • 7 个月前

Brain Parasites in MS Patients: Are We Missing the Real Enemy? Have we misunderstood multiple sclerosis all along? For decades, MS has been seen as an autoimmune disease—where the body attacks itself. But new research suggests something more sinister might be involved: parasites. Dr. Alan McDonald, a leading researcher in the field, has reported finding microscopic worms—nematodes—in the brain tissue of every MS patient he studied. These findings challenge the core assumptions of mainstream neurology. What if MS isn’t self-destruction, but a hidden war against invaders? This isn’t some remote, third-world threat. It could be happening here, right now. In some cases, spinal fluid from MS patients has shown signs of parasitic infection. These organisms aren’t passive. They consume brain tissue, damage neurons, and disrupt the nervous system from within. The idea may sound shocking, but it opens a new door. If parasites play a role in MS, new treatment options might emerge. Herbal detox protocols, long dismissed by conventional medicine, could help restore balance. The possibility is worth exploring—especially for those living with pain, fatigue, and uncertainty. This theory doesn’t claim to replace all we know about MS. But it adds a missing piece to the puzzle. And in medicine, sometimes one piece can change everything. Don’t stop asking questions. Don’t dismiss new ideas too quickly. Seeking truth from multiple angles might just lead to better care—and save lives.

Brain Parasites in MS Patients: Are We Missing the Real Enemy? Have we misunderstood multiple sclerosis all along? For decades, MS has been seen as an autoimmune disease—where the body attacks itself. But new research suggests something more sinister might be involved: parasites. Dr. Alan McDonald, a leading researcher in the field, has reported finding microscopic worms—nematodes—in the brain tissue of every MS patient he studied. These findings challenge the core assumptions of mainstream neurology. What if MS isn’t self-destruction, but a hidden war against invaders? This isn’t some remote, third-world threat. It could be happening here, right now. In some cases, spinal fluid from MS patients has shown signs of parasitic infection. These organisms aren’t passive. They consume brain tissue, damage neurons, and disrupt the nervous system from within. The idea may sound shocking, but it opens a new door. If parasites play a role in MS, new treatment options might emerge. Herbal detox protocols, long dismissed by conventional medicine, could help restore balance. The possibility is worth exploring—especially for those living with pain, fatigue, and uncertainty. This theory doesn’t claim to replace all we know about MS. But it adds a missing piece to the puzzle. And in medicine, sometimes one piece can change everything. Don’t stop asking questions. Don’t dismiss new ideas too quickly. Seeking truth from multiple angles might just lead to better care—and save lives.

Jack Straw

16,559 次观看 • 1 年前

Yes, Sam — but brains are far more energy efficient than computers. Brain: 20 watts AI: gigawatts Biology wins. Naveen Rao (Naveen Rao) CEO, Unconventional AI Konstantine Buhler (Konstantine Buhler) Partner, Sequoia Capital TLDR: Biology currently delivers far more general intelligence per watt than silicon. "Why can we not build a computer that acts like biology? The single thing that hit me when I was an undergrad, like 30 years ago, and that’s when I learned about 20 watts of energy in your brain, and just how biology kind of does computation. It doesn’t really do computation, by the way. It’s like dynamical systems, but we can get into that later. My whole career has been about that, actually. When I came out of undergrad, I was like, “Okay, well I wanna build computers. How do I build those?” So I actually became a computer architect. I worked on UltraSPARC III and a bunch of processors, then did a bunch of ASICs, then went back to school to do a PhD in neuroscience. And I’m like, “Okay, now I know how to build a machine. I’ve done it several times, sort of from scratch.” I’m still no closer to the answer of why computers aren’t as good as brains. At that time, we didn’t really understand what brains were doing. I think now we kind of do, but at that time we almost thought of brains as sort of magical." "But Naveen pointed out this is the moment to dramatically reduce power, which everybody knows is, if not the, major constraint of AI, and have a trade-off that’s much more reasonable in the AI world."

Yes, Sam — but brains are far more energy efficient than computers. Brain: 20 watts AI: gigawatts Biology wins. Naveen Rao (Naveen Rao) CEO, Unconventional AI Konstantine Buhler (Konstantine Buhler) Partner, Sequoia Capital TLDR: Biology currently delivers far more general intelligence per watt than silicon. "Why can we not build a computer that acts like biology? The single thing that hit me when I was an undergrad, like 30 years ago, and that’s when I learned about 20 watts of energy in your brain, and just how biology kind of does computation. It doesn’t really do computation, by the way. It’s like dynamical systems, but we can get into that later. My whole career has been about that, actually. When I came out of undergrad, I was like, “Okay, well I wanna build computers. How do I build those?” So I actually became a computer architect. I worked on UltraSPARC III and a bunch of processors, then did a bunch of ASICs, then went back to school to do a PhD in neuroscience. And I’m like, “Okay, now I know how to build a machine. I’ve done it several times, sort of from scratch.” I’m still no closer to the answer of why computers aren’t as good as brains. At that time, we didn’t really understand what brains were doing. I think now we kind of do, but at that time we almost thought of brains as sort of magical." "But Naveen pointed out this is the moment to dramatically reduce power, which everybody knows is, if not the, major constraint of AI, and have a trade-off that’s much more reasonable in the AI world."

Molly O’Shea

30,956 次观看 • 6 个月前

“Bitcoin is the most efficient market in history. We built the same thing for intelligence.” Const left Google Brain to build something Big Tech wouldn’t touch: open, permissionless AI that can be mined like Bitcoin. On a special TWiST deep dive, Bittensor’s co-founder breaks down the subnet economy, how subnets are making open models even cheaper to run, and why he doesn’t sell a token, but participation. cc: const, Openτensor Foundaτion, @jason, Lon Harris 0:00 The origin of Bittensor (and the name Const) 10:48 Northwest Registered Agent - Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity — Learn more at 13:55 From Bitcoin mining to mining intelligence 19:33 DigitalOcean - Head to to start building on DigitalOcean's AI-Native Cloud today — and cut your AI workload costs by up to 50%. 30:17 Odoo - The all-in-one business platform. Get started for free at 32:37 What is a subnet? 33:35 Forcing honest inference from bad actors 37:14 Building a subnet is harder than it looks 40:42 Understanding dTAO 51:57 Where the registration TAO actually goes 1:02:57 All about the Conviction "rug pull" 1:15:19 How Const is making himself irrelevant 1:17:33 The "Buy One TAO" philosophy 🎥 Watch the full episode here 👇

“Bitcoin is the most efficient market in history. We built the same thing for intelligence.” Const left Google Brain to build something Big Tech wouldn’t touch: open, permissionless AI that can be mined like Bitcoin. On a special TWiST deep dive, Bittensor’s co-founder breaks down the subnet economy, how subnets are making open models even cheaper to run, and why he doesn’t sell a token, but participation. cc: const, Openτensor Foundaτion, @jason, Lon Harris 0:00 The origin of Bittensor (and the name Const) 10:48 Northwest Registered Agent - Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity — Learn more at 13:55 From Bitcoin mining to mining intelligence 19:33 DigitalOcean - Head to to start building on DigitalOcean's AI-Native Cloud today — and cut your AI workload costs by up to 50%. 30:17 Odoo - The all-in-one business platform. Get started for free at 32:37 What is a subnet? 33:35 Forcing honest inference from bad actors 37:14 Building a subnet is harder than it looks 40:42 Understanding dTAO 51:57 Where the registration TAO actually goes 1:02:57 All about the Conviction "rug pull" 1:15:19 How Const is making himself irrelevant 1:17:33 The "Buy One TAO" philosophy 🎥 Watch the full episode here 👇

This Week in Startups

44,796 次观看 • 1 个月前

𝗦𝘂𝗽𝗲𝗿𝗿𝗮𝗱𝗶𝗮𝗻𝗰𝗲 𝗶𝗻 𝗠𝗶𝗰𝗿𝗼𝘁𝘂𝗯𝘂𝗹𝗲𝘀: 𝗔 𝗚𝗹𝗶𝗺𝗽𝘀𝗲 𝗜𝗻𝘁𝗼 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗕𝗶𝗼𝗹𝗼𝗴𝘆? Researchers may have just found quantum superpowers in microtubules. Yes, you read that right—quantum *superradiance* in the brain! Superradiance is a phenomenon where excited particles behave like a team, emitting photons collectively in a bright, ultra-fast burst. This is different from normal fluorescence, where photons are emitted slowly and individually. Imagine a synchronized light show on a quantum scale. The key ingredient? Quantum entanglement. If particles are spaced closer than the wavelength of incoming light, they form a collective quantum state. This allows them to act as one entity, amplifying energy release, just like a laser—but smaller in scale. The study zeroed in on tryptophan molecules inside microtubules. When hit with UV light, they emitted much more energy than regular fluorescence could explain—100 times more, to be exact. The researchers believe this can only happen through superradiance, implying large-scale quantum entanglement. If true, this discovery could be huge. It may hint that quantum effects play a bigger role in biology—and even in brain function—than we ever imagined. Could Penrose and the quantum brain theory be right after all? This clip is from "𝗪𝗮𝘀 𝗣𝗲𝗻𝗿𝗼𝘀𝗲 𝗥𝗶𝗴𝗵𝘁? 𝗡𝗘𝗪 𝗘𝗩𝗜𝗗𝗘𝗡𝗖𝗘 𝗙𝗼𝗿 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗘𝗳𝗳𝗲𝗰𝘁𝘀 𝗜𝗻 𝗧𝗵𝗲 𝗕𝗿𝗮𝗶𝗻" (PBS Space Time, YouTube, Jul 25, 2024)

𝗦𝘂𝗽𝗲𝗿𝗿𝗮𝗱𝗶𝗮𝗻𝗰𝗲 𝗶𝗻 𝗠𝗶𝗰𝗿𝗼𝘁𝘂𝗯𝘂𝗹𝗲𝘀: 𝗔 𝗚𝗹𝗶𝗺𝗽𝘀𝗲 𝗜𝗻𝘁𝗼 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗕𝗶𝗼𝗹𝗼𝗴𝘆? Researchers may have just found quantum superpowers in microtubules. Yes, you read that right—quantum superradiance in the brain! Superradiance is a phenomenon where excited particles behave like a team, emitting photons collectively in a bright, ultra-fast burst. This is different from normal fluorescence, where photons are emitted slowly and individually. Imagine a synchronized light show on a quantum scale. The key ingredient? Quantum entanglement. If particles are spaced closer than the wavelength of incoming light, they form a collective quantum state. This allows them to act as one entity, amplifying energy release, just like a laser—but smaller in scale. The study zeroed in on tryptophan molecules inside microtubules. When hit with UV light, they emitted much more energy than regular fluorescence could explain—100 times more, to be exact. The researchers believe this can only happen through superradiance, implying large-scale quantum entanglement. If true, this discovery could be huge. It may hint that quantum effects play a bigger role in biology—and even in brain function—than we ever imagined. Could Penrose and the quantum brain theory be right after all? This clip is from "𝗪𝗮𝘀 𝗣𝗲𝗻𝗿𝗼𝘀𝗲 𝗥𝗶𝗴𝗵𝘁? 𝗡𝗘𝗪 𝗘𝗩𝗜𝗗𝗘𝗡𝗖𝗘 𝗙𝗼𝗿 𝗤𝘂𝗮𝗻𝘁𝘂𝗺 𝗘𝗳𝗳𝗲𝗰𝘁𝘀 𝗜𝗻 𝗧𝗵𝗲 𝗕𝗿𝗮𝗶𝗻" (PBS Space Time, YouTube, Jul 25, 2024)

Ultra Skool 🧠

18,906 次观看 • 1 年前

🚨 SCIENTISTS JUST DISCOVERED A HIDDEN SIXTH SENSE IN HUMANS — WHAT ELSE IS HIDING INSIDE US? For centuries, humans have been told we have five senses. Sight. Hearing. Smell. Taste. Touch. But now scientists believe there may be a sixth. And it sounds like something straight out of science fiction. Researchers have reportedly found evidence that the human brain may be capable of detecting Earth's magnetic field. In other words? Humans may possess a hidden magnetic sixth sense. The same invisible force used by birds, sea turtles, sharks, and countless other animals to navigate across the planet without maps, GPS, or technology. Think about that for a second. An invisible force is passing through your body every second of every day. You can't see it. You can't hear it. You can't touch it. Yet scientists believe your brain may still be responding to it. In experiments, researchers reportedly observed changes in brain activity when magnetic fields around participants were altered. The participants weren't consciously aware anything had changed. But their brains appeared to react anyway. How much information is your brain processing that you never consciously experience? What if humans have been walking around with a hidden sixth sense this entire time? And if the brain can naturally detect magnetic fields, what else might it be capable of that science still doesn't understand? If this research is correct, this ability wasn't added to humans. It may have been there all along. Hidden in plain sight. If a hidden sixth sense can exist, what else do you think has been hiding in plain sight this entire time?

🚨 SCIENTISTS JUST DISCOVERED A HIDDEN SIXTH SENSE IN HUMANS — WHAT ELSE IS HIDING INSIDE US? For centuries, humans have been told we have five senses. Sight. Hearing. Smell. Taste. Touch. But now scientists believe there may be a sixth. And it sounds like something straight out of science fiction. Researchers have reportedly found evidence that the human brain may be capable of detecting Earth's magnetic field. In other words? Humans may possess a hidden magnetic sixth sense. The same invisible force used by birds, sea turtles, sharks, and countless other animals to navigate across the planet without maps, GPS, or technology. Think about that for a second. An invisible force is passing through your body every second of every day. You can't see it. You can't hear it. You can't touch it. Yet scientists believe your brain may still be responding to it. In experiments, researchers reportedly observed changes in brain activity when magnetic fields around participants were altered. The participants weren't consciously aware anything had changed. But their brains appeared to react anyway. How much information is your brain processing that you never consciously experience? What if humans have been walking around with a hidden sixth sense this entire time? And if the brain can naturally detect magnetic fields, what else might it be capable of that science still doesn't understand? If this research is correct, this ability wasn't added to humans. It may have been there all along. Hidden in plain sight. If a hidden sixth sense can exist, what else do you think has been hiding in plain sight this entire time?

HustleBitch

14,282 次观看 • 2 个月前

"Is Stretch really that innovative Bitcoin-backed credit, or is it just yield chasing right now?" David Duong on the real debate around Michael Saylor and Strategy "So far Saylor has demonstrated the ability to raise capital and grow his Bitcoin per share. That kind of stays ahead of the compounding dividend obligation he has. That engine so far has been running" "But is that an autopilot thing where he can just keep doing that in perpetuity? I don't have the answer to that. I don't think anyone does" "A lot of it comes down to Michael Saylor. How good is he at continuing this trend? I don't know what the answer is gonna be at the end of all things, but this is what a lot of people are internalizing at the moment"

"Is Stretch really that innovative Bitcoin-backed credit, or is it just yield chasing right now?" David Duong on the real debate around Michael Saylor and Strategy "So far Saylor has demonstrated the ability to raise capital and grow his Bitcoin per share. That kind of stays ahead of the compounding dividend obligation he has. That engine so far has been running" "But is that an autopilot thing where he can just keep doing that in perpetuity? I don't have the answer to that. I don't think anyone does" "A lot of it comes down to Michael Saylor. How good is he at continuing this trend? I don't know what the answer is gonna be at the end of all things, but this is what a lot of people are internalizing at the moment"

The Wolf Of All Streets

16,229 次观看 • 3 个月前

Michael Saylor's end game is to buy $3 trillion worth of #Bitcoin! 👀 Microstrategy could, CONSERVATIVELY, own approximately 16% of the total Bitcoin Supply or 3,439,002 Bitcoin!! For those that think this is a MOONBOI projection, listen to the video clip below, VERY CLOSELY, and you will hear him say that he plans on buying $3 trillion worth of Bitcoin 🤯 Even if Saylor buys $3 trillion worth of Bitcoin, at an average price of $1 million per coin, he would be able to buy 3,000,000 Bitcoin! Check my math! This would CONSERVATIVELY bring his total Bitcoin holdings to 3,444,262, or 16% of the total Bitcoin Supply!! Saylor could single handedly jack the price of Bitcoin to $1 million per coin and Samson Mow's Omega candle could be coming in 2025. What going to happen when Nation States, Google, Amazon, Facebook and billions of people complement Saylor's $3 trillion purchase? What is bigger than an omega candle? I asked GROK and it doesn't even know! 😂 I think we should name it the ♾️ candle. This would be representative of Wicked's Stock to Fomo model (see graphic below) and his post: Saylor has said he is going to double his $42 Billion Bitcoin investment at least 4 times and here is how this could lead to him acquiring more than 4 million Bitcoin in 2025: Q1 2025 - Raise $84 Billion to buy 700,000 Bitcoin at average price of $120k/Bitcoin. Q2 2025 - Raise $168 Billion to buy 988,235 Bitcoin at average price of $170k/Bitcoin Q3 2025 - Raise $336 Billion to buy 1,050,000 Bitcoin at average price of $320k/Bitcoin Q4 2025 - Raise $672 Billion to buy 1,680,000 Bitcoin at average price of $400k/Bitcoin In one year there is the possibility that he could REALISTICALLY buy 4,418,235 Bitcoin!! I say "realistically" because the demand for Saylor's $42 Billion equity raise was so great that he is going to be able to use it all up in 3-4 months instead of the projected 3 years!!🤯 This would bring their current Bitcoin holdings of 444,262 Bitcoin to 4,857,237!!!! Or 23% of all Bitcoin!! Calculations are based on our post below: We are closer to $1 million Bitcoin than you think. I believe we will get to this price sooner than Wicked 's projected date of 4/4/2030. I agree with Samson that we get to $1 million per coin by the end of 2025! Hold on to your hat, because we are about to experience exponential, LIFTOFF. To understand exponential growth, envision yourself holding two very powerful magnets. As you start to bring the two magnets together, it gets harder to hold them apart and all of a sudden, BAM, they clap together! This is what we are about to experience, a SUDDEN BAM, in the price of Bitcoin as adoption goes from <1% to 10% in a very short time frame. Now you may better understand why Saylor is frantically, but intelligently, trying to buy $42 Billion of Bitcoin. As an engineer he understands what exponential demand will cause to the price of a finite commodity. Saylor has been on record as saying that "he will be buying the top forever." Don't ever underestimate an astro/aeronautical MIT engineer.

Michael Saylor's end game is to buy $3 trillion worth of #Bitcoin! 👀 Microstrategy could, CONSERVATIVELY, own approximately 16% of the total Bitcoin Supply or 3,439,002 Bitcoin!! For those that think this is a MOONBOI projection, listen to the video clip below, VERY CLOSELY, and you will hear him say that he plans on buying $3 trillion worth of Bitcoin 🤯 Even if Saylor buys $3 trillion worth of Bitcoin, at an average price of $1 million per coin, he would be able to buy 3,000,000 Bitcoin! Check my math! This would CONSERVATIVELY bring his total Bitcoin holdings to 3,444,262, or 16% of the total Bitcoin Supply!! Saylor could single handedly jack the price of Bitcoin to $1 million per coin and Samson Mow's Omega candle could be coming in 2025. What going to happen when Nation States, Google, Amazon, Facebook and billions of people complement Saylor's $3 trillion purchase? What is bigger than an omega candle? I asked GROK and it doesn't even know! 😂 I think we should name it the ♾️ candle. This would be representative of Wicked's Stock to Fomo model (see graphic below) and his post: Saylor has said he is going to double his $42 Billion Bitcoin investment at least 4 times and here is how this could lead to him acquiring more than 4 million Bitcoin in 2025: Q1 2025 - Raise $84 Billion to buy 700,000 Bitcoin at average price of $120k/Bitcoin. Q2 2025 - Raise $168 Billion to buy 988,235 Bitcoin at average price of $170k/Bitcoin Q3 2025 - Raise $336 Billion to buy 1,050,000 Bitcoin at average price of $320k/Bitcoin Q4 2025 - Raise $672 Billion to buy 1,680,000 Bitcoin at average price of $400k/Bitcoin In one year there is the possibility that he could REALISTICALLY buy 4,418,235 Bitcoin!! I say "realistically" because the demand for Saylor's $42 Billion equity raise was so great that he is going to be able to use it all up in 3-4 months instead of the projected 3 years!!🤯 This would bring their current Bitcoin holdings of 444,262 Bitcoin to 4,857,237!!!! Or 23% of all Bitcoin!! Calculations are based on our post below: We are closer to $1 million Bitcoin than you think. I believe we will get to this price sooner than Wicked 's projected date of 4/4/2030. I agree with Samson that we get to $1 million per coin by the end of 2025! Hold on to your hat, because we are about to experience exponential, LIFTOFF. To understand exponential growth, envision yourself holding two very powerful magnets. As you start to bring the two magnets together, it gets harder to hold them apart and all of a sudden, BAM, they clap together! This is what we are about to experience, a SUDDEN BAM, in the price of Bitcoin as adoption goes from <1% to 10% in a very short time frame. Now you may better understand why Saylor is frantically, but intelligently, trying to buy $42 Billion of Bitcoin. As an engineer he understands what exponential demand will cause to the price of a finite commodity. Saylor has been on record as saying that "he will be buying the top forever." Don't ever underestimate an astro/aeronautical MIT engineer.

Satoshi’s Journal

280,298 次观看 • 1 年前