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"It just doesn't compute. And I think when things like this don't compute, it means that there is going to be a very fast reconciliation at some point, which is the Omega Candle and a fast run to $1 million [bitcoin]." - Samson Mow, CEO of JAN3

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.Shaun Maguire says SpaceX's data center deal with Google may suggest there is something fundamentally different about the company's terrestrial compute. "I think a lot of people were surprised by the Anthropic and Google announcements. And I think a lot of people are getting the wrong takeaway there." "The way a lot of people are interpreting that is it's like, 'oh, we're just in this temporary compute shortage. And so anyone's willing to work with anyone, and they're willing to pay any price for compute.'" "I think that might be a reasonable way to look at the Anthropic announcement. I don't think that makes sense for looking at the Google announcement." "To me, I think an alternative hypothesis is that SpaceX's terrestrial compute is not actually a commodity. There's something that's better about it than other people's terrestrial compute."

.Shaun Maguire says SpaceX's data center deal with Google may suggest there is something fundamentally different about the company's terrestrial compute. "I think a lot of people were surprised by the Anthropic and Google announcements. And I think a lot of people are getting the wrong takeaway there." "The way a lot of people are interpreting that is it's like, 'oh, we're just in this temporary compute shortage. And so anyone's willing to work with anyone, and they're willing to pay any price for compute.'" "I think that might be a reasonable way to look at the Anthropic announcement. I don't think that makes sense for looking at the Google announcement." "To me, I think an alternative hypothesis is that SpaceX's terrestrial compute is not actually a commodity. There's something that's better about it than other people's terrestrial compute."

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🚨 JUST IN: Samson Mow says time is running out to buy Bitcoin at low prices "Once we get to $500k Bitcoin, the world is going to wake up and join the race. That's when Bitcoin goes to $1 million and beyond very quickly." (CoinDesk Media)

🚨 JUST IN: Samson Mow says time is running out to buy Bitcoin at low prices "Once we get to $500k Bitcoin, the world is going to wake up and join the race. That's when Bitcoin goes to $1 million and beyond very quickly." (CoinDesk Media)

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Today I had the pleasure of interviewing Samson Mow to discuss: 🔥What do we call a $1M candle? 🔥Where is Bitcoins Veblen Threshold? 🔥When will we see the Bitcoin Omega candle? 📺Check out my FULL interview with Samson Mow below.👇

Today I had the pleasure of interviewing Samson Mow to discuss: 🔥What do we call a $1M candle? 🔥Where is Bitcoins Veblen Threshold? 🔥When will we see the Bitcoin Omega candle? 📺Check out my FULL interview with Samson Mow below.👇

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SAMSON MOW: “it’s not gonna be a gradual slow increase to $1 million a #Bitcoin, but rather a very short and violent upheaval that sends us there in a matter of weeks to months.” 🚀

SAMSON MOW: “it’s not gonna be a gradual slow increase to $1 million a #Bitcoin, but rather a very short and violent upheaval that sends us there in a matter of weeks to months.” 🚀

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SAMSON MOW: “it’s not gonna be a gradual slow increase to $1 million a #Bitcoin, but rather a very short and violent upheaval that sends us there in a matter of weeks to months.” 🚀

SAMSON MOW: “it’s not gonna be a gradual slow increase to $1 million a #Bitcoin, but rather a very short and violent upheaval that sends us there in a matter of weeks to months.” 🚀

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Howard Marks: "AI will change the world, but this doesn't mean there won't be a bubble." This is why I invest exclusively in picks & shovels when it comes to AI. There'll likely be overbuilding, which means picks & shovels will make a lot of money: Compute and energy.

Howard Marks: "AI will change the world, but this doesn't mean there won't be a bubble." This is why I invest exclusively in picks & shovels when it comes to AI. There'll likely be overbuilding, which means picks & shovels will make a lot of money: Compute and energy.

Oguz Erkan

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Jacob talks about making deliberate choices with his shoots: ‘Another trick that I learned years ago is that I don't shoot very much, so nobody can cut my show the way I don't want them to cut it. There's no excess. "Is there a close up?" and I'm like, "No." And so, I do a lot of that, and it's very deliberate. I mean, the thing about the show when you talk about the money and the resources, the reason that it is stretched to a point, is that we shot, I think, 57 locations in 34 days? So to keep the scope of the show the way we wanted, we had to move fast, and we had to get things done. And so that means there's going to be some one-ers, there's going to be some things, and instead of you seeing that as a limitation, you have to view that as like, “This is a fun opportunity to do something interesting.” We shot that cottage in two days. We had two days to do it, and so it was like, “Okay, here we are doing it.” And we finished early. 🗣️ CSA Presents: Focal Point, May 31, 2026. ▶️ ✍🏼 transcription by Heated Rivalry News

Jacob talks about making deliberate choices with his shoots: ‘Another trick that I learned years ago is that I don't shoot very much, so nobody can cut my show the way I don't want them to cut it. There's no excess. "Is there a close up?" and I'm like, "No." And so, I do a lot of that, and it's very deliberate. I mean, the thing about the show when you talk about the money and the resources, the reason that it is stretched to a point, is that we shot, I think, 57 locations in 34 days? So to keep the scope of the show the way we wanted, we had to move fast, and we had to get things done. And so that means there's going to be some one-ers, there's going to be some things, and instead of you seeing that as a limitation, you have to view that as like, “This is a fun opportunity to do something interesting.” We shot that cottage in two days. We had two days to do it, and so it was like, “Okay, here we are doing it.” And we finished early. 🗣️ CSA Presents: Focal Point, May 31, 2026. ▶️ ✍🏼 transcription by Heated Rivalry News

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Chris Haynes on Giannis future with the Bucks and believes he could be moved at some point: "When the losses keep compiling, Giannis is going to have to keep fielding these questions. Thats why its getting to a point he is tired of hearing it. The Bucks have to make a decision. Do you waste a players talent when you know what that player desire is and what you promised him? I don't think this will go away anytime soon. I think he could be moved at some point. Which point? That i don't know. This team is not good. They have to make a miraculous turn around."

Chris Haynes on Giannis future with the Bucks and believes he could be moved at some point: "When the losses keep compiling, Giannis is going to have to keep fielding these questions. Thats why its getting to a point he is tired of hearing it. The Bucks have to make a decision. Do you waste a players talent when you know what that player desire is and what you promised him? I don't think this will go away anytime soon. I think he could be moved at some point. Which point? That i don't know. This team is not good. They have to make a miraculous turn around."

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I'll let Noam Brown (OpenAI research) answer Yann's “told you so” again. There is nothing to add. There is no wall, there is no end in sight! "Now, we are in a world, like I said earlier, where the amount of compute that's going into pretraining for things large language models is very, very high. But the inference costs are very low. And there was a reasonable concern among various people that we were going to start seeing diminishing returns from AI progress because the costs and the amount of data that you need for pretraining would become so astronomical. And I think the really important takeaway from o1 is that that wall doesn't actually exist, that we can actually push this a lot further. Because, now, we can scale up inference compute. And there's so much room to scale up inference compute."

I'll let Noam Brown (OpenAI research) answer Yann's “told you so” again. There is nothing to add. There is no wall, there is no end in sight! "Now, we are in a world, like I said earlier, where the amount of compute that's going into pretraining for things large language models is very, very high. But the inference costs are very low. And there was a reasonable concern among various people that we were going to start seeing diminishing returns from AI progress because the costs and the amount of data that you need for pretraining would become so astronomical. And I think the really important takeaway from o1 is that that wall doesn't actually exist, that we can actually push this a lot further. Because, now, we can scale up inference compute. And there's so much room to scale up inference compute."

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RL is a powerful mechanism for training company-specific models on their unique work and data. This is what we do at Applied Compute. A key challenge is how to make RL efficient, because we need runs to be fast (delivered in days), cheap (scalable unit economics), and predictable (not just fast, but reliably fast). Here are some takeaways: • Synchronous RL is wasteful with time and compute. • Asynchronous RL is more efficient but introduces staleness, which causes learning instabilities. • Modeling and simulations can help analytically solve for what configuration leads to optimal efficiency. This allows us to rapidly prototype training configurations, without burning expensive compute cycles on trial runs. Two of our co-founders, Rhythm Garg and Linden Li, discussed some of this research at AI Engineer recently, with a focus on the following subproblem: what is the highest throughput way to do RL given a maximum staleness and compute budget?

RL is a powerful mechanism for training company-specific models on their unique work and data. This is what we do at Applied Compute. A key challenge is how to make RL efficient, because we need runs to be fast (delivered in days), cheap (scalable unit economics), and predictable (not just fast, but reliably fast). Here are some takeaways: • Synchronous RL is wasteful with time and compute. • Asynchronous RL is more efficient but introduces staleness, which causes learning instabilities. • Modeling and simulations can help analytically solve for what configuration leads to optimal efficiency. This allows us to rapidly prototype training configurations, without burning expensive compute cycles on trial runs. Two of our co-founders, Rhythm Garg and Linden Li, discussed some of this research at AI Engineer recently, with a focus on the following subproblem: what is the highest throughput way to do RL given a maximum staleness and compute budget?

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I don't think there's a single franchise out there that has been as consistently mishandled as Halo. Like it gets to a point that it's almost impressive in a way, if it weren't so sad. It sucks to see the trend setter become the trend chaser, losing it's identity and just trying to be whatever is popular at the time. I don't think we'll ever get this back again. There really is something to be said for series like Dark Souls that know when to end.

I don't think there's a single franchise out there that has been as consistently mishandled as Halo. Like it gets to a point that it's almost impressive in a way, if it weren't so sad. It sucks to see the trend setter become the trend chaser, losing it's identity and just trying to be whatever is popular at the time. I don't think we'll ever get this back again. There really is something to be said for series like Dark Souls that know when to end.

🎮𝙆𝙖𝙞𝙮𝙖🎮

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Shaun Maguire on SpaceX IPO: "Starship is the railroad to space." "In 2019, it was very predictable that Starlink would work and produce a massive amount of revenue, and we called that right." "We're now in a very similar point to where Starlink was in 2019 with AI infrastructure and orbital compute." "I think people are really underestimating how far along the orbital compute product is right now." On the $22 trillion TAM: "What do you think is the TAM for intelligence? What's the TAM for all compute infrastructure 50 years from now?" "People are underappreciating how much infrastructure is going to be built in space and how much easier it is to access energy in space." "We're at the beginning of this AI era, and we're going to double or triple the total amount of intelligence that we have access to over the next decade — so yes, I absolutely believe in the TAM, and I would even argue it's an underestimate." How much is the "railroad to space" worth in the era of AI and orbital compute? Now imagine the railroad company also owns the AI and the orbital compute. Elon Musk Shaun Maguire

Shaun Maguire on SpaceX IPO: "Starship is the railroad to space." "In 2019, it was very predictable that Starlink would work and produce a massive amount of revenue, and we called that right." "We're now in a very similar point to where Starlink was in 2019 with AI infrastructure and orbital compute." "I think people are really underestimating how far along the orbital compute product is right now." On the $22 trillion TAM: "What do you think is the TAM for intelligence? What's the TAM for all compute infrastructure 50 years from now?" "People are underappreciating how much infrastructure is going to be built in space and how much easier it is to access energy in space." "We're at the beginning of this AI era, and we're going to double or triple the total amount of intelligence that we have access to over the next decade — so yes, I absolutely believe in the TAM, and I would even argue it's an underestimate." How much is the "railroad to space" worth in the era of AI and orbital compute? Now imagine the railroad company also owns the AI and the orbital compute. Elon Musk Shaun Maguire

KanekoaTheGreat

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It’s critical that we bring our deficits down — and soon. Since one man’s debts are another man’s assets, debt problems pass through the system very quickly. When there’s a lot of debt, like there is today, it has to be sold — and we’re now at a point where there aren’t enough buyers for that debt. Historically, when that happens, bad things follow. So we need to get this problem under control and we need to do it fast.

It’s critical that we bring our deficits down — and soon. Since one man’s debts are another man’s assets, debt problems pass through the system very quickly. When there’s a lot of debt, like there is today, it has to be sold — and we’re now at a point where there aren’t enough buyers for that debt. Historically, when that happens, bad things follow. So we need to get this problem under control and we need to do it fast.

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