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$EOSE just launched Indensity which is a battery system built specifically for AI data centers that targets ~1 GWh per acre & ~4x the density of traditional storage. It directly addresses the core DC problem which is having steady, dispatchable power to keep GPUs fully utilized so this storage... show more

Shay Boloor

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133,414 просмотров • 6 месяцев назад •via X (Twitter)

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NEWS: BYD has launched its next-generation battery energy storage system. It has a unit capacity of 14.5 MWh, the highest globally to date. The energy storage system achieves an ultra-large capacity of 10 MWh within a space equivalent to a 20-foot container, BYD said. For a 1 GWh storage plant, it will cut the number of required units by more than half, reduce land use by one-third, and trim cell count by 76%, according to the manufacturer. It uses BYD’s self-developed 2,710 Ah Blade Battery cell, which the company claims is the largest energy storage cell in the world. "This next-generation cell delivers three times the capacity of conventional storage batteries, boasts a cycle life of over 10,000 cycles, and reduces the total lifecycle cost per kilowatt-hour to below $0.014 – a milestone that could reshape the economics of large-scale storage." BYD says it can cut project-level levelized costs (LCOS) by 21.7%. For a typical 1 GWh installation, total costs related to equipment procurement, transportation, and installation are expected to drop by around 30%. In addition, BYD has launched its new GC Flux grid-forming inverter solution, which covers the 2.5–10 MW capacity range. According to BYD, the inverter boasts a performance level approximately 38% higher than common industry standards and a maximum power density of 1,474 kW/㎡, which is around 130% above typical values in today’s market. The system provides an overload capacity of up to 3x for 10 seconds and reaches a peak efficiency of 99.35%.

NEWS: BYD has launched its next-generation battery energy storage system. It has a unit capacity of 14.5 MWh, the highest globally to date. The energy storage system achieves an ultra-large capacity of 10 MWh within a space equivalent to a 20-foot container, BYD said. For a 1 GWh storage plant, it will cut the number of required units by more than half, reduce land use by one-third, and trim cell count by 76%, according to the manufacturer. It uses BYD’s self-developed 2,710 Ah Blade Battery cell, which the company claims is the largest energy storage cell in the world. "This next-generation cell delivers three times the capacity of conventional storage batteries, boasts a cycle life of over 10,000 cycles, and reduces the total lifecycle cost per kilowatt-hour to below $0.014 – a milestone that could reshape the economics of large-scale storage." BYD says it can cut project-level levelized costs (LCOS) by 21.7%. For a typical 1 GWh installation, total costs related to equipment procurement, transportation, and installation are expected to drop by around 30%. In addition, BYD has launched its new GC Flux grid-forming inverter solution, which covers the 2.5–10 MW capacity range. According to BYD, the inverter boasts a performance level approximately 38% higher than common industry standards and a maximum power density of 1,474 kW/㎡, which is around 130% above typical values in today’s market. The system provides an overload capacity of up to 3x for 10 seconds and reaches a peak efficiency of 99.35%.

Sawyer Merritt

384,738 просмотров • 10 месяцев назад

This is Amazon's new $11 billion AI data center campus in St. Joseph County, Indiana. It will draw 2.2 gigawatts of electricity - the output of a large power plant, enough to supply 1 million homes. For years the public was told energy had to be rationed: use less, dismantle reliable sources, accept scarcity - all to save the planet. That story has now been abandoned. AI requires massive continuous electricity to power the data centers, and AI is now seen as the superior control system. So energy is no longer a liability. It is a strategic necessity. Power will now come from wherever. Whatever works. Whatever scales. The climate narrative was tossed out the moment AI dominance became the new priority. Power was to be rationed. Now it is required. Power was the problem. Now it is the solution.

This is Amazon's new $11 billion AI data center campus in St. Joseph County, Indiana. It will draw 2.2 gigawatts of electricity - the output of a large power plant, enough to supply 1 million homes. For years the public was told energy had to be rationed: use less, dismantle reliable sources, accept scarcity - all to save the planet. That story has now been abandoned. AI requires massive continuous electricity to power the data centers, and AI is now seen as the superior control system. So energy is no longer a liability. It is a strategic necessity. Power will now come from wherever. Whatever works. Whatever scales. The climate narrative was tossed out the moment AI dominance became the new priority. Power was to be rationed. Now it is required. Power was the problem. Now it is the solution.

Electroverse

41,103 просмотров • 5 месяцев назад

NEWS: A massive new $450 million Tesla Megapack battery energy storage system is now operational in Victoria, Australia. It's the biggest completed battery project on Australia’s main grid, and one of largest battery projects in the world. It features 444 Tesla Megapacks and three Toshiba 500kV HV transformers, for a total of 600 megawatts of capacity and 1,600 megawatt hours of storage. It will soak up excess wind & solar power during the daytime and shift that energy to the evening peaks.

NEWS: A massive new $450 million Tesla Megapack battery energy storage system is now operational in Victoria, Australia. It's the biggest completed battery project on Australia’s main grid, and one of largest battery projects in the world. It features 444 Tesla Megapacks and three Toshiba 500kV HV transformers, for a total of 600 megawatts of capacity and 1,600 megawatt hours of storage. It will soak up excess wind & solar power during the daytime and shift that energy to the evening peaks.

Sawyer Merritt

116,042 просмотров • 7 месяцев назад

🇺🇦🇷🇺 Ukraine hit Crimea’s only underground gas storage facility near Tarkhankut, triggering a fire at a key energy site for the occupied peninsula. Operators from Ukraine’s 413th SBS “Raid” Regiment reportedly used Fire Point medium-range drones to strike the Glebovskoye facility, which helps regulate gas supply during peak demand. The target matters because it supports the Balaklava and Tavricheskaya thermal power plants, which help power Russian military installations across Crimea. Writer: Sol

🇺🇦🇷🇺 Ukraine hit Crimea’s only underground gas storage facility near Tarkhankut, triggering a fire at a key energy site for the occupied peninsula. Operators from Ukraine’s 413th SBS “Raid” Regiment reportedly used Fire Point medium-range drones to strike the Glebovskoye facility, which helps regulate gas supply during peak demand. The target matters because it supports the Balaklava and Tavricheskaya thermal power plants, which help power Russian military installations across Crimea. Writer: Sol

Mario Nawfal

20,892 просмотров • 29 дней назад

Elon Musk explains the “series of miracles” xAI had to achieve to bring one gigawatt of power online for its supercomputer cluster in Memphis The xAI team coordinated dozens of gas turbines, faced permit challenges in Tennessee, and ultimately moved the power generation just across the border into Mississippi. From there, they had to run high-voltage transmission lines and build an entire power plant on the Mississippi side and it was very difficult to build that But the deeper point is even more important Most people calculate AI power needs by looking only at the GPUs. That is a serious mistake. A real data center also requires substantial power for networking, CPUs, storage, and most critically cooling In Memphis, where summer temperatures are extreme, peak cooling demand can add roughly 40% more power. On top of that, operators must maintain extra capacity so generators can be taken offline for servicing without shutting down the entire system. This redundancy typically adds another 20 to 25 percent When all of these factors are included, Elon stated that approximately 110,000 GB300 GPUs require roughly 330 megawatts of actual power generation This is why building and powering frontier AI data centers is far more difficult and far more capital intensive than it appears from the outside

Elon Musk explains the “series of miracles” xAI had to achieve to bring one gigawatt of power online for its supercomputer cluster in Memphis The xAI team coordinated dozens of gas turbines, faced permit challenges in Tennessee, and ultimately moved the power generation just across the border into Mississippi. From there, they had to run high-voltage transmission lines and build an entire power plant on the Mississippi side and it was very difficult to build that But the deeper point is even more important Most people calculate AI power needs by looking only at the GPUs. That is a serious mistake. A real data center also requires substantial power for networking, CPUs, storage, and most critically cooling In Memphis, where summer temperatures are extreme, peak cooling demand can add roughly 40% more power. On top of that, operators must maintain extra capacity so generators can be taken offline for servicing without shutting down the entire system. This redundancy typically adds another 20 to 25 percent When all of these factors are included, Elon stated that approximately 110,000 GB300 GPUs require roughly 330 megawatts of actual power generation This is why building and powering frontier AI data centers is far more difficult and far more capital intensive than it appears from the outside

X Freeze

140,274 просмотров • 2 месяцев назад

🔋 Ever wondered how batteries can strengthen a country's power grid? Our Energy Storage Lead Vadim Utkin explains how Ukraine's first utility-scale battery system is revolutionising its energy security: - What battery storage actually does - Why Ukraine needs it right now - How we built it during wartime - What it means for this winter Ukraine is the ultimate testing ground to demonstrate the resilience of this energy technology. Watch how we're opening a new chapter for Ukraine`s energy system.

🔋 Ever wondered how batteries can strengthen a country's power grid? Our Energy Storage Lead Vadim Utkin explains how Ukraine's first utility-scale battery system is revolutionising its energy security: - What battery storage actually does - Why Ukraine needs it right now - How we built it during wartime - What it means for this winter Ukraine is the ultimate testing ground to demonstrate the resilience of this energy technology. Watch how we're opening a new chapter for Ukraine`s energy system.

DTEK Group

3,103,231 просмотров • 10 месяцев назад

TESLA FLIPS THE SWITCH ON A MEGAPACK GIANT IN CALIFORNIA Tesla has brought a serious heavyweight online in Kern County, California: a Megapack battery system paired with 500 megawatts of solar generation. That combination puts the project among the largest solar plus storage sites in the United States, and it is now fully operational. At full output, the site can supply enough electricity to cover the annual needs of roughly 467,000 homes. More importantly, it does so when the grid actually needs it most. Power generated during sunny daytime hours is stored and then released in the evening, when demand spikes and solar production drops. That shift alone helps prevent outages and reduces reliance on gas peaker plants. The emissions impact is just as significant. The project is expected to cut more than one million metric tons of carbon dioxide every year, while adding real stability to a grid that has struggled during heat waves and peak demand events. California has quietly become the proving ground for large-scale battery storage, and this site shows why. Energy storage is no longer theoretical or niche. It is operational, reliable, and scalable. Tesla’s Megapack footprint keeps expanding worldwide, and projects like this make the case clearly. Clean energy is not just about generation anymore. It is about control, timing, and resilience. Source: Tesla Megapack

TESLA FLIPS THE SWITCH ON A MEGAPACK GIANT IN CALIFORNIA Tesla has brought a serious heavyweight online in Kern County, California: a Megapack battery system paired with 500 megawatts of solar generation. That combination puts the project among the largest solar plus storage sites in the United States, and it is now fully operational. At full output, the site can supply enough electricity to cover the annual needs of roughly 467,000 homes. More importantly, it does so when the grid actually needs it most. Power generated during sunny daytime hours is stored and then released in the evening, when demand spikes and solar production drops. That shift alone helps prevent outages and reduces reliance on gas peaker plants. The emissions impact is just as significant. The project is expected to cut more than one million metric tons of carbon dioxide every year, while adding real stability to a grid that has struggled during heat waves and peak demand events. California has quietly become the proving ground for large-scale battery storage, and this site shows why. Energy storage is no longer theoretical or niche. It is operational, reliable, and scalable. Tesla’s Megapack footprint keeps expanding worldwide, and projects like this make the case clearly. Clean energy is not just about generation anymore. It is about control, timing, and resilience. Source: Tesla Megapack

Mario Nawfal

67,663 просмотров • 7 месяцев назад

AI shouldn’t just belong to a few big companies 🤖 OORT | The Data Cloud for Decentralized AI is creating a decentralized AI cloud where your data, storage, and compute help power the next generation of AI , and you get rewarded for it. Global, transparent, and community-driven. Are you ready to join? 🌍⚡ #OORT #DecentralizedAI #Blockchain #Web3 #AICommunity #CryptoTech #DataRevolution #Onchain #Innovation #FutureOfAI

AI shouldn’t just belong to a few big companies 🤖 OORT | The Data Cloud for Decentralized AI is creating a decentralized AI cloud where your data, storage, and compute help power the next generation of AI , and you get rewarded for it. Global, transparent, and community-driven. Are you ready to join? 🌍⚡ #OORT #DecentralizedAI #Blockchain #Web3 #AICommunity #CryptoTech #DataRevolution #Onchain #Innovation #FutureOfAI

Sky Wee

194,643 просмотров • 6 месяцев назад

Groq's LPU is faster than GPUs, handling requests and responding more quickly. Groq's LPUs don't need speedy data delivery like Nvidia GPUs do because they don't have HBM in their system. They use SRAM, which is about 20 times faster than what GPUs use. Since inference runs use way less data than model training, Groq's LPU is more energy-efficient. It reads less from external memory and uses less power than a Nvidia GPU for inference tasks. The LPU works differently from GPUs. It uses a Temporal Instruction Set Computer architecture, so it doesn't have to reload data from memory as often as GPUs do with High Bandwidth Memory (HBM). This helps avoid issues with HBM shortages and keeps costs down. If Groq's LPU is used in places that do AI processing, you might not need special storage for Nvidia GPUs. The LPU doesn't demand super-fast storage like GPUs do. Groq is claiming that its technology could replace GPUs in AI tasks with its powerful chip and software.

Groq's LPU is faster than GPUs, handling requests and responding more quickly. Groq's LPUs don't need speedy data delivery like Nvidia GPUs do because they don't have HBM in their system. They use SRAM, which is about 20 times faster than what GPUs use. Since inference runs use way less data than model training, Groq's LPU is more energy-efficient. It reads less from external memory and uses less power than a Nvidia GPU for inference tasks. The LPU works differently from GPUs. It uses a Temporal Instruction Set Computer architecture, so it doesn't have to reload data from memory as often as GPUs do with High Bandwidth Memory (HBM). This helps avoid issues with HBM shortages and keeps costs down. If Groq's LPU is used in places that do AI processing, you might not need special storage for Nvidia GPUs. The LPU doesn't demand super-fast storage like GPUs do. Groq is claiming that its technology could replace GPUs in AI tasks with its powerful chip and software.

Brian Roemmele

87,151 просмотров • 2 лет назад

Powerwall 3P is now available in Germany The new three-phase energy storage system is designed to meet the power needs of 95% of German homes with a single unit while optimizing energy usage to maximize savings - 15.4 kW continuous AC output - 21 kW peak power during power outages - Supports mixed DC- and AC-coupled configurations - 4 MPPTs, making it suitable for different roof orientations and shading conditions - Comes standard with Tesla Home, a fully integrated home energy management system

Powerwall 3P is now available in Germany The new three-phase energy storage system is designed to meet the power needs of 95% of German homes with a single unit while optimizing energy usage to maximize savings - 15.4 kW continuous AC output - 21 kW peak power during power outages - Supports mixed DC- and AC-coupled configurations - 4 MPPTs, making it suitable for different roof orientations and shading conditions - Comes standard with Tesla Home, a fully integrated home energy management system

Tesla Energy

1,911,447 просмотров • 2 месяцев назад

Appreciate you Charles for having me on today! We covered: • $AMD emerging as the second source of the AI economy • My two favorite emerging market names for 2026: $MELI & $JMIA • $MU at the center of the next AI spend cycle as AI becomes memory-first • $NVDA laying out the blueprint for the operating system of the AI economy • $META & $AMZN winning in AI through distribution, data, and workflow control • $EOSE as a winner from AI data centers creating extreme load swings that long-duration zinc storage is built to handle

Appreciate you Charles for having me on today! We covered: • $AMD emerging as the second source of the AI economy • My two favorite emerging market names for 2026: $MELI & $JMIA • $MU at the center of the next AI spend cycle as AI becomes memory-first • $NVDA laying out the blueprint for the operating system of the AI economy • $META & $AMZN winning in AI through distribution, data, and workflow control • $EOSE as a winner from AI data centers creating extreme load swings that long-duration zinc storage is built to handle

Shay Boloor

250,124 просмотров • 6 месяцев назад

$NVDA CEO Jensen Huang is saying there’s no bubble because AI manufactures intelligence in real time which means every query consumes fresh compute & forces the system to scale its GPU base as usage grows. That is why demand for GPUs & power keeps accelerating & why this looks like a genuine industrial build-out rather than a bubble.

$NVDA CEO Jensen Huang is saying there’s no bubble because AI manufactures intelligence in real time which means every query consumes fresh compute & forces the system to scale its GPU base as usage grows. That is why demand for GPUs & power keeps accelerating & why this looks like a genuine industrial build-out rather than a bubble.

Shay Boloor

405,751 просмотров • 8 месяцев назад

Robots enter data centers! 💽 SeRo developed by NAVER LABS, is built for one of the most overlooked but critical tasks in a data center: managing servers in the IT warehouse. It can autonomously load and unload servers, identify their asset numbers, and log their lifecycle data. Physically, SeRo is designed tall to handle racks up to three meters high, maximizing storage density. SeRo also works as part of a larger system. It hands assets to GaRo, an autonomous transport robot, for seamless movement between warehouse and server room. More AI ops, more data centers, more data centers ops... Perfect market for robotics! 🦾

Robots enter data centers! 💽 SeRo developed by NAVER LABS, is built for one of the most overlooked but critical tasks in a data center: managing servers in the IT warehouse. It can autonomously load and unload servers, identify their asset numbers, and log their lifecycle data. Physically, SeRo is designed tall to handle racks up to three meters high, maximizing storage density. SeRo also works as part of a larger system. It hands assets to GaRo, an autonomous transport robot, for seamless movement between warehouse and server room. More AI ops, more data centers, more data centers ops... Perfect market for robotics! 🦾

Lukas Ziegler

30,311 просмотров • 10 месяцев назад

Dylan Patel just mapped out the most important investment theme in AI infrastructure (Save this). "In about two years, solar plus battery will be cheaper than gas." Every new NVIDIA Blackwell rack pulls 120 kilowatts, Rubin Ultra rack pulls 600 kilowatts and the next generation hits a megawatt. The US grid cannot keep up, interconnection queues now run five years in many markets so the entire industry is being forced to solve power from first principles. The solar thesis is already happening. BloombergNEF's 2026 LCOE report, covering 800+ financed projects across 50+ markets puts solar plus 4 hour battery storage at $57 per megawatt-hour. Combined cycle gas turbines hit $102 per megawatt hour, the highest on record, up 16% year over year. In California and parts of Texas, solar plus storage is already cheaper than gas for data center power today and solar panel costs are expected to drop another 30% by 2035. Getting power from the grid into the form chips actually require is an entire industry unto itself and NVIDIA just rewrote the rules. The 800 volt DC transition is the most important infrastructure shift that's happening right now. Today's data centers run on 48 volt DC power delivery, a single next-generation GPU pulls over 2,500 watts and at 48 volts, the current required to power a megawatt rack would melt the copper wiring. The investment thesis breaks into four layers and the first layer is power semiconductors, specifically silicon carbide and gallium nitride. At 800 volts, traditional silicon based IGBTs hit their physical limits. SiC and GaN devices are the mandatory replacement. Infineon estimates $175,000 of semiconductor content per megawatt of AI rack power, versus almost nothing today and by 2030, power semiconductor content per AI cabinet grows from $15,000 to $115,000+. The names here are Infineon ($IFNNY), ON Semiconductor ($ON), Wolfspeed ($WOLF), Navitas ($NVTS), and STMicroelectronics ($STM). The second layer is power management and conversion. Vertiv ($VRT) is NVIDIA's lead architectural collaborator for the 800V transition, building the hardware that converts grid AC to 800V DC and the DC to DC power shelves for ultra dense racks. Eaton ($ETN) and Monolithic Power Systems ($MPWR) round out this layer. The third layer is grid to site infrastructure, GE Vernova ($GEV) builds the heavy electrical equipment that connects utility power to the data center campus. Orders are running at twice the rate of shipments, the classic leading indicator of sustained multi year revenue growth. The fourth layer is behind the meter power generation like your bloom energy because grid interconnection queues run five years, hyperscalers are bypassing the grid entirely, building dedicated gas, solar and battery systems on site. Make sure to follow me Melvin for more opportunities across the AI supply chain.

Dylan Patel just mapped out the most important investment theme in AI infrastructure (Save this). "In about two years, solar plus battery will be cheaper than gas." Every new NVIDIA Blackwell rack pulls 120 kilowatts, Rubin Ultra rack pulls 600 kilowatts and the next generation hits a megawatt. The US grid cannot keep up, interconnection queues now run five years in many markets so the entire industry is being forced to solve power from first principles. The solar thesis is already happening. BloombergNEF's 2026 LCOE report, covering 800+ financed projects across 50+ markets puts solar plus 4 hour battery storage at $57 per megawatt-hour. Combined cycle gas turbines hit $102 per megawatt hour, the highest on record, up 16% year over year. In California and parts of Texas, solar plus storage is already cheaper than gas for data center power today and solar panel costs are expected to drop another 30% by 2035. Getting power from the grid into the form chips actually require is an entire industry unto itself and NVIDIA just rewrote the rules. The 800 volt DC transition is the most important infrastructure shift that's happening right now. Today's data centers run on 48 volt DC power delivery, a single next-generation GPU pulls over 2,500 watts and at 48 volts, the current required to power a megawatt rack would melt the copper wiring. The investment thesis breaks into four layers and the first layer is power semiconductors, specifically silicon carbide and gallium nitride. At 800 volts, traditional silicon based IGBTs hit their physical limits. SiC and GaN devices are the mandatory replacement. Infineon estimates $175,000 of semiconductor content per megawatt of AI rack power, versus almost nothing today and by 2030, power semiconductor content per AI cabinet grows from $15,000 to $115,000+. The names here are Infineon ($IFNNY), ON Semiconductor ($ON), Wolfspeed ($WOLF), Navitas ($NVTS), and STMicroelectronics ($STM). The second layer is power management and conversion. Vertiv ($VRT) is NVIDIA's lead architectural collaborator for the 800V transition, building the hardware that converts grid AC to 800V DC and the DC to DC power shelves for ultra dense racks. Eaton ($ETN) and Monolithic Power Systems ($MPWR) round out this layer. The third layer is grid to site infrastructure, GE Vernova ($GEV) builds the heavy electrical equipment that connects utility power to the data center campus. Orders are running at twice the rate of shipments, the classic leading indicator of sustained multi year revenue growth. The fourth layer is behind the meter power generation like your bloom energy because grid interconnection queues run five years, hyperscalers are bypassing the grid entirely, building dedicated gas, solar and battery systems on site. Make sure to follow me Melvin for more opportunities across the AI supply chain.

Melvin

104,139 просмотров • 7 дней назад

Jensen Huang just laid out the exact playbook for the next leg of the AI infrastructure boom. The future of data centers isn't where people live, it's moving to the most remote corners of the planet to tap into massive, under-utilized sources of sustainable energy. The real bottleneck isn't a lack of global energy; it's a geographic mismatch. The winning strategy is to build hyperscale compute infrastructure directly on top of stranded, off-grid power generation. "Train the models there. When they graduate, bring them back." A powerful insight into how the next generation of AI infrastructure will be built and scaled. Watch him break down the macro infrastructure thesis below: 👇

Jensen Huang just laid out the exact playbook for the next leg of the AI infrastructure boom. The future of data centers isn't where people live, it's moving to the most remote corners of the planet to tap into massive, under-utilized sources of sustainable energy. The real bottleneck isn't a lack of global energy; it's a geographic mismatch. The winning strategy is to build hyperscale compute infrastructure directly on top of stranded, off-grid power generation. "Train the models there. When they graduate, bring them back." A powerful insight into how the next generation of AI infrastructure will be built and scaled. Watch him break down the macro infrastructure thesis below: 👇

Leopold Stock Tracker

16,736 просмотров • 1 месяц назад

$IBM is having its worst day in nearly six decades after its CEO said customers redirected quarterly spending toward servers, storage and memory to secure supply-constrained infrastructure ahead of expected price increases. That comment is huge because it provides one of the clearest real-world examples yet of the AI infrastructure buildout reshaping enterprise technology budgets. Demand for compute, memory, networking, power, cooling and skilled labor is becoming so large that companies are being forced to reallocate capital across the rest of their businesses.

$IBM is having its worst day in nearly six decades after its CEO said customers redirected quarterly spending toward servers, storage and memory to secure supply-constrained infrastructure ahead of expected price increases. That comment is huge because it provides one of the clearest real-world examples yet of the AI infrastructure buildout reshaping enterprise technology budgets. Demand for compute, memory, networking, power, cooling and skilled labor is becoming so large that companies are being forced to reallocate capital across the rest of their businesses.

Shay Boloor

109,549 просмотров • 4 дней назад

CEO Rene Haas on why AI agents are spiking CPU demand: ▫️use >15x more tokens than humans ▫️a 1GW data centres now need 4x CPU cores (120m vs. 30m) for the AI agents AI agents are doing general asynchronous tasks (browse, spreadsheets) that are best-suited CPUs. So, 4x more CPUs per 1GW of GPUs…but the data centre’s power envelope is the same. Need energy-efficient CPU solutions, which is right down Arm’s lane of expertise (its ubiquitous mobile chips win on energy efficiency)….hence ARM’s recent AI CPU announcement.

CEO Rene Haas on why AI agents are spiking CPU demand: ▫️use >15x more tokens than humans ▫️a 1GW data centres now need 4x CPU cores (120m vs. 30m) for the AI agents AI agents are doing general asynchronous tasks (browse, spreadsheets) that are best-suited CPUs. So, 4x more CPUs per 1GW of GPUs…but the data centre’s power envelope is the same. Need energy-efficient CPU solutions, which is right down Arm’s lane of expertise (its ubiquitous mobile chips win on energy efficiency)….hence ARM’s recent AI CPU announcement.

Bearly AI

129,780 просмотров • 3 месяцев назад

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

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 просмотров • 1 год назад

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.

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 просмотров • 25 дней назад