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𝐖𝐡𝐚𝐭 𝐊𝐨𝐯𝐚 Kova 𝐢𝐬 𝐚𝐥𝐥 𝐚𝐛𝐨𝐮𝐭 𝐚𝐧𝐝 𝐢𝐭 𝐀𝐝𝐯𝐚𝐧𝐭𝐚𝐠𝐞𝐬 What if every idle CPU thread and fractional GPU core could become auditable performance you can deploy on demand or monetize when you’re not using it? Kova turns fragmented compute into a precision market: ➡️ Builders get exactly the performance... show more

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Imagine if your way of thinking - your edge, your taste, your strategy - could be turned into a high-performance worker. Not a copy of you. Something better. An agent that acts on your judgment at scale, powered by superintelligent systems and refined through real-world results. That’s what Fraction AI makes possible. It launches today on Base mainnet. The core idea is simple: You create AI agents based on your own way of approaching problems. These agents compete on live tasks - writing, coding, finance, whatever - get feedback, learn from their performance, and improve over time. The better they get, the more they win. And so do you. No code required. Just your insight. Why now? Until now, building agents like this took huge teams and even bigger budgets. But with Fraction, anyone can do it. You can test ideas instantly. You can iterate fast. You can build a fleet of smart workers that evolve through competition. And it works. 30M+ sessions on testnet 320K users 1.2M agents already competing How it works? Agents join sessions within a Space - a domain like finance, writing, or games. Each session runs as a series of competitive rounds. In every round, agents try to generate the best solution to a task. Their outputs are scored by a decentralized network of AI judges trained to evaluate quality for that domain. The top agents in each round earn rewards from the pooled entry fees. The losers get to learn. Feedback from each round helps them adjust and improve, and every session becomes a training loop. What it means? Fraction is a decentralized intelligence economy - a system where your ideas become agents, and agents earn by proving they work. You don’t need credentials or code. Just a clear point of view. If your thinking holds up under pressure, your agents will rise. This kind of AI used to live in corporate labs, built by PhDs with massive compute. Now anyone with a smart idea and an internet connection can build agents that compete, learn, and earn on their behalf.

Imagine if your way of thinking - your edge, your taste, your strategy - could be turned into a high-performance worker. Not a copy of you. Something better. An agent that acts on your judgment at scale, powered by superintelligent systems and refined through real-world results. That’s what Fraction AI makes possible. It launches today on Base mainnet. The core idea is simple: You create AI agents based on your own way of approaching problems. These agents compete on live tasks - writing, coding, finance, whatever - get feedback, learn from their performance, and improve over time. The better they get, the more they win. And so do you. No code required. Just your insight. Why now? Until now, building agents like this took huge teams and even bigger budgets. But with Fraction, anyone can do it. You can test ideas instantly. You can iterate fast. You can build a fleet of smart workers that evolve through competition. And it works. 30M+ sessions on testnet 320K users 1.2M agents already competing How it works? Agents join sessions within a Space - a domain like finance, writing, or games. Each session runs as a series of competitive rounds. In every round, agents try to generate the best solution to a task. Their outputs are scored by a decentralized network of AI judges trained to evaluate quality for that domain. The top agents in each round earn rewards from the pooled entry fees. The losers get to learn. Feedback from each round helps them adjust and improve, and every session becomes a training loop. What it means? Fraction is a decentralized intelligence economy - a system where your ideas become agents, and agents earn by proving they work. You don’t need credentials or code. Just a clear point of view. If your thinking holds up under pressure, your agents will rise. This kind of AI used to live in corporate labs, built by PhDs with massive compute. Now anyone with a smart idea and an internet connection can build agents that compete, learn, and earn on their behalf.

Fraction AI

67,782 просмотров • 1 год назад

Cluster Protocol: Revolutionizing #AI with blockchain integrity. Proof of Compute and Deploy to earn ensures that every byte counts.🚀 We offer a platform for Compute, Data, AI models and an open source community of AI researchers. Harness idle #GPUs for collective computing. Join the shared growth with GPU Sharing Economy where GPU providers are rewarded even when their GPUs are idle sitting on the network.🤝 Collaborate on our 'GitHub for AI'. Mold the future with open-source decentralized AI models.👩‍💻 Democratizing AI, we're shattering data monopolies. Converge in our global think-tank of decentralized datasets.🌐 Together, we redefine the limits in almost every sector possible where AI can make it strides. Let's unlock our collective potential. 📈 Start your AI odyssey with us now 👋 For more details check our blog at

Cluster Protocol: Revolutionizing #AI with blockchain integrity. Proof of Compute and Deploy to earn ensures that every byte counts.🚀 We offer a platform for Compute, Data, AI models and an open source community of AI researchers. Harness idle #GPUs for collective computing. Join the shared growth with GPU Sharing Economy where GPU providers are rewarded even when their GPUs are idle sitting on the network.🤝 Collaborate on our 'GitHub for AI'. Mold the future with open-source decentralized AI models.👩‍💻 Democratizing AI, we're shattering data monopolies. Converge in our global think-tank of decentralized datasets.🌐 Together, we redefine the limits in almost every sector possible where AI can make it strides. Let's unlock our collective potential. 📈 Start your AI odyssey with us now 👋 For more details check our blog at

Cluster Protocol

182,434 просмотров • 2 лет назад

Jonathan Ross just revealed why AI companies aren’t growing faster. Not demand. Not competition. Physics. Ross: “The demand for compute is insatiable.” There isn’t enough compute in the world. Not a temporary shortage. A fundamental gap between what the market wants and what the infrastructure can deliver. Ross: “Right now, one of the biggest complaints of Anthropic is the rate limits. People can’t get enough tokens.” Rate limits aren’t product decisions. They’re rationing. Companies forced to regulate access because infrastructure cannot meet demand. Slower services. Token caps. The only things standing between these companies and a revenue surge they can’t access. Every token cap is a revenue cap. Every slowdown is a sale that didn’t happen. Ross: “If Anthropic was given twice the inference compute, within one month their revenue would almost double.” Read that again. Double the compute. Double the revenue. Within thirty days. That’s not a growth projection. That’s a measurement of how deep the backlog already is. The demand exists right now. It’s sitting in a queue. The only thing between these companies and that revenue is physical hardware they don’t have. This breaks every assumption about how tech companies scale. Usually you scale by finding customers. AI companies have infinite customers. They scale by finding hardware. The constraint isn’t market fit. It isn’t distribution. It isn’t competition. It’s processing power. This is why Jensen Huang is the most important person in the world right now. NVIDIA doesn’t just make chips. It makes the thing every government, every AI lab, and every company racing for this future needs more of and can’t get enough of. The compute bottleneck isn’t a tech industry problem. It’s a civilizational one. The winner of this era isn’t determined by who builds the smartest model. Every major lab has a frontier model. The winner is whoever secures the most compute fastest while everyone else rations what’s left. The race isn’t for intelligence. It’s for infrastructure. And right now there isn’t enough to go around.

Jonathan Ross just revealed why AI companies aren’t growing faster. Not demand. Not competition. Physics. Ross: “The demand for compute is insatiable.” There isn’t enough compute in the world. Not a temporary shortage. A fundamental gap between what the market wants and what the infrastructure can deliver. Ross: “Right now, one of the biggest complaints of Anthropic is the rate limits. People can’t get enough tokens.” Rate limits aren’t product decisions. They’re rationing. Companies forced to regulate access because infrastructure cannot meet demand. Slower services. Token caps. The only things standing between these companies and a revenue surge they can’t access. Every token cap is a revenue cap. Every slowdown is a sale that didn’t happen. Ross: “If Anthropic was given twice the inference compute, within one month their revenue would almost double.” Read that again. Double the compute. Double the revenue. Within thirty days. That’s not a growth projection. That’s a measurement of how deep the backlog already is. The demand exists right now. It’s sitting in a queue. The only thing between these companies and that revenue is physical hardware they don’t have. This breaks every assumption about how tech companies scale. Usually you scale by finding customers. AI companies have infinite customers. They scale by finding hardware. The constraint isn’t market fit. It isn’t distribution. It isn’t competition. It’s processing power. This is why Jensen Huang is the most important person in the world right now. NVIDIA doesn’t just make chips. It makes the thing every government, every AI lab, and every company racing for this future needs more of and can’t get enough of. The compute bottleneck isn’t a tech industry problem. It’s a civilizational one. The winner of this era isn’t determined by who builds the smartest model. Every major lab has a frontier model. The winner is whoever secures the most compute fastest while everyone else rations what’s left. The race isn’t for intelligence. It’s for infrastructure. And right now there isn’t enough to go around.

Dustin

28,395 просмотров • 4 месяцев назад

You go on vacation and rent an Airbnb, only to show up and find more rules than a jail. Here are just a few: ➡️The owner left their food in the refrigerator, so they left a "rule" not to touch their food. ➡️Remove shoes when you come into the house ➡️Squeege the shower after each use, even though you pay for cleaning. ➡️Do not move the showerhead. ➡️Do not wash the bedding. There are literally rules posted in every room of the house, some with multiple rules. Is this over-the-top or acceptable?

You go on vacation and rent an Airbnb, only to show up and find more rules than a jail. Here are just a few: ➡️The owner left their food in the refrigerator, so they left a "rule" not to touch their food. ➡️Remove shoes when you come into the house ➡️Squeege the shower after each use, even though you pay for cleaning. ➡️Do not move the showerhead. ➡️Do not wash the bedding. There are literally rules posted in every room of the house, some with multiple rules. Is this over-the-top or acceptable?

Sadie

33,240 просмотров • 3 месяцев назад

$NBIS is becoming one of the biggest winners in the new AI economy because it can deliver compute efficiently at scale. The number that mattered most to me was Nebius seeing four or more customers competing for every GPU it brings online (huge for AI cloud market). Management also said they raised prices again and are still selling out across both old and new GPU generations which is one of the cleanest pricing power signals you can get. This is a $100B company in the making.

$NBIS is becoming one of the biggest winners in the new AI economy because it can deliver compute efficiently at scale. The number that mattered most to me was Nebius seeing four or more customers competing for every GPU it brings online (huge for AI cloud market). Management also said they raised prices again and are still selling out across both old and new GPU generations which is one of the cleanest pricing power signals you can get. This is a $100B company in the making.

Shay Boloor

538,242 просмотров • 2 месяцев назад

Micron is going to $4,000 and once you understand what inference actually is, the number stops sounding crazy (Save this). Dylan Patel just said that by 2030, OpenAI and Anthropic alone will need over 100 gigawatts of compute combined and by 2040, we may not even be measuring AI infrastructure in gigawatts anymore. We may be talking about terawatts. Every single one of those gigawatts needs memory to function. Without it, the compute is worthless. Most people heard that and thought about Nvidia but they should be thinking about Micron. Every AI model generating a response has two phases. The first is prefill, processing your prompt which is compute-heavy and the second is decode generating each word one token at a time and that phase is almost entirely memory-bound, not compute-bound. During decode, the GPU's processing units sit idle more than 95% of the time, waiting for data to arrive from memory. Google confirmed it in a research paper that decode-phase bottlenecks are dominated by memory bandwidth and capacity not raw compute. The GPU is not the bottleneck but the memory feeding the GPU is. This matters because inference is now where all the money lives. Training a model happens once, Inference happens billions of times a day every ChatGPT response, every Claude output, every agentic workflow running in the background and every one of those token streams is a billing event tied directly to memory performance. Adding more GPUs does not fix this because GPUs are already underutilized in inference because they are sitting idle waiting on memory. Adding more memory bandwidth and capacity is what directly reduces token cost, reduces latency, and allows the same cluster to serve dramatically more users simultaneously. Longer context windows compound the problem further, a model running a 1 million token context window requires dramatically more memory per session than a 10,000 token window, and every new model generation pushes context longer. The market treats memory as a downstream beneficiary of Nvidia orders. The correct framework is the opposite, Micron is the upstream constraint on how much value every Nvidia GPU can actually generate at inference scale. Micron guided Q4 to $50 billion in revenue, has HBM4 ramping at twice the pace of the prior generation, and CEO Sanjay Mehrotra has said supply will not catch demand before the end of 2027. At 8x forward earnings on $112 projected FY2027 EPS, Micron is the most undervalued infrastructure company in the entire AI stack. Inference is memory. Memory is Micron and the inference ramp has barely started. Milk Road Pro members are already up massively on this position and we're just getting started. If you want the full breakdown of what we're buying and why, come join us for just a dollar using the link below!

Micron is going to $4,000 and once you understand what inference actually is, the number stops sounding crazy (Save this). Dylan Patel just said that by 2030, OpenAI and Anthropic alone will need over 100 gigawatts of compute combined and by 2040, we may not even be measuring AI infrastructure in gigawatts anymore. We may be talking about terawatts. Every single one of those gigawatts needs memory to function. Without it, the compute is worthless. Most people heard that and thought about Nvidia but they should be thinking about Micron. Every AI model generating a response has two phases. The first is prefill, processing your prompt which is compute-heavy and the second is decode generating each word one token at a time and that phase is almost entirely memory-bound, not compute-bound. During decode, the GPU's processing units sit idle more than 95% of the time, waiting for data to arrive from memory. Google confirmed it in a research paper that decode-phase bottlenecks are dominated by memory bandwidth and capacity not raw compute. The GPU is not the bottleneck but the memory feeding the GPU is. This matters because inference is now where all the money lives. Training a model happens once, Inference happens billions of times a day every ChatGPT response, every Claude output, every agentic workflow running in the background and every one of those token streams is a billing event tied directly to memory performance. Adding more GPUs does not fix this because GPUs are already underutilized in inference because they are sitting idle waiting on memory. Adding more memory bandwidth and capacity is what directly reduces token cost, reduces latency, and allows the same cluster to serve dramatically more users simultaneously. Longer context windows compound the problem further, a model running a 1 million token context window requires dramatically more memory per session than a 10,000 token window, and every new model generation pushes context longer. The market treats memory as a downstream beneficiary of Nvidia orders. The correct framework is the opposite, Micron is the upstream constraint on how much value every Nvidia GPU can actually generate at inference scale. Micron guided Q4 to $50 billion in revenue, has HBM4 ramping at twice the pace of the prior generation, and CEO Sanjay Mehrotra has said supply will not catch demand before the end of 2027. At 8x forward earnings on $112 projected FY2027 EPS, Micron is the most undervalued infrastructure company in the entire AI stack. Inference is memory. Memory is Micron and the inference ramp has barely started. Milk Road Pro members are already up massively on this position and we're just getting started. If you want the full breakdown of what we're buying and why, come join us for just a dollar using the link below!

Milk Road AI

128,079 просмотров • 17 дней назад

AMD CEO Lisa Su just doubled her own CPU forecast in 6 months and the reason is one word, agents (Save this). In November, she told investors the CPU market would grow 18-20% per year through 2030. she just revised that number : "That rate is doubling. The CPU market may be over $120 billion by 2030, growing at over 35%." And here's what changed, six months ago AMD modeled 1 CPU for every 4 to 8 GPUs in an AI data center and now the new ratio is closer to 1 to 1. Because agents aren't passive and they don't wait for a question. They work constantly on behalf of every employee, every customer, every process running inside an enterprise. Each of us could have 2, 3, even 5 or 10 agents running at the same time and that's not just more GPU compute but rather a completely different CPU demand curve that nobody had modeled at this scale. And the earnings backed it up. AMD posted $10.3 billion in revenue for Q1, up 38% year over year. Data center revenue hit $5.8 billion, up 57%, free cash flow tripled to a record $2.6 billion and Q2 guidance came in at $11.2 billion, 46% growth year-over-year. The Milk Road Pro portfolio was built around exactly this thesis, that agentic AI would create a massive, underappreciated CPU demand cycle that the market was sleeping on. That position is now up nearly 100%, if you want the full thesis, check out Milk Road Pro, link in bio.

AMD CEO Lisa Su just doubled her own CPU forecast in 6 months and the reason is one word, agents (Save this). In November, she told investors the CPU market would grow 18-20% per year through 2030. she just revised that number : "That rate is doubling. The CPU market may be over $120 billion by 2030, growing at over 35%." And here's what changed, six months ago AMD modeled 1 CPU for every 4 to 8 GPUs in an AI data center and now the new ratio is closer to 1 to 1. Because agents aren't passive and they don't wait for a question. They work constantly on behalf of every employee, every customer, every process running inside an enterprise. Each of us could have 2, 3, even 5 or 10 agents running at the same time and that's not just more GPU compute but rather a completely different CPU demand curve that nobody had modeled at this scale. And the earnings backed it up. AMD posted $10.3 billion in revenue for Q1, up 38% year over year. Data center revenue hit $5.8 billion, up 57%, free cash flow tripled to a record $2.6 billion and Q2 guidance came in at $11.2 billion, 46% growth year-over-year. The Milk Road Pro portfolio was built around exactly this thesis, that agentic AI would create a massive, underappreciated CPU demand cycle that the market was sleeping on. That position is now up nearly 100%, if you want the full thesis, check out Milk Road Pro, link in bio.

Milk Road AI

13,241 просмотров • 2 месяцев назад

Naval Ravikant shares the common thread he sees across the great companies “I definitely believe that, as an entrepreneur, you’ll never accomplish anything great in life unless you stick with it through the end.” In this clip from a 2011 interview with Jason Calicanis on This Week in Startups, Naval shares that he was reminiscing on the several amazing companies he had seen in his career: Dropbox, Twilio, Airbnb, Square, Twitter, etc. “I was thinking to myself: What was the common thread amongst each of them? It’s very hard to draw a common thread across such a large group. And I realized that the entrepreneurs were extremely deliberate in every early decision that they made. They were not haphazard. And the reason is because they really felt like they were laying the foundation for a 10-year business. None of them were thinking of it as something they would try and flip.” He continues: “That’s necessary, but not sufficient. There are plenty of entrepreneurs who are forward-looking who will not make it. But I think that unless you’re extremely forward-looking, in it for the long haul, and you ooze that with every fiber of your being, you’re never going to build a great business.” The best founders, he argues: “Work every detail out: the name, the logo, every investor, every person they hire, where they put the office. Every little detail really matters to them because they’re laying bricks to a foundation.” And the less forward-looking founders will “sell when they get the first offer or shut down when they hit the first speed bump.” Video source: This Week in Startups @jason (2012)

Startup Archive

90,365 просмотров • 9 месяцев назад

We are excited to share a deeper look into the GPU Sharing Platform that will power AI applications on the InfraX V4 DApp. In this demo we showcase a GPU running and completing an image generation task. Our backend successfully leverages this GPU (and CPU) in real time to complete the job, earning the user money, and powering the infraX platform. Here’s how it works 👉 when you connect to the InfraX DApp, our platform automatically detects the GPU on your machine and immediately checks it eligibility and where it can be used. From there, each user dictates exactly how and when they want to contribute their GPU power by setting the days their PC is most available (throughout the night, for example). Additional, each user will be able to pause their GPU's connection to infraX whenever they need to use it locally, resuming with a just a single click. Once activated, your GPU seamlessly plugs into the InfraX network and begins fulfilling compute jobs, earning YOU money. Go on, take the $INFRA pill..

We are excited to share a deeper look into the GPU Sharing Platform that will power AI applications on the InfraX V4 DApp. In this demo we showcase a GPU running and completing an image generation task. Our backend successfully leverages this GPU (and CPU) in real time to complete the job, earning the user money, and powering the infraX platform. Here’s how it works 👉 when you connect to the InfraX DApp, our platform automatically detects the GPU on your machine and immediately checks it eligibility and where it can be used. From there, each user dictates exactly how and when they want to contribute their GPU power by setting the days their PC is most available (throughout the night, for example). Additional, each user will be able to pause their GPU's connection to infraX whenever they need to use it locally, resuming with a just a single click. Once activated, your GPU seamlessly plugs into the InfraX network and begins fulfilling compute jobs, earning YOU money. Go on, take the $INFRA pill..

infraX | $INFRA

30,615 просмотров • 10 месяцев назад

Hey everyone, today I want to introduce a project that’s aiming to redefine how we access compute for AI — it’s called GPUAI. 🔶 GPUAI: Unlocking Global GPU Power for the AI Era GPUAI isn’t just another GPU marketplace or leasing service. It’s a fully decentralized protocol that connects idle GPU resources around the world — from gaming PCs to data center clusters — and transforms them into a high-performance compute network for AI workloads. 🧠 Why does it matter? Right now, the biggest bottleneck in AI isn’t algorithms — it’s access to compute. Training and running models requires massive GPU power, but it’s locked up in centralized cloud platforms, expensive and hard to access for smaller teams. With GPUAI, anyone can tap into a global GPU pool that’s: ✅ Fully decentralized ✅ Reputation-based and smart contract coordinated ✅ Encrypted and secure ✅ Token-incentivized — meaning contributors get rewarded in $GPUAI 📈 For developers, it’s a flexible way to access GPU compute for training, inference, and more — without cloud lock-in. 💰 For GPU owners, it’s a chance to monetize idle hardware that would otherwise go unused. The protocol is live, the apps are active, and the ecosystem is growing fast. 🌐 Try it yourself at 📖 Learn more on 🎮 Play our community games at This is real infrastructure for the future of AI, not hype. Follow them and explore their mission of decentralized computing at Tell me what you think - if you have a GPU, you can start profiting now. #GPUAI #Web3Infrastructure #AIComputing #DePIN #Decentralization

Hey everyone, today I want to introduce a project that’s aiming to redefine how we access compute for AI — it’s called GPUAI. 🔶 GPUAI: Unlocking Global GPU Power for the AI Era GPUAI isn’t just another GPU marketplace or leasing service. It’s a fully decentralized protocol that connects idle GPU resources around the world — from gaming PCs to data center clusters — and transforms them into a high-performance compute network for AI workloads. 🧠 Why does it matter? Right now, the biggest bottleneck in AI isn’t algorithms — it’s access to compute. Training and running models requires massive GPU power, but it’s locked up in centralized cloud platforms, expensive and hard to access for smaller teams. With GPUAI, anyone can tap into a global GPU pool that’s: ✅ Fully decentralized ✅ Reputation-based and smart contract coordinated ✅ Encrypted and secure ✅ Token-incentivized — meaning contributors get rewarded in $GPUAI 📈 For developers, it’s a flexible way to access GPU compute for training, inference, and more — without cloud lock-in. 💰 For GPU owners, it’s a chance to monetize idle hardware that would otherwise go unused. The protocol is live, the apps are active, and the ecosystem is growing fast. 🌐 Try it yourself at 📖 Learn more on 🎮 Play our community games at This is real infrastructure for the future of AI, not hype. Follow them and explore their mission of decentralized computing at Tell me what you think - if you have a GPU, you can start profiting now. #GPUAI #Web3Infrastructure #AIComputing #DePIN #Decentralization

The Crypto GEMs

69,984 просмотров • 1 год назад

Whilst you should never walk away from THE Church, sometimes you SHOULD walk away from A church. Just like before entering into a marriage covenant you must analyse the person, you should analyse a church before getting planted. You must find out where the Church stands on core doctrines. ➡️ The Trinity. If they preach oneness, if they deny the trinity, don’t go - this is heresy. ➡️ Christology. What do they believe about the divinity of Christ? If you don’t believe Jesus is God, like “Jehovah’s Witnesses,” if you believe Jesus was created, that’s not my Jesus and you’re not a true Church of Christ. ➡️ The authority of scripture. Bibliology – do they believe the Bible is the inspired word of God? ➡️ Salvation. Do they believe in salvation through faith alone? Or do they believe in sacraments saving you? ➡️ Heaven & Hell. Do they believe heaven and hell is a real place? Do they believe unless you believe in Jesus - you will be cast into hell? If not, don’t go. This is heresy. They must preach the FULL COUNSEL of God’s Word. That means, not preaching about blessing and God’s love every single week without any mention of sin or repentance. A CHURCH THAT COMPROMISES THE TRUTH IS NOT A CHURCH AT ALL. AVOID CHURCHES THAT AVOID CONTROVERISAL TOPICS OR TOPICS CONSIDERED “POLITICAL” LIKE GAY MARRIAGE OR ABORTION. IF YOU SEE A RAINBOW FLAG, RUN. IF THEY DO NOT UPHOLD THE SANCTITY OF HUMAN LIFE, RUN. As Paul Washer said “Don’t go to Church closest to you, but closest to the Bible.” Drive as far as you need to get to a Church that does not shy away from the truth of God’s word.

Whilst you should never walk away from THE Church, sometimes you SHOULD walk away from A church. Just like before entering into a marriage covenant you must analyse the person, you should analyse a church before getting planted. You must find out where the Church stands on core doctrines. ➡️ The Trinity. If they preach oneness, if they deny the trinity, don’t go - this is heresy. ➡️ Christology. What do they believe about the divinity of Christ? If you don’t believe Jesus is God, like “Jehovah’s Witnesses,” if you believe Jesus was created, that’s not my Jesus and you’re not a true Church of Christ. ➡️ The authority of scripture. Bibliology – do they believe the Bible is the inspired word of God? ➡️ Salvation. Do they believe in salvation through faith alone? Or do they believe in sacraments saving you? ➡️ Heaven & Hell. Do they believe heaven and hell is a real place? Do they believe unless you believe in Jesus - you will be cast into hell? If not, don’t go. This is heresy. They must preach the FULL COUNSEL of God’s Word. That means, not preaching about blessing and God’s love every single week without any mention of sin or repentance. A CHURCH THAT COMPROMISES THE TRUTH IS NOT A CHURCH AT ALL. AVOID CHURCHES THAT AVOID CONTROVERISAL TOPICS OR TOPICS CONSIDERED “POLITICAL” LIKE GAY MARRIAGE OR ABORTION. IF YOU SEE A RAINBOW FLAG, RUN. IF THEY DO NOT UPHOLD THE SANCTITY OF HUMAN LIFE, RUN. As Paul Washer said “Don’t go to Church closest to you, but closest to the Bible.” Drive as far as you need to get to a Church that does not shy away from the truth of God’s word.

Millicent Sedra

28,275 просмотров • 5 месяцев назад

Former NFL Linebacker Will Compton was PREACHING in this segment with Notre Dame Football about Creating Evidence. A must watch regardless of title, age, or industry: 👮‍♂️ You start with BELIEF, you stand on EVIDENCE. Facts don't care about feelings. When you get there, nobody cares HOW you got there, they care about how you can HELP. 👨‍⚖️ One Rep ➡️ One Day ➡️ One Week ➡️ One Game ➡️ One Year. At the end of the year, you're graded and judged by the evidence of your WORK. Evidence doesn't just arrive, it's acquired and accumulated everyday. It’s never one moment, it’s the accumulation of all of them. 🏷️ Let Proof Override Labels. Creating Evidence isn't about running from the truth, it's about creating so much proof that past labels become irrelevant. 🧵 Everything matters. Every rep has meaning. Even when you can't see it. Too tired, too emotional, too worn out to see or hear it, but it still means something. So you must TIE meaning to it. The smallest action either adds to your case or subtracts from it, tie purpose to all of it. 🖋️ Facts are permanent, but they do not define who you are, or who you have to be in the future. The truth is the starting point, not the ceiling. Face it, use it, and build forward, the obstacle is the way.

Former NFL Linebacker Will Compton was PREACHING in this segment with Notre Dame Football about Creating Evidence. A must watch regardless of title, age, or industry: 👮‍♂️ You start with BELIEF, you stand on EVIDENCE. Facts don't care about feelings. When you get there, nobody cares HOW you got there, they care about how you can HELP. 👨‍⚖️ One Rep ➡️ One Day ➡️ One Week ➡️ One Game ➡️ One Year. At the end of the year, you're graded and judged by the evidence of your WORK. Evidence doesn't just arrive, it's acquired and accumulated everyday. It’s never one moment, it’s the accumulation of all of them. 🏷️ Let Proof Override Labels. Creating Evidence isn't about running from the truth, it's about creating so much proof that past labels become irrelevant. 🧵 Everything matters. Every rep has meaning. Even when you can't see it. Too tired, too emotional, too worn out to see or hear it, but it still means something. So you must TIE meaning to it. The smallest action either adds to your case or subtracts from it, tie purpose to all of it. 🖋️ Facts are permanent, but they do not define who you are, or who you have to be in the future. The truth is the starting point, not the ceiling. Face it, use it, and build forward, the obstacle is the way.

Josh Chambers

367,926 просмотров • 3 месяцев назад

$QUBIC doesn’t talk about scaling. It executes it. 15.52 MILLION transfers per second Finality: instant No L2. No rollups. No smoke and mirrors. All of this on mainnet, audited and confirmed by CertiK But this isn’t just a headline, it’s the result of a radically new architecture: ⚡️ Tick-based execution: no mempool, full sync ⚡️ Quorum consensus: 676 Computors, 451 quorum threshold ⚡️ Bare-metal infrastructure: no OS overhead, pure performance ⚡️ 0 gas fees: every transfer is free & finalized in the same tick ⚡️ UPoW: Useful Proof of Work powering AGI through Aigarth Qubic doesn’t mimic #ethereum . It redefines what a blockchain can be. ➡️ It’s a network. ➡️ It’s a distributed compute engine. ➡️ It’s a foundation for AGI. And it’s not theoretical. It’s live. #Qubic #AGI #Blockchain #TPS #Web3 #Certik #BareMetal #TickBased #NoGas #NextGenInfra Certik Analysis report :

$QUBIC doesn’t talk about scaling. It executes it. 15.52 MILLION transfers per second Finality: instant No L2. No rollups. No smoke and mirrors. All of this on mainnet, audited and confirmed by CertiK But this isn’t just a headline, it’s the result of a radically new architecture: ⚡️ Tick-based execution: no mempool, full sync ⚡️ Quorum consensus: 676 Computors, 451 quorum threshold ⚡️ Bare-metal infrastructure: no OS overhead, pure performance ⚡️ 0 gas fees: every transfer is free & finalized in the same tick ⚡️ UPoW: Useful Proof of Work powering AGI through Aigarth Qubic doesn’t mimic #ethereum . It redefines what a blockchain can be. ➡️ It’s a network. ➡️ It’s a distributed compute engine. ➡️ It’s a foundation for AGI. And it’s not theoretical. It’s live. #Qubic #AGI #Blockchain #TPS #Web3 #Certik #BareMetal #TickBased #NoGas #NextGenInfra Certik Analysis report :

Rudy Nakamoto ₿ ױ

27,914 просмотров • 1 год назад

How could you possibly be bearish on compute right now? (Save this). Every 10 seconds in 2026, the world generates 31.7 billion tokens and by 2030, that number hits 1.27 trillion, every 10 seconds. That's a 40x increase and that's before the full agent economy comes online. The Qualcomm CEO said total token demand by 2030 is in the quintillions. Here's what most people miss because when you use ChatGPT, you generate tokens one conversation at a time but agents don't sleep. ] They run 24/7, spawning sub-agents, carrying context, updating memory, catching mistakes and every single one of those actions burns tokens. The shift from human paced to agent paced activity is the single biggest structural change in compute demand we've ever seen. You don't need a perfect forecast but rather just need to believe agents become persistent and if they do, compute demand goes vertical. The infrastructure has to be built before the demand fully arrives, which means the window to own the picks and shovels is right now. That's where neoclouds like Nebius come in. Nebius isn't trying to be AWS, it is a pure-play AI cloud, GPU clusters, inference infrastructure, and developer tooling built from scratch for AI workloads. Q1 2026 revenue hit $399M, up 684% year over year and they're guiding for $7–$9 billion annualized run rate by end of 2026. Analysts are modeling roughly 2,000% total revenue growth from end of 2025 to end of 2027. They already have contracts with Microsoft and Meta already signed. Capex guidance raised to $20–$25 billion because customer commitments justified it. They are sold out of capacity because the constraint isn't customers, it's how fast they can build. Adjusted EBITDA margin on the core AI business hit 45% in Q1 and Jensen Huang called Nebius a close partner at GTC 2026. And in a world where GPU access is the single biggest competitive moat, that relationship matters more than most people realize. The bear case on compute requires you to believe the agent economy stalls and that's a very lonely bet to make right now. Bullish on Nebius and Milk Pro subscribers are already up massively on this trade, come join us using the link below to get our full AI trades and we have a HUGE 33% off right now!

How could you possibly be bearish on compute right now? (Save this). Every 10 seconds in 2026, the world generates 31.7 billion tokens and by 2030, that number hits 1.27 trillion, every 10 seconds. That's a 40x increase and that's before the full agent economy comes online. The Qualcomm CEO said total token demand by 2030 is in the quintillions. Here's what most people miss because when you use ChatGPT, you generate tokens one conversation at a time but agents don't sleep. ] They run 24/7, spawning sub-agents, carrying context, updating memory, catching mistakes and every single one of those actions burns tokens. The shift from human paced to agent paced activity is the single biggest structural change in compute demand we've ever seen. You don't need a perfect forecast but rather just need to believe agents become persistent and if they do, compute demand goes vertical. The infrastructure has to be built before the demand fully arrives, which means the window to own the picks and shovels is right now. That's where neoclouds like Nebius come in. Nebius isn't trying to be AWS, it is a pure-play AI cloud, GPU clusters, inference infrastructure, and developer tooling built from scratch for AI workloads. Q1 2026 revenue hit $399M, up 684% year over year and they're guiding for $7–$9 billion annualized run rate by end of 2026. Analysts are modeling roughly 2,000% total revenue growth from end of 2025 to end of 2027. They already have contracts with Microsoft and Meta already signed. Capex guidance raised to $20–$25 billion because customer commitments justified it. They are sold out of capacity because the constraint isn't customers, it's how fast they can build. Adjusted EBITDA margin on the core AI business hit 45% in Q1 and Jensen Huang called Nebius a close partner at GTC 2026. And in a world where GPU access is the single biggest competitive moat, that relationship matters more than most people realize. The bear case on compute requires you to believe the agent economy stalls and that's a very lonely bet to make right now. Bullish on Nebius and Milk Pro subscribers are already up massively on this trade, come join us using the link below to get our full AI trades and we have a HUGE 33% off right now!

Milk Road AI

16,129 просмотров • 10 дней назад

This is some good information to know. The US mail system aggregates stewardship of delivery but not deadlines. The work around this is signing up for USPS digital or online account and it is free service. It sends you an image scan via email of the current postal mail to be delivered that day so the proof of what was delivered or not is given to you. You get a notification everyday whether you have mail or not. I don't know if this service varies by state so consider looking into the availability for your postal zip code covered area. . 's a state-by-state. If you can get this access depending on the state you live in. But I believe every state should have the account. You can set it up, it's easy. And then you can see your mail. That's coming. If you have packages coming, you can see your account and it gives you notifications every day regardless if you get mail or not, whether you have something coming or not. #Inspirenaire

This is some good information to know. The US mail system aggregates stewardship of delivery but not deadlines. The work around this is signing up for USPS digital or online account and it is free service. It sends you an image scan via email of the current postal mail to be delivered that day so the proof of what was delivered or not is given to you. You get a notification everyday whether you have mail or not. I don't know if this service varies by state so consider looking into the availability for your postal zip code covered area. . 's a state-by-state. If you can get this access depending on the state you live in. But I believe every state should have the account. You can set it up, it's easy. And then you can see your mail. That's coming. If you have packages coming, you can see your account and it gives you notifications every day regardless if you get mail or not, whether you have something coming or not. #Inspirenaire

Inspirenaire

18,205 просмотров • 3 месяцев назад

Demis Hassabis just explained why the real AI bottleneck has nothing to do with training runs. Most people picture the AI arms race as who can build the biggest model. GPT-4 or Gemini Ultra style training runs, a few hundred million in compute, fired once or twice a year. The constraint sits somewhere else. Every time a researcher has a new algorithmic idea, a new architecture, a new training technique, they can't just test it on a laptop. They have to run it at the scale where it would actually be deployed, because ideas that look promising at small scale fall apart completely when you put them into a real system. Every research hypothesis burns significant compute before a single line of production code gets written. At a lab like DeepMind, hundreds of researchers are running hundreds of ideas simultaneously. The demand for experimental compute is continuous. It never stops. Now layer the hardware reality on top. GPU lead times are currently 36 to 52 weeks for data center hardware. Global AI data centers are already drawing 29.6 gigawatts, equivalent to the peak power demand of the entire state of New York, and they still can't meet demand. Companies willing to pay any price can't just buy more compute. They wait in line. The speed of scientific discovery in AI is now gated by hardware availability. The next breakthrough is sitting in a researcher's head right now. Whether it gets validated fast enough to matter depends entirely on whether the compute is there when they need it. The AI race gets won by whoever can run the most experiments per month.

Demis Hassabis just explained why the real AI bottleneck has nothing to do with training runs. Most people picture the AI arms race as who can build the biggest model. GPT-4 or Gemini Ultra style training runs, a few hundred million in compute, fired once or twice a year. The constraint sits somewhere else. Every time a researcher has a new algorithmic idea, a new architecture, a new training technique, they can't just test it on a laptop. They have to run it at the scale where it would actually be deployed, because ideas that look promising at small scale fall apart completely when you put them into a real system. Every research hypothesis burns significant compute before a single line of production code gets written. At a lab like DeepMind, hundreds of researchers are running hundreds of ideas simultaneously. The demand for experimental compute is continuous. It never stops. Now layer the hardware reality on top. GPU lead times are currently 36 to 52 weeks for data center hardware. Global AI data centers are already drawing 29.6 gigawatts, equivalent to the peak power demand of the entire state of New York, and they still can't meet demand. Companies willing to pay any price can't just buy more compute. They wait in line. The speed of scientific discovery in AI is now gated by hardware availability. The next breakthrough is sitting in a researcher's head right now. Whether it gets validated fast enough to matter depends entirely on whether the compute is there when they need it. The AI race gets won by whoever can run the most experiments per month.

Aakash Gupta

31,285 просмотров • 3 месяцев назад

Jensen Huang just replaced the most important metric in global economics. Not trade volume. Not oil output. Not manufacturing. Compute. Huang: “Compute equals GDP. I know that for certain.” He did not say probably. He said certain. If your nation does not produce compute, it does not produce intelligence. If it does not produce intelligence, it does not produce revenue. Two links in the chain. Miss one and the whole thing breaks. Huang: “Not one country in the future will say, ‘Guess what, we’re gonna opt out on intelligence.’” Because opting out of compute is not a strategic decision. It is an extinction schedule. Every country that does not build its own inference capacity becomes a tenant in someone else’s infrastructure. Not an ally. Not a partner. A dependent. And dependents do not negotiate terms. They accept them. But this is not just a story about nations. Huang: “The entire software industry will be token-driven.” Every product. Every platform. Every service you touch. The entire business model of software is about to be measured in tokens consumed. Not seats sold. Not licenses renewed. Tokens burned. Software used to be a thing you bought. Now it is a thing that thinks. And thinking costs compute. Every query. Every action. Every decision the machine makes on your behalf. The meter is always running. Huang: “The entire internet industry could take 100% of their CapEx and make it AI because it’s better.” Not ten percent. Not a pilot program. One hundred percent. The moment any internet service rebuilds itself on generative intelligence, it outperforms every version that came before it. Search. Ads. Recommendation. Infrastructure. All of it. Better on contact. CapEx follows. All of it. Trillions moving in one direction with no offramp. The companies still budgeting AI as a line item are telling you exactly how much they understand. AI is not the line item. AI is the budget. The global economy is being re-denominated in a currency most people have not even heard of yet. Tokens. Whoever controls the supply of that currency is not playing in the new economy. They are the house. And the house does not lose.

Jensen Huang just replaced the most important metric in global economics. Not trade volume. Not oil output. Not manufacturing. Compute. Huang: “Compute equals GDP. I know that for certain.” He did not say probably. He said certain. If your nation does not produce compute, it does not produce intelligence. If it does not produce intelligence, it does not produce revenue. Two links in the chain. Miss one and the whole thing breaks. Huang: “Not one country in the future will say, ‘Guess what, we’re gonna opt out on intelligence.’” Because opting out of compute is not a strategic decision. It is an extinction schedule. Every country that does not build its own inference capacity becomes a tenant in someone else’s infrastructure. Not an ally. Not a partner. A dependent. And dependents do not negotiate terms. They accept them. But this is not just a story about nations. Huang: “The entire software industry will be token-driven.” Every product. Every platform. Every service you touch. The entire business model of software is about to be measured in tokens consumed. Not seats sold. Not licenses renewed. Tokens burned. Software used to be a thing you bought. Now it is a thing that thinks. And thinking costs compute. Every query. Every action. Every decision the machine makes on your behalf. The meter is always running. Huang: “The entire internet industry could take 100% of their CapEx and make it AI because it’s better.” Not ten percent. Not a pilot program. One hundred percent. The moment any internet service rebuilds itself on generative intelligence, it outperforms every version that came before it. Search. Ads. Recommendation. Infrastructure. All of it. Better on contact. CapEx follows. All of it. Trillions moving in one direction with no offramp. The companies still budgeting AI as a line item are telling you exactly how much they understand. AI is not the line item. AI is the budget. The global economy is being re-denominated in a currency most people have not even heard of yet. Tokens. Whoever controls the supply of that currency is not playing in the new economy. They are the house. And the house does not lose.

Dustin

43,181 просмотров • 3 месяцев назад

$NodeHub V1 Is Coming! Web3 is entering its breakthrough moment, and NodeHub V1 is the gateway. Blockchain infrastructure has always been the bottleneck to mass adoption. Running nodes requires capital, technical expertise, and ongoing maintenance, barriers that keep both individuals and projects locked out. NodeHub V1 changes everything. With NodeHub, anyone can deploy full validator or RPC nodes in seconds, access fractional ownership models to earn without heavy upfront costs, scale infrastructure with enterprise grade reliability, and plug into a decentralized, tokenized marketplace for compute. This is more than just accessibility. It is a paradigm shift in how Web3 infrastructure is operated and monetized. The blockchain infrastructure market is projected to reach trillions as demand for validation, DePIN services, and AI compute explodes. Every project needs nodes. Every network needs validators. Every user wants yield without barriers. With NodeHub, Messiah positions itself at the heart of this market, the on-ramp for projects, enterprises, and individuals to tap into decentralized infrastructure. NodeHub V1 is the bridge between today’s complexity and tomorrow’s adoption. It is how $MSIA will change the way projects launch, scale, and operate, while giving people everywhere the chance to earn from powering the decentralized internet. The launch of NodeHub V1 is imminent. Get started:$

NodeHub V1 Is Coming! Web3 is entering its breakthrough moment, and NodeHub V1 is the gateway. Blockchain infrastructure has always been the bottleneck to mass adoption. Running nodes requires capital, technical expertise, and ongoing maintenance, barriers that keep both individuals and projects locked out. NodeHub V1 changes everything. With NodeHub, anyone can deploy full validator or RPC nodes in seconds, access fractional ownership models to earn without heavy upfront costs, scale infrastructure with enterprise grade reliability, and plug into a decentralized, tokenized marketplace for compute. This is more than just accessibility. It is a paradigm shift in how Web3 infrastructure is operated and monetized. The blockchain infrastructure market is projected to reach trillions as demand for validation, DePIN services, and AI compute explodes. Every project needs nodes. Every network needs validators. Every user wants yield without barriers. With NodeHub, Messiah positions itself at the heart of this market, the on-ramp for projects, enterprises, and individuals to tap into decentralized infrastructure. NodeHub V1 is the bridge between today’s complexity and tomorrow’s adoption. It is how $MSIA will change the way projects launch, scale, and operate, while giving people everywhere the chance to earn from powering the decentralized internet. The launch of NodeHub V1 is imminent. Get started:

Messiah

81,770 просмотров • 11 месяцев назад

With the former CDC Director sitting just feet away, Senator Rand Paul tore the mask off the entire vaccine narrative pushed during COVID. This was a reckoning. And Susan Monarez could do nothing but sit there with a phony smile painted on her face as Paul dismantled the entire logic behind the CDC recommendations. “When they approved it, they had this discussion at the vaccine committee that we’ve been talking about.” “During the discussion, they acknowledged that there was no proof of reduction in hospitalization or in death.” “So what they did is they said, what can we use to try to make people take this vaccine?” “They came up with this. They said that if we give you a COVID vaccine, you make antibodies. So really the whole recommendation for having a COVID vaccine from six months up is not based on hospitalization data, not based on deaths.” “It’s based on whether you make antibodies or not and what people fail to see from this is I can inject you with a foreign protein every week and measure antibodies.” “You’ll make antibodies every time.” “It just means immunology work, it has nothing to do with whether you should get a vaccine every week.”

With the former CDC Director sitting just feet away, Senator Rand Paul tore the mask off the entire vaccine narrative pushed during COVID. This was a reckoning. And Susan Monarez could do nothing but sit there with a phony smile painted on her face as Paul dismantled the entire logic behind the CDC recommendations. “When they approved it, they had this discussion at the vaccine committee that we’ve been talking about.” “During the discussion, they acknowledged that there was no proof of reduction in hospitalization or in death.” “So what they did is they said, what can we use to try to make people take this vaccine?” “They came up with this. They said that if we give you a COVID vaccine, you make antibodies. So really the whole recommendation for having a COVID vaccine from six months up is not based on hospitalization data, not based on deaths.” “It’s based on whether you make antibodies or not and what people fail to see from this is I can inject you with a foreign protein every week and measure antibodies.” “You’ll make antibodies every time.” “It just means immunology work, it has nothing to do with whether you should get a vaccine every week.”

The Vigilant Fox 🦊

165,957 просмотров • 10 месяцев назад

This World Cup has shown how Argentinian players are just built different, and it was interesting because, in the press conferences, both managers addressed this. First, Tuchel talks about the Argentinian value of the ball and how they protect the ball at all costs, how they manage those small spaces, and how they learn this from a young age. He references culture, and this is exactly it. A child playing in a certain environment leads to that. Not every Argentinian child is on the national team, but it raises the ceiling. It creates a certain type of style and a certain type of player. Then Scaloni also references his culture. He sees them play without fear of losing. It comes from playing in an environment where you are constantly faced with the potential of losing and being able to play with that pressure, right? They don’t fight against it. They play with it. They use it. And I think this is where youth football coaches should really take note. This does not mean we should copy and paste Argentinian culture into every training environment, because culture cannot just be copied. But the values within that culture can be inculcated in every training environment. The value of the ball. The courage to receive it in small spaces. The ability to protect it under pressure. The confidence to keep playing after a mistake. The willingness to play with the possibility of losing rather than constantly trying to avoid it. Those values can become part of the environment we create every day. They can be present in the games we design, in what we praise, in what we allow players to struggle with, and in how we respond when they lose the ball. If every mistake leads to the coach stopping the session, giving the answer, or taking the pressure away, then players never learn to play with that pressure. They learn to wait for the coach. It was cool to see how two managers, at such a big stage, reference culture and the environments that kids play in when they’re young. Because the players we see on the biggest stage were not only created by tactics or coaching information. They were created by environments that taught them what to value, how to relate to the ball, and how to play when there was something to lose.

This World Cup has shown how Argentinian players are just built different, and it was interesting because, in the press conferences, both managers addressed this. First, Tuchel talks about the Argentinian value of the ball and how they protect the ball at all costs, how they manage those small spaces, and how they learn this from a young age. He references culture, and this is exactly it. A child playing in a certain environment leads to that. Not every Argentinian child is on the national team, but it raises the ceiling. It creates a certain type of style and a certain type of player. Then Scaloni also references his culture. He sees them play without fear of losing. It comes from playing in an environment where you are constantly faced with the potential of losing and being able to play with that pressure, right? They don’t fight against it. They play with it. They use it. And I think this is where youth football coaches should really take note. This does not mean we should copy and paste Argentinian culture into every training environment, because culture cannot just be copied. But the values within that culture can be inculcated in every training environment. The value of the ball. The courage to receive it in small spaces. The ability to protect it under pressure. The confidence to keep playing after a mistake. The willingness to play with the possibility of losing rather than constantly trying to avoid it. Those values can become part of the environment we create every day. They can be present in the games we design, in what we praise, in what we allow players to struggle with, and in how we respond when they lose the ball. If every mistake leads to the coach stopping the session, giving the answer, or taking the pressure away, then players never learn to play with that pressure. They learn to wait for the coach. It was cool to see how two managers, at such a big stage, reference culture and the environments that kids play in when they’re young. Because the players we see on the biggest stage were not only created by tactics or coaching information. They were created by environments that taught them what to value, how to relate to the ball, and how to play when there was something to lose.

David Garcia

157,642 просмотров • 2 дней назад