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Storage just stole the show. Between KV cache offload and SSD prices going vertical, storage went from afterthought to headliner. Vik Malyala walks through Supermicro's storage stack. "Storage, whether it be for KV cache offload or just the incredible rise in cost of SSDs, is the primary thing to...

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SemiAnalysis

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61,919 次观看 • 2 个月前 •via X (Twitter)

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$WDC CEO says storage demand and requirement compound and grow whether AI runs on US frontier models or cheaper open-source ones. "Whether it's the traditional frontier models that you've seen in the U.S. that are premium-based, or some of the new open-source, more economical models, the underlying requirement is still that they're going to require a lot of data to support the training of these models." "These models are going to generate a lot more data that requires storage for us." "So we view it as very positive, because even as compute maybe drives greater efficiency in terms of compute and memory resources, the requirement for storage is just going to compound and grow." "So we view it very positively for demand going forward."
0:35

$WDC CEO says storage demand and requirement compound and grow whether AI runs on US frontier models or cheaper open-source ones. "Whether it's the traditional frontier models that you've seen in the U.S. that are premium-based, or some of the new open-source, more economical models, the underlying requirement is still that they're going to require a lot of data to support the training of these models." "These models are going to generate a lot more data that requires storage for us." "So we view it as very positive, because even as compute maybe drives greater efficiency in terms of compute and memory resources, the requirement for storage is just going to compound and grow." "So we view it very positively for demand going forward."

Fireside Alpha

14,114 次观看 • 1 个月前

The Easiest Way Into Decentralized AI: Space Acres Powered by Proof-of-Archival-Storage, Autonomys | AI3.0 makes it simple for anyone to get involved. During the BitMart AMA, CEO Todd Ruoff | AI3.0 explained: 👉 “You need no tokens to get started. Just download the client, plot your drive, and off you go. This novel mechanism creates a tremendously decentralized and secure network, and as a byproduct of that security, we get storage — and that storage is what we think is going to be very useful going forward with AI and a lot of other applications.” 🎥 Watch the clip Start farming today:
0:33

The Easiest Way Into Decentralized AI: Space Acres Powered by Proof-of-Archival-Storage, Autonomys | AI3.0 makes it simple for anyone to get involved. During the BitMart AMA, CEO Todd Ruoff | AI3.0 explained: 👉 “You need no tokens to get started. Just download the client, plot your drive, and off you go. This novel mechanism creates a tremendously decentralized and secure network, and as a byproduct of that security, we get storage — and that storage is what we think is going to be very useful going forward with AI and a lot of other applications.” 🎥 Watch the clip Start farming today:

Autonomys | AI3.0

22,416 次观看 • 1 年前

Alberta Premier Danielle Smith: “I want to talk about batteries for a minute, because I know that everybody thinks that this economy is going to be operated on wind and solar and battery power — and it cannot. There is no industrialized economy in the world operating that way, because they need baseload. And, I’ll tell you what I know about batteries, because I talked to somebody thinking of investing in it on a 200 megawatt plant. One million dollars to be able to get each megawatt stored: that’s 200 million dollars for his plant alone, and he would get 1 hour of storage. So if you want me to have 12 thousand megawatts of storage, that’s 12 billion dollars for 1 hour of storage, 24 billion dollars for 2 hours of storage, 36 billion dollars for 3 hours of storage, and there are long stretches in winter, where we can go weeks without wind or solar. That is the reason why we need legitimate, real solutions that rely on baseload power rather than fantasy thinking.” Nicely said Premier Smith. 💪😎
0:53

Alberta Premier Danielle Smith: “I want to talk about batteries for a minute, because I know that everybody thinks that this economy is going to be operated on wind and solar and battery power — and it cannot. There is no industrialized economy in the world operating that way, because they need baseload. And, I’ll tell you what I know about batteries, because I talked to somebody thinking of investing in it on a 200 megawatt plant. One million dollars to be able to get each megawatt stored: that’s 200 million dollars for his plant alone, and he would get 1 hour of storage. So if you want me to have 12 thousand megawatts of storage, that’s 12 billion dollars for 1 hour of storage, 24 billion dollars for 2 hours of storage, 36 billion dollars for 3 hours of storage, and there are long stretches in winter, where we can go weeks without wind or solar. That is the reason why we need legitimate, real solutions that rely on baseload power rather than fantasy thinking.” Nicely said Premier Smith. 💪😎

Paul Mitchell

172,209 次观看 • 2 年前

Dylan Patel of SemiAnalysis says a worse GPU with better storage and memory now beats the best chip without them, so buying the newest GPU alone no longer wins inference. So, an AMD GPU with more memory can outperform Nvidia in some cases. "So what we have is we have over $80 million of compute, GPUs from Nvidia, AMD, TPUs from Google, Trainium from Amazon, and we run this benchmark constantly on the newest inference engine, newest drivers, newest PyTorch version, whatever it is." "Every day it runs on an automated CI, and we run it on all the latest Chinese models, from GLM, Zhipu, Moonshot, Kimi, Alibaba, all these models we run." "Initially, when we were benchmarking the difference between these chips and different engines, different schemes for parallelism, we were just running it fixed context length." "But now with Agent X, we've analyzed over $5 million worth of Claude Code traces. This is real production traffic that people have donated to us as well as internally generated. Now we know what the actual agent workload looks like." "And then as we implement that and run those benchmarks, it turns out yes, the chip you're using is very important, but now even more important is how are you handling this memory offload?" "And so while an Nvidia GPU is faster than an AMD GPU in most cases, because AMD GPUs have more memory, they actually end up outperforming in some cases." "Or you can have a worse GPU, but a much better storage solution, and now you can outperform what the best GPU can do without those solutions. So just buying the newest and latest GPU alone doesn't get you the best inference economics." "Actually, you need to layer in all these other innovations including storage and memory." [ Who's the top player on your chart? ] "That really is a difficult multivariable problem. And generally that means you need to have, yes, you need to have the best GPU, a GB300, but you also need to have the best storage solutions. And so I won't spoil who's the best right here, but I will say that storage solutions matter a lot and memory solutions matter a lot, as does your front-end networking. That matters a lot."
2:00

Dylan Patel of SemiAnalysis says a worse GPU with better storage and memory now beats the best chip without them, so buying the newest GPU alone no longer wins inference. So, an AMD GPU with more memory can outperform Nvidia in some cases. "So what we have is we have over $80 million of compute, GPUs from Nvidia, AMD, TPUs from Google, Trainium from Amazon, and we run this benchmark constantly on the newest inference engine, newest drivers, newest PyTorch version, whatever it is." "Every day it runs on an automated CI, and we run it on all the latest Chinese models, from GLM, Zhipu, Moonshot, Kimi, Alibaba, all these models we run." "Initially, when we were benchmarking the difference between these chips and different engines, different schemes for parallelism, we were just running it fixed context length." "But now with Agent X, we've analyzed over $5 million worth of Claude Code traces. This is real production traffic that people have donated to us as well as internally generated. Now we know what the actual agent workload looks like." "And then as we implement that and run those benchmarks, it turns out yes, the chip you're using is very important, but now even more important is how are you handling this memory offload?" "And so while an Nvidia GPU is faster than an AMD GPU in most cases, because AMD GPUs have more memory, they actually end up outperforming in some cases." "Or you can have a worse GPU, but a much better storage solution, and now you can outperform what the best GPU can do without those solutions. So just buying the newest and latest GPU alone doesn't get you the best inference economics." "Actually, you need to layer in all these other innovations including storage and memory." [ Who's the top player on your chart? ] "That really is a difficult multivariable problem. And generally that means you need to have, yes, you need to have the best GPU, a GB300, but you also need to have the best storage solutions. And so I won't spoil who's the best right here, but I will say that storage solutions matter a lot and memory solutions matter a lot, as does your front-end networking. That matters a lot."

Fireside Alpha

183,978 次观看 • 2 个月前

The Truth About Switching Our Economy To Electric Energy Exposed. $12,000,000,000 (Billion Dollar) Cost Per 1 Hour Of Battery Storage Would Be Needed. It’s Absolutely Impossible & Pure Insanity “I wanna talk about batteries for a minute because I know that everybody thinks that this economy is going to be operated on wind and solar and battery power, and it cannot. There is no industrialized economy in the world operating that way because they need baseload. And I'll tell you what I know about batteries because I talked to somebody who was thinking of investing in it on a two hundred megawatt plant. $1,000,000 to be able to get each megawatt stored. That's $200,000,000 for his plant alone, And he would get 1 hour of storage. So if you want me to have 12,000 megawatts of storage, that's $12,000,000,000 for 1 hour of storage, $24,000,000,000 for 2 hours of storage, $36,000,000,000 for 3 hours of storage, and there are long stretches In winter, where we can go weeks without wind or solar, that is the reason why we need legitimate, real solutions that rely on base load power rather than fantasy thinking. And I am not going to engage in fantasy thinking and say something is possible When I know that my principal job I I think we need to stop. Principle job is to have a reliable energy grid. That's what I'm trying to do.”
1:04

The Truth About Switching Our Economy To Electric Energy Exposed. $12,000,000,000 (Billion Dollar) Cost Per 1 Hour Of Battery Storage Would Be Needed. It’s Absolutely Impossible & Pure Insanity “I wanna talk about batteries for a minute because I know that everybody thinks that this economy is going to be operated on wind and solar and battery power, and it cannot. There is no industrialized economy in the world operating that way because they need baseload. And I'll tell you what I know about batteries because I talked to somebody who was thinking of investing in it on a two hundred megawatt plant. $1,000,000 to be able to get each megawatt stored. That's $200,000,000 for his plant alone, And he would get 1 hour of storage. So if you want me to have 12,000 megawatts of storage, that's $12,000,000,000 for 1 hour of storage, $24,000,000,000 for 2 hours of storage, $36,000,000,000 for 3 hours of storage, and there are long stretches In winter, where we can go weeks without wind or solar, that is the reason why we need legitimate, real solutions that rely on base load power rather than fantasy thinking. And I am not going to engage in fantasy thinking and say something is possible When I know that my principal job I I think we need to stop. Principle job is to have a reliable energy grid. That's what I'm trying to do.”

Wall Street Apes

212,494 次观看 • 2 年前

Dylan Patel on the importance of memory and storage Two key quotes: "An $NVDA GPU is faster than an $AMD GPU in most cases, but because AMD GPUs have more memory, they can outperform Nvidia in certain workloads." “It is a difficult, multivariable problem. Generally, you need the best GPU, such as a GB300, but you also need the best storage solutions. I will not spoil who comes out on top, but storage solutions matter a lot, memory solutions matter a lot, and frontend networking also matters significantly" Full Quote: “We have over $80 million of compute: GPUs from $NVDA and $AMD, TPUs from Google, and Trainium from Amazon. We constantly run this benchmark using the newest inference engines, drivers, PyTorch versions, and other software. It runs every day through automated CI across the latest Chinese models from GLM, Zhipu, Moonshot, Kimi, Alibaba, and others. Initially, when we were benchmarking the differences between these chips, inference engines, and parallelism schemes, we used fixed context lengths. But with Agent X, we have now analyzed more than $5 million worth of Claude Code traces. This is real production traffic that users have donated to us, combined with internally generated data, so we now understand what an actual agent workload looks like. When we implement those workloads and run the benchmarks, it turns out that the chip you are using is very important, but how you handle memory offload can be even more important. An Nvidia GPU is faster than an AMD GPU in most cases, but because AMD GPUs have more memory, they can outperform Nvidia in certain workloads. Similarly, you can use a less powerful GPU with a much better storage solution and outperform the best GPU when it lacks those solutions. Simply buying the newest GPU does not necessarily give you the best inference economics. You need to layer in other innovations, including storage and memory.” Interviewer: “Who is the top player on your chart? Can you tell us?” Dylan Patel: “It is a difficult, multivariable problem. Generally, you need the best GPU, such as a GB300, but you also need the best storage solutions. I will not spoil who comes out on top, but storage solutions matter a lot, memory solutions matter a lot, and frontend networking also matters significantly.”
2:27

Dylan Patel on the importance of memory and storage Two key quotes: "An $NVDA GPU is faster than an $AMD GPU in most cases, but because AMD GPUs have more memory, they can outperform Nvidia in certain workloads." “It is a difficult, multivariable problem. Generally, you need the best GPU, such as a GB300, but you also need the best storage solutions. I will not spoil who comes out on top, but storage solutions matter a lot, memory solutions matter a lot, and frontend networking also matters significantly" Full Quote: “We have over $80 million of compute: GPUs from $NVDA and $AMD, TPUs from Google, and Trainium from Amazon. We constantly run this benchmark using the newest inference engines, drivers, PyTorch versions, and other software. It runs every day through automated CI across the latest Chinese models from GLM, Zhipu, Moonshot, Kimi, Alibaba, and others. Initially, when we were benchmarking the differences between these chips, inference engines, and parallelism schemes, we used fixed context lengths. But with Agent X, we have now analyzed more than $5 million worth of Claude Code traces. This is real production traffic that users have donated to us, combined with internally generated data, so we now understand what an actual agent workload looks like. When we implement those workloads and run the benchmarks, it turns out that the chip you are using is very important, but how you handle memory offload can be even more important. An Nvidia GPU is faster than an AMD GPU in most cases, but because AMD GPUs have more memory, they can outperform Nvidia in certain workloads. Similarly, you can use a less powerful GPU with a much better storage solution and outperform the best GPU when it lacks those solutions. Simply buying the newest GPU does not necessarily give you the best inference economics. You need to layer in other innovations, including storage and memory.” Interviewer: “Who is the top player on your chart? Can you tell us?” Dylan Patel: “It is a difficult, multivariable problem. Generally, you need the best GPU, such as a GB300, but you also need the best storage solutions. I will not spoil who comes out on top, but storage solutions matter a lot, memory solutions matter a lot, and frontend networking also matters significantly.”

Daniel Romero

48,894 次观看 • 2 个月前

Dylan Patel of SemiAnalysis says speed is the moat in AI inference, and getting there runs through new compute (Groq/Cerebras), KV-cache offload, and networking optimization (Aria). "Most of the infrastructure is pretty optimized for high throughput, I would say, but more and more people want to pay for speed. It turns out agents are very sequential, task-oriented, and models running in sequential tasks." "Trying something, verifying it, checking if it's right, and you do that in a loop. It ends up being very slow." "And speed is the moat. The faster you go, speed is the moat." "So a lot of the workloads and high-end use cases that people are developing now are all focused on high interactivity, and the infrastructure there is quite different." "So let's break that down into a few components." "One is you can do new compute: you can do Groq or Cerebras-style compute, which is very much focused on high interactivity." "But even with existing GPUs you can do a few things. One, if you're focused heavily on time to first token, you might offload KV cache to storage, keep it cached, move it back into the compute whenever you need it, much faster than recomputing." "And the third thing you can do is you have to optimize the network."
1:12

Dylan Patel of SemiAnalysis says speed is the moat in AI inference, and getting there runs through new compute (Groq/Cerebras), KV-cache offload, and networking optimization (Aria). "Most of the infrastructure is pretty optimized for high throughput, I would say, but more and more people want to pay for speed. It turns out agents are very sequential, task-oriented, and models running in sequential tasks." "Trying something, verifying it, checking if it's right, and you do that in a loop. It ends up being very slow." "And speed is the moat. The faster you go, speed is the moat." "So a lot of the workloads and high-end use cases that people are developing now are all focused on high interactivity, and the infrastructure there is quite different." "So let's break that down into a few components." "One is you can do new compute: you can do Groq or Cerebras-style compute, which is very much focused on high interactivity." "But even with existing GPUs you can do a few things. One, if you're focused heavily on time to first token, you might offload KV cache to storage, keep it cached, move it back into the compute whenever you need it, much faster than recomputing." "And the third thing you can do is you have to optimize the network."

Fireside Alpha

284,032 次观看 • 2 个月前

Agents are producing content and working across your daily tasks. But most of it remains in the chatbox, and the next person or agent needs to start over. With Filecoin warm storage, we are building the layer that agents can use to store and share with ease. Molly Mackinlay | momack gives a glimpse on what's coming from us to power your agents with a robust warm storage layer.
2:09

Agents are producing content and working across your daily tasks. But most of it remains in the chatbox, and the next person or agent needs to start over. With Filecoin warm storage, we are building the layer that agents can use to store and share with ease. Molly Mackinlay | momack gives a glimpse on what's coming from us to power your agents with a robust warm storage layer.

Filecoin

86,111 次观看 • 13 天前

Justin Thomas was asked about his group getting put on the clock: "We just didn't really agree with it. ... The hard part to me with the whole pace of play thing is that you, there's so much that goes into golf and there's so much that goes into hole to hole in terms of, are you hitting it close, are you able to tap it in, or you have to mark it, stuff like that, to where, are you holding the group up or are you not, to where it's very hard to make that call. And we just didn't agree with it, to be honest. "But we got taken off, and a hole later we were caught up. So it kind of goes to our point of why we didn't think we should of, but it is what it is. It's a part of it."
1:15

Justin Thomas was asked about his group getting put on the clock: "We just didn't really agree with it. ... The hard part to me with the whole pace of play thing is that you, there's so much that goes into golf and there's so much that goes into hole to hole in terms of, are you hitting it close, are you able to tap it in, or you have to mark it, stuff like that, to where, are you holding the group up or are you not, to where it's very hard to make that call. And we just didn't agree with it, to be honest. "But we got taken off, and a hole later we were caught up. So it kind of goes to our point of why we didn't think we should of, but it is what it is. It's a part of it."

Cameron Jourdan

619,272 次观看 • 4 个月前

If $MU says NAND pricing is still strong, enterprise SSD demand is picking up and AI inference is creating more storage demand then $SNDK should benefit because SanDisk is one of the more direct ways to own that part of the cycle. Hyperscalers are still figuring out the right mix of DRAM, HBM, TLC NAND, QLC NAND and other storage architectures which can keep supply tighter for longer as memory companies are going to be hesitant to add too much capacity before demand becomes clearer. I'm going to be listening closely for Micron’s QLC commentary because QLC NAND for read-heavy inference workloads is the big driver and if Micron calls that out then it would show that the storage side of the AI memory story is still earlier than DRAM.
1:03

If $MU says NAND pricing is still strong, enterprise SSD demand is picking up and AI inference is creating more storage demand then $SNDK should benefit because SanDisk is one of the more direct ways to own that part of the cycle. Hyperscalers are still figuring out the right mix of DRAM, HBM, TLC NAND, QLC NAND and other storage architectures which can keep supply tighter for longer as memory companies are going to be hesitant to add too much capacity before demand becomes clearer. I'm going to be listening closely for Micron’s QLC commentary because QLC NAND for read-heavy inference workloads is the big driver and if Micron calls that out then it would show that the storage side of the AI memory story is still earlier than DRAM.

Shay Boloor

108,953 次观看 • 3 个月前

ABC’s George Stephanopoulos attempted to trip up Secretary of State Marco Rubio by asking the same question about Venezuela three different times. “What is the legal authority for the United States to be running Venezuela?” And three times, Rubio shut him down. RUBIO: “I explained to you what our goals are and how we’re going to use the leverage to make it happen.” “As far as our legal authority on the quarantine, simple. We have court orders. These are sanctioned boats, and we get orders from courts to go after and seize these sanctions. Is a court not a legal authority?” STEPHANOPOULOS: “Is the United States running Venezuela right now?” RUBIO: “Well, I’ve explained once again, I’ll do it one more time.” “What we are running is the direction this is going to move moving forward, and that is we have leverage.” “This leverage we are using and we intend to use. We started using already. You can see where they are running out of storage capacity. In a few weeks, they’re going to have to start pumping oil, unless they make changes.” “That leverage that we have with the armada of boats that are currently positioned, allow us to seize any sanctioned boats coming into or out of Venezuela loaded with oil or on its way in to pick up oil.” “We can pick and choose which ones we go after. We have court orders for each one.” “That will continue to be in place until the people who have control over the levers of power in that country make changes that are not just in the interest of the people of Venezuela but are in the interest of the United States and the things that we care about.” “The legal authority is the court orders that we have.”
2:32

ABC’s George Stephanopoulos attempted to trip up Secretary of State Marco Rubio by asking the same question about Venezuela three different times. “What is the legal authority for the United States to be running Venezuela?” And three times, Rubio shut him down. RUBIO: “I explained to you what our goals are and how we’re going to use the leverage to make it happen.” “As far as our legal authority on the quarantine, simple. We have court orders. These are sanctioned boats, and we get orders from courts to go after and seize these sanctions. Is a court not a legal authority?” STEPHANOPOULOS: “Is the United States running Venezuela right now?” RUBIO: “Well, I’ve explained once again, I’ll do it one more time.” “What we are running is the direction this is going to move moving forward, and that is we have leverage.” “This leverage we are using and we intend to use. We started using already. You can see where they are running out of storage capacity. In a few weeks, they’re going to have to start pumping oil, unless they make changes.” “That leverage that we have with the armada of boats that are currently positioned, allow us to seize any sanctioned boats coming into or out of Venezuela loaded with oil or on its way in to pick up oil.” “We can pick and choose which ones we go after. We have court orders for each one.” “That will continue to be in place until the people who have control over the levers of power in that country make changes that are not just in the interest of the people of Venezuela but are in the interest of the United States and the things that we care about.” “The legal authority is the court orders that we have.”

Overton

213,086 次观看 • 8 个月前

✨ People asked for me to add data storage But becoming like Pastebin is a lot of work cause you have to start moderating it and it'll get lots of abuse So I thought what if we just store the data in the URL so you can share it without me hosting it Chrome has a limit of 32,000 character URLs, but with LZ compression on top of that we can store about 48,000 to 80,000 characters in a URL Here's an excerpt of 1984 by George Orwell on JSON pub:
0:43

✨ People asked for me to add data storage But becoming like Pastebin is a lot of work cause you have to start moderating it and it'll get lots of abuse So I thought what if we just store the data in the URL so you can share it without me hosting it Chrome has a limit of 32,000 character URLs, but with LZ compression on top of that we can store about 48,000 to 80,000 characters in a URL Here's an excerpt of 1984 by George Orwell on JSON pub:

@levelsio

248,624 次观看 • 1 年前

.Palmer Luckey says Erebor won't be a purely digital or purely crypto bank. They're going to have a physical vault with a lot of treasure in it: "A lot of the companies that are very interested in working with us want us to have secure actual vaulted storage."
1:20

.Palmer Luckey says Erebor won't be a purely digital or purely crypto bank. They're going to have a physical vault with a lot of treasure in it: "A lot of the companies that are very interested in working with us want us to have secure actual vaulted storage."

TBPN

18,324 次观看 • 7 个月前

THIS IS WHERE "THE CLOUD" ACTUALLY LIVES - A ROOM OF DELL STORAGE ARRAYS YOU RENT A SLIVER OF EVERY MONTH. that clip is a real datacenter aisle, rack after rack of dell powerstore arrays, every hexagon panel packed with drives. this is "the cloud." not a metaphor, this room, plus the power, cooling and staff keeping it alive. when you pay for cloud storage, you rent a few gigabytes of these arrays. forever. the bill grows with every photo. here's the part they'd rather you not connect. these enterprise drives run on a schedule. data centers swap them out long before they fail, by the pallet. those decommissioned drives get tested and resold as recertified, the same 20tb enterprise disk for a fraction of new. so the exact hardware humming in this room ends up in a nas on your desk, minus the monthly rent. no cloud subscription, no data on someone else's array, no bill that grows with your library. the uncomfortable part isn't that the cloud is huge. it's that "the cloud" was always just this room, and you can buy a piece of it once instead of renting it forever. follow RetroChainer for what the cloud doesn't want you to picture, and bookmark this before your next storage renewal.
1:10

THIS IS WHERE "THE CLOUD" ACTUALLY LIVES - A ROOM OF DELL STORAGE ARRAYS YOU RENT A SLIVER OF EVERY MONTH. that clip is a real datacenter aisle, rack after rack of dell powerstore arrays, every hexagon panel packed with drives. this is "the cloud." not a metaphor, this room, plus the power, cooling and staff keeping it alive. when you pay for cloud storage, you rent a few gigabytes of these arrays. forever. the bill grows with every photo. here's the part they'd rather you not connect. these enterprise drives run on a schedule. data centers swap them out long before they fail, by the pallet. those decommissioned drives get tested and resold as recertified, the same 20tb enterprise disk for a fraction of new. so the exact hardware humming in this room ends up in a nas on your desk, minus the monthly rent. no cloud subscription, no data on someone else's array, no bill that grows with your library. the uncomfortable part isn't that the cloud is huge. it's that "the cloud" was always just this room, and you can buy a piece of it once instead of renting it forever. follow RetroChainer for what the cloud doesn't want you to picture, and bookmark this before your next storage renewal.

RetroChainer

34,236 次观看 • 1 个月前

Prusa CORE One - Side Storage This is a custom-made modular storage system for the Prusa CORE One 3D printer which fits neatly in the left-side recess. Once you print the body of the storage box, you can then decide what type of accessories you want to use - there are various options and you can, of course, design your own. Prusa CORE One - Printable DryBox This is a custom-made, 3D-printable DryBox for the Prusa CORE One 3D printer. It is designed to fit perfectly into the right-side recess (where the spool holder is located). This DryBox enables you to store your filament spools in a more controlled environment - don't forget to add silica gel into the DryBox for it to work. Keep in mind that it's not airtight, so there will be some humidity build-up over time. #3dprinters #3dprinted #3dprint #3dprinting #prusa3d #prusa #prusa #3d #3dprinter #prusaresearch #3dart #diy #diyproject #prusacore #coreone #prusacore #core #drybox #storage #sidepanel #printsheet
1:08

Prusa CORE One - Side Storage This is a custom-made modular storage system for the Prusa CORE One 3D printer which fits neatly in the left-side recess. Once you print the body of the storage box, you can then decide what type of accessories you want to use - there are various options and you can, of course, design your own. Prusa CORE One - Printable DryBox This is a custom-made, 3D-printable DryBox for the Prusa CORE One 3D printer. It is designed to fit perfectly into the right-side recess (where the spool holder is located). This DryBox enables you to store your filament spools in a more controlled environment - don't forget to add silica gel into the DryBox for it to work. Keep in mind that it's not airtight, so there will be some humidity build-up over time. #3dprinters #3dprinted #3dprint #3dprinting #prusa3d #prusa #prusa #3d #3dprinter #prusaresearch #3dart #diy #diyproject #prusacore #coreone #prusacore #core #drybox #storage #sidepanel #printsheet

Prusaguy

30,130 次观看 • 1 年前

Most $SUI holders know one thing about the token: total supply is capped at 10 billion. They have never read the mechanic that makes that cap matter. It is called the Storage Fund. And it is the most important thing in the $SUI tokenomics docs that nobody is talking about. Here is exactly how it works: Every time a transaction adds data to the Sui blockchain, the user pays a storage fee. That fee does not go to validators directly. It goes into the Storage Fund, a pool of SUI that never fully depletes. Here is where it gets interesting. The Storage Fund has its own stake in the network. It earns staking rewards the same way every other stakeholder does. Those rewards are then distributed to validators to compensate them for storing historical data. This solves a problem every other blockchain ignores: When a new validator joins Sui, they have to store all the historical data from transactions that happened before they existed. Why would a new validator pay to store someone else's old data? The Storage Fund pays them for it. Past users who created the storage requirements in the first place funded the pool. Future validators get compensated from that pool indefinitely. The fund pays out only the returns on its capital, never the principal. It cannot be drained. It is designed to survive forever. Now here is the part that directly connects to $SUI token value. The Sui docs state this explicitly: Deflation is a feature of Sui, not a bug. Here is why: Total supply is capped at 10 billion SUI. As network activity increases, more transactions are processed. More transactions mean more storage fees flowing into the Storage Fund. As the Storage Fund grows, it holds more SUI. More SUI held in the fund means less SUI in active circulation. Less circulating supply against the same or growing demand means the value of each SUI token increases. Network growth directly reduces circulating supply. That is not speculation. That is the economic model built into the protocol at the architecture level. One more detail worth knowing: If you delete data you stored on chain, you receive a partial refund of your original storage fees. The system charges for storage, rewards deletion, and compounds the fund's stake indefinitely. Most people holding $SUI today are pricing the speed narrative: The parallel transaction processing. The sub-second finality. The Move language safety. They have not started pricing the storage fund deflation mechanic. That gap between what the tokenomics actually does and what the market currently understands is where the long-term thesis lives. The people who read the docs always buy before the people who read the price.
2:17

Most $SUI holders know one thing about the token: total supply is capped at 10 billion. They have never read the mechanic that makes that cap matter. It is called the Storage Fund. And it is the most important thing in the $SUI tokenomics docs that nobody is talking about. Here is exactly how it works: Every time a transaction adds data to the Sui blockchain, the user pays a storage fee. That fee does not go to validators directly. It goes into the Storage Fund, a pool of SUI that never fully depletes. Here is where it gets interesting. The Storage Fund has its own stake in the network. It earns staking rewards the same way every other stakeholder does. Those rewards are then distributed to validators to compensate them for storing historical data. This solves a problem every other blockchain ignores: When a new validator joins Sui, they have to store all the historical data from transactions that happened before they existed. Why would a new validator pay to store someone else's old data? The Storage Fund pays them for it. Past users who created the storage requirements in the first place funded the pool. Future validators get compensated from that pool indefinitely. The fund pays out only the returns on its capital, never the principal. It cannot be drained. It is designed to survive forever. Now here is the part that directly connects to $SUI token value. The Sui docs state this explicitly: Deflation is a feature of Sui, not a bug. Here is why: Total supply is capped at 10 billion SUI. As network activity increases, more transactions are processed. More transactions mean more storage fees flowing into the Storage Fund. As the Storage Fund grows, it holds more SUI. More SUI held in the fund means less SUI in active circulation. Less circulating supply against the same or growing demand means the value of each SUI token increases. Network growth directly reduces circulating supply. That is not speculation. That is the economic model built into the protocol at the architecture level. One more detail worth knowing: If you delete data you stored on chain, you receive a partial refund of your original storage fees. The system charges for storage, rewards deletion, and compounds the fund's stake indefinitely. Most people holding $SUI today are pricing the speed narrative: The parallel transaction processing. The sub-second finality. The Move language safety. They have not started pricing the storage fund deflation mechanic. That gap between what the tokenomics actually does and what the market currently understands is where the long-term thesis lives. The people who read the docs always buy before the people who read the price.

2xnmore

47,695 次观看 • 4 个月前

Rep Anna Luna says the White House will likely allow permanent immunity for those disclosing knowledge of UFO programs “We do have a meeting set up at the White House. The White House is going to play ball on this. So as Rep Burlison and Burchett has stated they are following through on everything that we are sending them. So the next course of action and something that they are willing to entertain is if you are an intelligence official or have knowledge of locations of materials and in doing our due diligence and following up with the task force they are considering and I do believe that they are going to be providing immunity permanently so that people can't be hit with a violation of the espionage act. So again there's a lot of people that have a lot of information but it's really can we prove it and what information can we then bring forward to the American people.”
0:42

Rep Anna Luna says the White House will likely allow permanent immunity for those disclosing knowledge of UFO programs “We do have a meeting set up at the White House. The White House is going to play ball on this. So as Rep Burlison and Burchett has stated they are following through on everything that we are sending them. So the next course of action and something that they are willing to entertain is if you are an intelligence official or have knowledge of locations of materials and in doing our due diligence and following up with the task force they are considering and I do believe that they are going to be providing immunity permanently so that people can't be hit with a violation of the espionage act. So again there's a lot of people that have a lot of information but it's really can we prove it and what information can we then bring forward to the American people.”

Red Panda Koala

14,941 次观看 • 3 个月前

Trump has forced Iran into an "end-game scenario" by overflowing their oil storage facilities, US Oil & Gas Association President Tim Stewart tells me: “What we gather is that they are almost there… The floating storage has obviously been shut off, which puts intense pressure on the tank storage or the pipeline storage. The Kharg Island situation, which handles 90% of the exports, is under intense pressure. [Iran had] to start turning the valve down on the wells. The problem is that those are very old legacy fields... those fields have water issues, they have pressure issues, they have migration issues with them… Obviously, it's going to have a long-term impact on their ability to ramp up to another 3 million barrels a day."
1:40

Trump has forced Iran into an "end-game scenario" by overflowing their oil storage facilities, US Oil & Gas Association President Tim Stewart tells me: “What we gather is that they are almost there… The floating storage has obviously been shut off, which puts intense pressure on the tank storage or the pipeline storage. The Kharg Island situation, which handles 90% of the exports, is under intense pressure. [Iran had] to start turning the valve down on the wells. The problem is that those are very old legacy fields... those fields have water issues, they have pressure issues, they have migration issues with them… Obviously, it's going to have a long-term impact on their ability to ramp up to another 3 million barrels a day."

Glenn Beck

109,351 次观看 • 4 个月前

Free electricity for every American? Chamath explains how it’s possible. Chamath Palihapitiya: “I think the president should try to create a $300B-$500B tax equity fund and help eliminate the electricity costs of 50-100M American households.” “If you actually go to solar and storage, for every 15 million homes, you take a terawatt hour of demand off the grid, that's an extra terawatt hour that you don't need to build.” “So the reason why I like solar and storage is you make these folks so self-reliant.” “Now all of a sudden we're actually catching up to China faster than we would've otherwise.” “We actually get a 2-for-1. The consumer homes don't have that anxiety anymore. They don't have the bill. And because they're generating their own power, they're off the grid, and now what that means is that extra terawatt hour can actually go to the commercial and industrial applications, including these datacenters.” “The president preserved the ability to make those kinds of investments and be tax advantaged for doing it in the One Big Beautiful Bill.” @jason: “And if we want to live in the age of abundance, and we want to bring the bottom half of the country up, and we want affordability, where do people spend their money?” “Food, groceries, their rent, and their electricity, and the utilities.” “So it doesn't come out of Americans' pockets and their taxes, it comes out of corporations, which are printing money.” “If you wanna talk about redistribution of wealth, this is a way for the great American Mag 7 corporations to give something back to Americans.” Chamath: “We will look back and I think that we will want to have seen these big companies who are unbelievably profitable, step up on behalf of American homeowners.”
1:35

Free electricity for every American? Chamath explains how it’s possible. Chamath Palihapitiya: “I think the president should try to create a $300B-$500B tax equity fund and help eliminate the electricity costs of 50-100M American households.” “If you actually go to solar and storage, for every 15 million homes, you take a terawatt hour of demand off the grid, that's an extra terawatt hour that you don't need to build.” “So the reason why I like solar and storage is you make these folks so self-reliant.” “Now all of a sudden we're actually catching up to China faster than we would've otherwise.” “We actually get a 2-for-1. The consumer homes don't have that anxiety anymore. They don't have the bill. And because they're generating their own power, they're off the grid, and now what that means is that extra terawatt hour can actually go to the commercial and industrial applications, including these datacenters.” “The president preserved the ability to make those kinds of investments and be tax advantaged for doing it in the One Big Beautiful Bill.” @jason: “And if we want to live in the age of abundance, and we want to bring the bottom half of the country up, and we want affordability, where do people spend their money?” “Food, groceries, their rent, and their electricity, and the utilities.” “So it doesn't come out of Americans' pockets and their taxes, it comes out of corporations, which are printing money.” “If you wanna talk about redistribution of wealth, this is a way for the great American Mag 7 corporations to give something back to Americans.” Chamath: “We will look back and I think that we will want to have seen these big companies who are unbelievably profitable, step up on behalf of American homeowners.”

The All-In Podcast

526,669 次观看 • 8 个月前