正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

Will AI data centers become more consolidated — or more distributed? jsun, Founder of FLock.io, sees inference pushing compute outward. Unlike large-scale training, many inference workloads don’t require massive, tightly connected clusters. That could make smaller sites with underused power viable as “mini data centers.” Desmond Lim, Co-founder &... show more

YZi Labs

754,136 subscribers

31,095 次观看 • 1 个月前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

6 条评论

IronRed | SandHive 的头像

IronRed | SandHive1 个月前

@0x7SUN @flock_io Mini data centers = democratized AI access. Imagine edge applications we haven't even dreamed of yet. Can't wait to see the impact!

Onchain Matrix 的头像

Onchain Matrix1 个月前

The distributed inference argument is getting stronger. Smaller compute sites can make sense when workloads can be routed to where power and capacity are available. But I think both views can coexist: centralized infrastructure for training, distributed infrastructure for inference.

jaime 的头像

jaime1 个月前

@0x7SUN @flock_io Inference at the edge makes sense, but i think the real bottleneck isn't compute location, it's latency + data gravity.

NHK | GYNDORE DAY ONE 的头像

NHK | GYNDORE DAY ONE1 个月前

@0x7SUN @flock_io Inference distributes, capital still consolidates

Shahzad 🔶 BNB 的头像

Shahzad 🔶 BNB1 个月前

@0x7SUN @flock_io NFA

lvnbbs_bnb 🐬TermMax 的头像

lvnbbs_bnb 🐬TermMax1 个月前

@0x7SUN @flock_io inference goes edhe but capital stays core

相关视频

Could your home become a mini AI data center? For jsun, CEO of FLock.io, inference opens up that possibility. Large-scale training needs tightly connected GPUs in one place. Inference can be less demanding about where it runs. His example is Gelephu Mindfulness City l Bhutan and its hydropower supply: run inference when power is available, and reduce computing hours during lean periods. “There's an uptime and a lean time. But for inference, that's actually tolerable.” He sees that opening up locations previously considered unsuitable for AI data centers - potentially even our homes. The question is no longer just where to build the next giant data center. It’s how small and distributed AI compute could become.

Could your home become a mini AI data center? For jsun, CEO of FLock.io, inference opens up that possibility. Large-scale training needs tightly connected GPUs in one place. Inference can be less demanding about where it runs. His example is Gelephu Mindfulness City l Bhutan and its hydropower supply: run inference when power is available, and reduce computing hours during lean periods. “There's an uptime and a lean time. But for inference, that's actually tolerable.” He sees that opening up locations previously considered unsuitable for AI data centers - potentially even our homes. The question is no longer just where to build the next giant data center. It’s how small and distributed AI compute could become.

YZi Labs

43,619 次观看 • 29 天前

Think bigger than data centers. Much bigger. Elon Musk just unveiled SpaceXAI's first AI satellite, a spacecraft designed specifically for running AI workloads in orbit. The satellite features 150 kW of solar power, a 70-meter wingspan and massive radiators to dump heat into space, solving one of the biggest challenges in scaling AI. But this is just the beginning. Musk says truly large-scale orbital AI could eventually require hundreds of gigawatts to a terawatt of power, meaning millions of tons of infrastructure in orbit. The long-term vision isn't AI running in data centers. It's AI running in space at a scale that's impossible on Earth. Elon Musk

Think bigger than data centers. Much bigger. Elon Musk just unveiled SpaceXAI's first AI satellite, a spacecraft designed specifically for running AI workloads in orbit. The satellite features 150 kW of solar power, a 70-meter wingspan and massive radiators to dump heat into space, solving one of the biggest challenges in scaling AI. But this is just the beginning. Musk says truly large-scale orbital AI could eventually require hundreds of gigawatts to a terawatt of power, meaning millions of tons of infrastructure in orbit. The long-term vision isn't AI running in data centers. It's AI running in space at a scale that's impossible on Earth. Elon Musk

Tesla Owners Silicon Valley

19,221 次观看 • 4 个月前

Amazon CEO, Jeff Bezos: Within 10-20 years, the giant, gigawatt-scale data centers for AI training clusters will be built in space This would leverage 24/7 solar power and make space a key part of Earth's industrial and technological infrastructure

Amazon CEO, Jeff Bezos: Within 10-20 years, the giant, gigawatt-scale data centers for AI training clusters will be built in space This would leverage 24/7 solar power and make space a key part of Earth's industrial and technological infrastructure

Haider.

729,159 次观看 • 1 年前

As AI context windows grow and inference workloads scale, storage architectures must keep pace. Huawei OceanStor M900 Context Memory Storage delivers massive shared capacity, high-performance data access, and optimized token costs for hyperscale AI data centers.

As AI context windows grow and inference workloads scale, storage architectures must keep pace. Huawei OceanStor M900 Context Memory Storage delivers massive shared capacity, high-performance data access, and optimized token costs for hyperscale AI data centers.

Huawei

8,338,135 次观看 • 25 天前

AI INFRASTRUCTURE/ENERGY DEMAND STOCKS TO KEEP ON WATCH FOR 2026 Ex-CEO $GOOGL Eric Schmidt on energy demand driven by AI: "We need energy and the numbers are profound. What we need from you is energy in all forms. People are planning 10 gigawatt data centers" $IREN: owns and develops vertically integrated data centers for hyperscalers $CIFR: large power footprint, 3.4 GW pipeline for AI workloads + HPC $WULF: high capacity, low cost data center expansion across Texas and New York $NBIS: AI compute and cloud services translating energy into revenue $CLSK: America’s Bitcoin Miner transitioning to AI infrastructure with a massive power footprint across 30+ data center sites $BITF: owns and operates power sites positioned for AI workloads, yet to sign with a hyperscaler but could come this year $GLXY: multi-gigawatt data center infrastructure at scale

AI INFRASTRUCTURE/ENERGY DEMAND STOCKS TO KEEP ON WATCH FOR 2026 Ex-CEO $GOOGL Eric Schmidt on energy demand driven by AI: "We need energy and the numbers are profound. What we need from you is energy in all forms. People are planning 10 gigawatt data centers" $IREN: owns and develops vertically integrated data centers for hyperscalers $CIFR: large power footprint, 3.4 GW pipeline for AI workloads + HPC $WULF: high capacity, low cost data center expansion across Texas and New York $NBIS: AI compute and cloud services translating energy into revenue $CLSK: America’s Bitcoin Miner transitioning to AI infrastructure with a massive power footprint across 30+ data center sites $BITF: owns and operates power sites positioned for AI workloads, yet to sign with a hyperscaler but could come this year $GLXY: multi-gigawatt data center infrastructure at scale

Small Cap Snipa

116,034 次观看 • 10 个月前

AI answers your questions in seconds, but behind that speed is something called inference—the compute-intensive process where trained models generate responses. At AWS, we've built custom chips like Trainium, intelligent routing systems, and unified infrastructure to make inference faster and more affordable. As AI agents handle complex multi-step tasks, inference accounts for 80-90% of AI computing power. We're engineering at planetary scale to keep those milliseconds reliable.

AI answers your questions in seconds, but behind that speed is something called inference—the compute-intensive process where trained models generate responses. At AWS, we've built custom chips like Trainium, intelligent routing systems, and unified infrastructure to make inference faster and more affordable. As AI agents handle complex multi-step tasks, inference accounts for 80-90% of AI computing power. We're engineering at planetary scale to keep those milliseconds reliable.

Amazon Web Services

27,021 次观看 • 8 个月前

$IREN owns and develops large-scale, power-dense data center campuses in energy-rich regions for AI cloud, GPU clusters and build-to-suit data centers. Today’s 800MW Australia announcement reinforces the thesis that IREN can turn massive power capacity into AI infrastructure revenue faster than the market expected.

$IREN owns and develops large-scale, power-dense data center campuses in energy-rich regions for AI cloud, GPU clusters and build-to-suit data centers. Today’s 800MW Australia announcement reinforces the thesis that IREN can turn massive power capacity into AI infrastructure revenue faster than the market expected.

Shay Boloor

164,651 次观看 • 5 个月前

Our approach to AI infra is simple: build the most fungible and flexible fleet to meet the real world's needs across inference and training as Scott Guthrie shared with Alex Kantrowitz. And we are already doing it at scale today, as we power the biggest AI workloads like Copilot and ChatGPT, APIs that power 3P products & enterprise workloads and high scale training.

Our approach to AI infra is simple: build the most fungible and flexible fleet to meet the real world's needs across inference and training as Scott Guthrie shared with Alex Kantrowitz. And we are already doing it at scale today, as we power the biggest AI workloads like Copilot and ChatGPT, APIs that power 3P products & enterprise workloads and high scale training.

Satya Nadella

114,713 次观看 • 1 年前

.Josh Wolfe, co-founder of Lux Capital, discusses why the massive build-out of AI data centers may be overextended: "The amount of spend, the amount of CapEx, the amount of build for these multi-gigawatt data centers, it to me does not make sense." “I'm just not that optimistic that all this compute is actually going to be needed."

.Josh Wolfe, co-founder of Lux Capital, discusses why the massive build-out of AI data centers may be overextended: "The amount of spend, the amount of CapEx, the amount of build for these multi-gigawatt data centers, it to me does not make sense." “I'm just not that optimistic that all this compute is actually going to be needed."

The Information

111,890 次观看 • 7 个月前

AI is exposing a simple truth: digital innovation is accelerating faster than the physical infrastructure required to support it. $IREN was founded to bridge that gap – deploying large scale, grid-connected data centers at unprecedented speed to power the high-energy demands of tomorrow’s compute.

AI is exposing a simple truth: digital innovation is accelerating faster than the physical infrastructure required to support it. $IREN was founded to bridge that gap – deploying large scale, grid-connected data centers at unprecedented speed to power the high-energy demands of tomorrow’s compute.

IREN

293,170 次观看 • 1 年前

2026: the year of explosive AI innovation. Fireworks AI Co-founder & CEO Lin Qiao speaks on how the massive expansion of customized inference and models is creating speed of light production to scale timelines.

2026: the year of explosive AI innovation. Fireworks AI Co-founder & CEO Lin Qiao speaks on how the massive expansion of customized inference and models is creating speed of light production to scale timelines.

NVIDIA

35,963 次观看 • 6 个月前

Mark Cuban warns that the AI boom could turn into a debt bubble, with some data centers eventually becoming obsolete. He believes the industry needs to do more with less power, rather than simply building bigger and more expensive infrastructure. “ A lot of these data centers will turn into pickleball courts.”

Mark Cuban warns that the AI boom could turn into a debt bubble, with some data centers eventually becoming obsolete. He believes the industry needs to do more with less power, rather than simply building bigger and more expensive infrastructure. “ A lot of these data centers will turn into pickleball courts.”

Thomas Sowell Quotes

15,424 次观看 • 7 天前

At the AI in America Summit, Fred Thiel, CEO of MARA, described how data centers are evolving to support both AI and Bitcoin by treating energy like a flexible, optimizable resource. He explained that Bitcoin mining can absorb excess grid capacity, balance energy demand, and complement AI workloads—creating a more efficient model where data centers maximize the value of every megawatt. Explore more: #TheHillTech #AIInfrastructure #DigitalAssets

At the AI in America Summit, Fred Thiel, CEO of MARA, described how data centers are evolving to support both AI and Bitcoin by treating energy like a flexible, optimizable resource. He explained that Bitcoin mining can absorb excess grid capacity, balance energy demand, and complement AI workloads—creating a more efficient model where data centers maximize the value of every megawatt. Explore more: #TheHillTech #AIInfrastructure #DigitalAssets

The Hill Events

13,070 次观看 • 10 个月前

Coming soon: $AI gensyn, the network for machine intelligence, is an open infrastructure layer for AI. It provides infrastructure AI needs to operate at scale: compute, data, and information exchange. Get ready →

Coming soon: $AI gensyn, the network for machine intelligence, is an open infrastructure layer for AI. It provides infrastructure AI needs to operate at scale: compute, data, and information exchange. Get ready →

Kraken Listings

53,246 次观看 • 6 个月前

🚨 🇰🇷 Jensen Huang hints at deeper NVIDIA-LG collaboration in robotics and AI data centers NVIDIA CEO Jensen Huang visited LG Twin Towers on June 8 and emphasized the company’s growing partnership with LG after meeting with LG Chairman Koo Kwang-mo and other executives. Huang said LG is a world-class company across many important future technologies and noted that NVIDIA and LG are working together on many areas. He highlighted robotics as one of the most important fields, describing it as the fusion of electronics, mechanical systems, and artificial intelligence. He said NVIDIA is working with LG on motor technology and mechanical systems, which could support future humanoid robotics. Huang also pointed to next-generation data centers, saying future facilities will scale to gigawatt levels and require advanced cooling, power, and infrastructure technologies. He added that there will be “many more announcements” in the near future, suggesting NVIDIA and LG’s cooperation in AI, robotics, and data centers could become more concrete soon.

🚨 🇰🇷 Jensen Huang hints at deeper NVIDIA-LG collaboration in robotics and AI data centers NVIDIA CEO Jensen Huang visited LG Twin Towers on June 8 and emphasized the company’s growing partnership with LG after meeting with LG Chairman Koo Kwang-mo and other executives. Huang said LG is a world-class company across many important future technologies and noted that NVIDIA and LG are working together on many areas. He highlighted robotics as one of the most important fields, describing it as the fusion of electronics, mechanical systems, and artificial intelligence. He said NVIDIA is working with LG on motor technology and mechanical systems, which could support future humanoid robotics. Huang also pointed to next-generation data centers, saying future facilities will scale to gigawatt levels and require advanced cooling, power, and infrastructure technologies. He added that there will be “many more announcements” in the near future, suggesting NVIDIA and LG’s cooperation in AI, robotics, and data centers could become more concrete soon.

TeslaZoa

35,216 次观看 • 4 个月前

Elon Musk explains Tesla’s new Megapod concept for scaling distributed AI compute: “We’re building a Megapod design that pairs Tesla AI4 computers with x86 systems in a box...essentially digital Optimus in a box Similar to how Megapack packages batteries, a Megapod would combine a large number of AI4 and x86 systems inside one deployable unit These boxes could be placed anywhere across the country or outside the country allowing us to scale AI compute using distributed electricity production There is power available all around the world, including at our Supercharger sites. We have something like 7 gigawatts of power across the Supercharger network, and that continues to grow We could place Megapods at many of these locations and use that distributed power for AI compute I think that could be quite a big deal” Instead of relying entirely on enormous centralized data centers, Tesla could deploy modular AI-compute infrastructure wherever sufficient power is already available

Elon Musk explains Tesla’s new Megapod concept for scaling distributed AI compute: “We’re building a Megapod design that pairs Tesla AI4 computers with x86 systems in a box...essentially digital Optimus in a box Similar to how Megapack packages batteries, a Megapod would combine a large number of AI4 and x86 systems inside one deployable unit These boxes could be placed anywhere across the country or outside the country allowing us to scale AI compute using distributed electricity production There is power available all around the world, including at our Supercharger sites. We have something like 7 gigawatts of power across the Supercharger network, and that continues to grow We could place Megapods at many of these locations and use that distributed power for AI compute I think that could be quite a big deal” Instead of relying entirely on enormous centralized data centers, Tesla could deploy modular AI-compute infrastructure wherever sufficient power is already available

X Freeze

17,025 次观看 • 3 个月前

Why Would We Need Data Centers in Space? I interviewed co-founder and CEO of Starcloud, Philip Johnston to learn exactly why even if AI is a bubble, data centers in space would still prosper. Philip Johnston

Why Would We Need Data Centers in Space? I interviewed co-founder and CEO of Starcloud, Philip Johnston to learn exactly why even if AI is a bubble, data centers in space would still prosper. Philip Johnston

Ellie in Space 🚀💫

39,490 次观看 • 10 个月前

“Bitcoin was the first distributed systems paper I read with an economic layer built into it — and that changed everything.” Kenzi Morikawa (3061.eth) sits down with avery.apt 🇺🇸, Co-Founder & CTO of Aptos, to explore his path from supercomputing and large-scale data infrastructure at Meta to the world of crypto. Avery reflects on discovering Bitcoin and recognizing how economic incentives could transform distributed systems, a realization that eventually shaped his decision to co-found Aptos Labs.

“Bitcoin was the first distributed systems paper I read with an economic layer built into it — and that changed everything.” Kenzi Morikawa (3061.eth) sits down with avery.apt 🇺🇸, Co-Founder & CTO of Aptos, to explore his path from supercomputing and large-scale data infrastructure at Meta to the world of crypto. Avery reflects on discovering Bitcoin and recognizing how economic incentives could transform distributed systems, a realization that eventually shaped his decision to co-found Aptos Labs.

0xBlockwire

65,153 次观看 • 6 天前

🚨 WE’RE NOT BULLISH ENOUGH! 56% of my portfolio is in $IREN, $CIFR, $NBIS, $TE = AI/HPC, GRID & ENERGY. Spend 45 seconds watching this clip, and you’ll know why. 1. $CIFR has an elite team of ex-hyperscaler specialists from $GOOG, $META, and $AAPL optimizing every site. 2. The next couple of years will see more acquisitions, more sites, more deals in AI data centers. 3. $IREN secured a $9.7B AI cloud contract with $MSFT. $CIFR inked a $5.5B lease with $AMZN AWS and has a stake from $GOOG. 4. $NBIS landed $3B with $META and multi-billion with $MSFT. 5. J.P. Morgan forecasts AI infrastructure capex for data centers hitting $1.4 trillion annually by 2030, tripling near-term levels. 6. Jon Gray, President and COO of Blackstone Inc., stated in his latest presentation: “It starts with the picks and shovels, with things like chips, data centers, and power at massive scale. We have really focused on the right two circles here.” (Refering to data centers and power) 7. $NVDA’s Jensen Huang: “We wish we had more compute energy.” 8. The current administration pushes AI, energy, and defense with plans for massive power plants to fuel the AI boom. Onwards, -BP Not financial advice. Turn on notifications 🔔 for alerts on new posts.

🚨 WE’RE NOT BULLISH ENOUGH! 56% of my portfolio is in $IREN, $CIFR, $NBIS, $TE = AI/HPC, GRID & ENERGY. Spend 45 seconds watching this clip, and you’ll know why. 1. $CIFR has an elite team of ex-hyperscaler specialists from $GOOG, $META, and $AAPL optimizing every site. 2. The next couple of years will see more acquisitions, more sites, more deals in AI data centers. 3. $IREN secured a $9.7B AI cloud contract with $MSFT. $CIFR inked a $5.5B lease with $AMZN AWS and has a stake from $GOOG. 4. $NBIS landed $3B with $META and multi-billion with $MSFT. 5. J.P. Morgan forecasts AI infrastructure capex for data centers hitting $1.4 trillion annually by 2030, tripling near-term levels. 6. Jon Gray, President and COO of Blackstone Inc., stated in his latest presentation: “It starts with the picks and shovels, with things like chips, data centers, and power at massive scale. We have really focused on the right two circles here.” (Refering to data centers and power) 7. $NVDA’s Jensen Huang: “We wish we had more compute energy.” 8. The current administration pushes AI, energy, and defense with plans for massive power plants to fuel the AI boom. Onwards, -BP Not financial advice. Turn on notifications 🔔 for alerts on new posts.

Black Panther Capital

58,387 次观看 • 9 个月前