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ICP Cloud Engines Will Be Immune to Infrastructure Hacks and Conflict Internet Computer (DFINITY Foundation) is preparing to roll out cloud engines to mitigate escalating physical and cyber threats against centralized data centers. ICP CEO states that cloud engines utilize a tamper-proof architecture that ensures hosted services remain operational... show more

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Dear ICP community, the Internet Computer has now been running strong for 5 years 👏👏👏 Here is a celebratory preview of ICP "cloud engines," the sovereign frontier cloud technology the network shall soon provide from Main points: — Cloud engines enable anyone to spin up their own sovereign frontier cloud. The technology involves an extraordinary inventive step, in which cloud is created from a mathematically secure network of nodes. The nodes run as part of the Internet Computer network ( but are selected and configured by the cloud engine's owner. — The frontier cloud provided by engines is strongly focused on enabling AI agents to build and update online applications and services for us. The world is changing fast, and nearly all new online apps and services are already being built with the help of AI, and thus cloud engines target the future of cloud. — Software hosted on cloud engines is tamperproof, which means that it is immune to infrastructure hacks, because it runs inside a mathematically secure network protocol, rather than on computers directly. This means that AI agents, and those building with them, don't need to have a security team in the loop, or to trust someone else's security team. This is crucial, because in the future, non technical people will demand the freedom to build with full automation — where they just need to issue instructions to AI about what to build, and don't need to worry about anything or anyone else. Of course, apps and services running on engines are also vastly safer from the new breed of hacker being enabled by frontier AI. (The cloud engines themselves are also "tamperproof." Even if a hacker gains physical access to some portion of a cloud engine's nodes, and can make arbitrary changes, the computations and data of the hosted apps and services cannot be corrupted or interrupted so long as the network's fault bounds aren't exceeded. The recent hack of Vercel, a major cloud platform, which gave hackers access to the apps it hosted, provides additional perspective on the importance of this advantage.) — Software hosted on cloud engines is guaranteed to run, so long as a sufficient number of the engine's nodes are running. This means that AI can build applications and services without the need to have a human systems admin team constantly tinkering with the underlying platform to keep it running, which is again crucial, because in the future, non technical people will expect the freedom to use AI to build without the support of others. — New frontier programming language technology, in the form of the Motoko language developed by Caffeine Labs, leverages seminal "orthogonal persistence" technology that unifies program logic and data to deliver further unlocks for AI (Motoko is the first computer language being developed that targets agents that are writing software rather than humans engineers per se). Nowadays, AI can build and update production apps at a prodigious rate, even at the speed of conversation. But it can also make mistakes, and there's a risk that an update it creates might be "lossy" in the sense it causes some transformed data to be lost. Again, in this new world, it's both undesirable and impractical for everyone to have to have a systems admin team on-hand to detect lossy updates and roll them back, but Motoko provides a solution: it can detect new software updates are lossy before they are applied, reducing potentially catastrophic errors by AI to harmless coding retries. — Software hosted on cloud engines is "serverless" but unlike traditional serverless software, directly it directly incorporates data through "orthogonal persistence." Another key purpose is simplify backend software logic and fuel the modeling power of AI by increasing abstraction (sorry for the technical language!!!). Put simply, this enables AI to produce more sophisticated backends, faster, and at dramatically lower costs, as measured by the number AI API tokens consumed during coding. (Tip for the technical: orthogonal persistence is a new paradigm where "the program is the database," and data lives inside program variables, which is possible because it's as if hosted software runs forever in persistent memory). — An expanding database of skills at shall make it possible to develop and directly deploy apps and services to your cloud engines directly from Claude Code, Perplexity, Codex and other AI platforms. Further, your account on can be connected, so that new apps and updates created through conversation automatically appear hosted from your cloud engine. In the future, R&D is going to be very seamless. You converse with AI, and your secure and unstoppable apps or services are created or updated. Cloud engines are designed to directly support this "self-writing cloud" future where we can work hands-free. — Tech sovereignty is becoming a huge issue worldwide, with governments and corporations seeking to create sovereign tech stacks owing to geopolitical tensions. Increasingly, people are realizing that tech provided by foreign nations can come with hidden backdoors and kills switches, from the base platform, right up through hosted apps and services. ICP technology is open source, and those building on ICP using AI own their own source code. When you have the source code, you can verify that there are no backdoors, and when you own the source code thanks to AI, you can update it at will, freeing you from vendor lock-in. But cloud engines take sovereignty much further... — You create a cloud engine by selecting the nodes that will be combined. You can choose the class of nodes used, and their number, but more importantly, you can choose who operates the nodes, and where they are located. Almost any configuration is possible, because the Internet Computer scales the security privileges afforded to hosted software within the network according to configuration (software hosted on cloud engines can directly interoperate with software on other engines and traditional subnets, but base restrictions are applied according to security rules). A cloud engine can be created within a region such as Europe, to comply with regs such as GDPR, or completely within a sovereign state like Switzerland or Pakistan. But cloud engines go further still... — Sovereignty is also about freedom from vendor lock-in. Cloud engines are essentially ICP (Internet Computer Protocol) network configurations, and this means the underlying compute nodes they combine can be swapped out without interrupting their hosted apps and services. This is a big deal. In addition, cloud engines now support nodes that are instances running on Big Tech's clouds, in addition to nodes that are dedicated specialized hardware, as per the Gen I and Gen II nodes that dominate the Internet Computer today. For example, it is possible to have an engine running across different AWS data centers, say, and then reconfigure the engine to run across a mixture of AWS, Google, Azure and Hetzner for even more resilience, without the users of hosted apps and services noticing a thing. That's true freedom. — Sovereign AI is becoming increasingly important too, and cloud engines allow special "AI nodes" to be added to them, so that hosted software can perform inference on hardware provisioned by the owner from a location the owner has selected. Even though the AI nodes are only accessible within the cloud engine, they can still benefit from the forthcoming Internet Intelligence Gateway (IG), which will make it possible to validate inference performed on key frontier open weights LLMs, even when the inference is performed on completely independent AI clouds. When the results of inference are received, this technology can verify that neither the prompt+context (input) nor the inference result (output) have been modified, and that the results were produced by the precise LLM expected. This ensures that AI clouds don't cheat by running inference on cheaper models than are being paid for, and bad actors aren't modifying the inputs or outputs to surreptitiously insert advertising into results, say, or change facts, or insert malware when code is being generated. What's super cool about this technology is the cost of the verification is scalable. A very valuable additional security can be achieved with only 1-2% of extra cost. — Scaling apps and services when they hit capacity limits is another thorny problem that cloud engines help the world address. Engines make scaling possible without rewriting or reconfiguring software. The query workload capacity of hosted software can be horizontally scaled simply by adding new nodes to an engine, and nodes can also be added in geographical proximity to demand. Meanwhile, update workload capacity can first be scaled-up by swapping an engine's nodes out for the next class up, and then when no larger class of node is available, horizontally scaled-out by "splitting" the engine into two, which doubles available capacity. (Technical tip: horizontally scaling update capacity by splitting engines requires multi-canister architectures). — For those who have been following how Caffeine builds apps that can efficiently store large numbers of files, I should mention that apps built on cloud engines will also support the new ICP Blob Storage cloud network (since cloud engines currently have up to about 3 TB of memory, which apps storing large amounts of files can easily exceed). We are also working on allowing blob storage nodes to be added to cloud engines, to enable sovereign mass blob storage within an engine, similarly to how AI nodes can be added currently. — Lastly, but certainly not least, I should mention that cloud engines are multi-blockchain capable, and ready for digital assets, thanks to the clever math at their core. For example, an e-commerce service built on a cloud engine can securely accept and custody stablecoin payments, or a multi-chain DEX could be hosted. Further, engines can support software autonomy (software orchestrated and controlled by other autonomous software, in a decentralized way) and can themselves be orchestrated by SNS technology, and thus run autonomously too. Today, though, the focus is on *mainstream* cloud. This year, the cloud industry will generate approximately one trillion dollars in revenue. That number is already huge, but is expected to grow to two trillion dollars by 2030. After years of continuous development, which have seen more than $500m spent on R&D, the Internet Computer network is now tacking directly toward this mainstream cloud market with cloud engine technology. In their first version, cloud engines are not meant to be a cloud panacea. For example, currently they are not ideal for working with big data. You should use something like DataBricks for that. Cloud engines are carefully targeted at enabling AI to produce traditional online applications and services, including SaaS, in a safer and more productive way, which represents a new market segment with tremendous potential. Of course, DFINITY will continue to work relentlessly to push forward ICP's capabilities, so expect further developments. It's worth mentioning that this cloud segment isn't just about creating new apps and services using AI, it's also about replacing legacy systems and apps built on super expensive SaaS services. Caffeine Labs is working to produce technology (Caffeine Snorkel) that can study an enterprise's legacy systems and app built on SaaS, create replacement systems and apps, and migrate the data, while supporting key stakeholders through the process over email and chat, with full automation. Thus the legacy systems and SaaS markets shall also be addressed by cloud engines. Zooming out, and reasoning in a more metaphysical way, we believe, as we always have, that there is room for a new kind of cloud created by mathematical networks, that provides seminal advances in the fields of security and resilience, as well as true sovereignty and freedom from lock-in. That this same technology, with the help of additional technologies like orthogonal persistence and Motoko, enables AI to build for us without the need for so much oversight, and to create more backend sophistication while consuming fewer AI API tokens, enables ICP to bring game-changing advances to the world. Cloud engines will work synergistically with the Intelligence Gateway, which will enable apps and services running on engines to seamlessly leverage AI, wherever that AI is running, while providing verifiability at extremely low cost for open weights frontier models. We believe that cloud engines represent an inflection point in the storied history of the Internet Computer project, and I'm very proud to be sharing the details with you on the network's fifth birthday 💪 I'll be back with more news soon!!

Dear ICP community, the Internet Computer has now been running strong for 5 years 👏👏👏 Here is a celebratory preview of ICP "cloud engines," the sovereign frontier cloud technology the network shall soon provide from Main points: — Cloud engines enable anyone to spin up their own sovereign frontier cloud. The technology involves an extraordinary inventive step, in which cloud is created from a mathematically secure network of nodes. The nodes run as part of the Internet Computer network ( but are selected and configured by the cloud engine's owner. — The frontier cloud provided by engines is strongly focused on enabling AI agents to build and update online applications and services for us. The world is changing fast, and nearly all new online apps and services are already being built with the help of AI, and thus cloud engines target the future of cloud. — Software hosted on cloud engines is tamperproof, which means that it is immune to infrastructure hacks, because it runs inside a mathematically secure network protocol, rather than on computers directly. This means that AI agents, and those building with them, don't need to have a security team in the loop, or to trust someone else's security team. This is crucial, because in the future, non technical people will demand the freedom to build with full automation — where they just need to issue instructions to AI about what to build, and don't need to worry about anything or anyone else. Of course, apps and services running on engines are also vastly safer from the new breed of hacker being enabled by frontier AI. (The cloud engines themselves are also "tamperproof." Even if a hacker gains physical access to some portion of a cloud engine's nodes, and can make arbitrary changes, the computations and data of the hosted apps and services cannot be corrupted or interrupted so long as the network's fault bounds aren't exceeded. The recent hack of Vercel, a major cloud platform, which gave hackers access to the apps it hosted, provides additional perspective on the importance of this advantage.) — Software hosted on cloud engines is guaranteed to run, so long as a sufficient number of the engine's nodes are running. This means that AI can build applications and services without the need to have a human systems admin team constantly tinkering with the underlying platform to keep it running, which is again crucial, because in the future, non technical people will expect the freedom to use AI to build without the support of others. — New frontier programming language technology, in the form of the Motoko language developed by Caffeine Labs, leverages seminal "orthogonal persistence" technology that unifies program logic and data to deliver further unlocks for AI (Motoko is the first computer language being developed that targets agents that are writing software rather than humans engineers per se). Nowadays, AI can build and update production apps at a prodigious rate, even at the speed of conversation. But it can also make mistakes, and there's a risk that an update it creates might be "lossy" in the sense it causes some transformed data to be lost. Again, in this new world, it's both undesirable and impractical for everyone to have to have a systems admin team on-hand to detect lossy updates and roll them back, but Motoko provides a solution: it can detect new software updates are lossy before they are applied, reducing potentially catastrophic errors by AI to harmless coding retries. — Software hosted on cloud engines is "serverless" but unlike traditional serverless software, directly it directly incorporates data through "orthogonal persistence." Another key purpose is simplify backend software logic and fuel the modeling power of AI by increasing abstraction (sorry for the technical language!!!). Put simply, this enables AI to produce more sophisticated backends, faster, and at dramatically lower costs, as measured by the number AI API tokens consumed during coding. (Tip for the technical: orthogonal persistence is a new paradigm where "the program is the database," and data lives inside program variables, which is possible because it's as if hosted software runs forever in persistent memory). — An expanding database of skills at shall make it possible to develop and directly deploy apps and services to your cloud engines directly from Claude Code, Perplexity, Codex and other AI platforms. Further, your account on can be connected, so that new apps and updates created through conversation automatically appear hosted from your cloud engine. In the future, R&D is going to be very seamless. You converse with AI, and your secure and unstoppable apps or services are created or updated. Cloud engines are designed to directly support this "self-writing cloud" future where we can work hands-free. — Tech sovereignty is becoming a huge issue worldwide, with governments and corporations seeking to create sovereign tech stacks owing to geopolitical tensions. Increasingly, people are realizing that tech provided by foreign nations can come with hidden backdoors and kills switches, from the base platform, right up through hosted apps and services. ICP technology is open source, and those building on ICP using AI own their own source code. When you have the source code, you can verify that there are no backdoors, and when you own the source code thanks to AI, you can update it at will, freeing you from vendor lock-in. But cloud engines take sovereignty much further... — You create a cloud engine by selecting the nodes that will be combined. You can choose the class of nodes used, and their number, but more importantly, you can choose who operates the nodes, and where they are located. Almost any configuration is possible, because the Internet Computer scales the security privileges afforded to hosted software within the network according to configuration (software hosted on cloud engines can directly interoperate with software on other engines and traditional subnets, but base restrictions are applied according to security rules). A cloud engine can be created within a region such as Europe, to comply with regs such as GDPR, or completely within a sovereign state like Switzerland or Pakistan. But cloud engines go further still... — Sovereignty is also about freedom from vendor lock-in. Cloud engines are essentially ICP (Internet Computer Protocol) network configurations, and this means the underlying compute nodes they combine can be swapped out without interrupting their hosted apps and services. This is a big deal. In addition, cloud engines now support nodes that are instances running on Big Tech's clouds, in addition to nodes that are dedicated specialized hardware, as per the Gen I and Gen II nodes that dominate the Internet Computer today. For example, it is possible to have an engine running across different AWS data centers, say, and then reconfigure the engine to run across a mixture of AWS, Google, Azure and Hetzner for even more resilience, without the users of hosted apps and services noticing a thing. That's true freedom. — Sovereign AI is becoming increasingly important too, and cloud engines allow special "AI nodes" to be added to them, so that hosted software can perform inference on hardware provisioned by the owner from a location the owner has selected. Even though the AI nodes are only accessible within the cloud engine, they can still benefit from the forthcoming Internet Intelligence Gateway (IG), which will make it possible to validate inference performed on key frontier open weights LLMs, even when the inference is performed on completely independent AI clouds. When the results of inference are received, this technology can verify that neither the prompt+context (input) nor the inference result (output) have been modified, and that the results were produced by the precise LLM expected. This ensures that AI clouds don't cheat by running inference on cheaper models than are being paid for, and bad actors aren't modifying the inputs or outputs to surreptitiously insert advertising into results, say, or change facts, or insert malware when code is being generated. What's super cool about this technology is the cost of the verification is scalable. A very valuable additional security can be achieved with only 1-2% of extra cost. — Scaling apps and services when they hit capacity limits is another thorny problem that cloud engines help the world address. Engines make scaling possible without rewriting or reconfiguring software. The query workload capacity of hosted software can be horizontally scaled simply by adding new nodes to an engine, and nodes can also be added in geographical proximity to demand. Meanwhile, update workload capacity can first be scaled-up by swapping an engine's nodes out for the next class up, and then when no larger class of node is available, horizontally scaled-out by "splitting" the engine into two, which doubles available capacity. (Technical tip: horizontally scaling update capacity by splitting engines requires multi-canister architectures). — For those who have been following how Caffeine builds apps that can efficiently store large numbers of files, I should mention that apps built on cloud engines will also support the new ICP Blob Storage cloud network (since cloud engines currently have up to about 3 TB of memory, which apps storing large amounts of files can easily exceed). We are also working on allowing blob storage nodes to be added to cloud engines, to enable sovereign mass blob storage within an engine, similarly to how AI nodes can be added currently. — Lastly, but certainly not least, I should mention that cloud engines are multi-blockchain capable, and ready for digital assets, thanks to the clever math at their core. For example, an e-commerce service built on a cloud engine can securely accept and custody stablecoin payments, or a multi-chain DEX could be hosted. Further, engines can support software autonomy (software orchestrated and controlled by other autonomous software, in a decentralized way) and can themselves be orchestrated by SNS technology, and thus run autonomously too. Today, though, the focus is on mainstream cloud. This year, the cloud industry will generate approximately one trillion dollars in revenue. That number is already huge, but is expected to grow to two trillion dollars by 2030. After years of continuous development, which have seen more than $500m spent on R&D, the Internet Computer network is now tacking directly toward this mainstream cloud market with cloud engine technology. In their first version, cloud engines are not meant to be a cloud panacea. For example, currently they are not ideal for working with big data. You should use something like DataBricks for that. Cloud engines are carefully targeted at enabling AI to produce traditional online applications and services, including SaaS, in a safer and more productive way, which represents a new market segment with tremendous potential. Of course, DFINITY will continue to work relentlessly to push forward ICP's capabilities, so expect further developments. It's worth mentioning that this cloud segment isn't just about creating new apps and services using AI, it's also about replacing legacy systems and apps built on super expensive SaaS services. Caffeine Labs is working to produce technology (Caffeine Snorkel) that can study an enterprise's legacy systems and app built on SaaS, create replacement systems and apps, and migrate the data, while supporting key stakeholders through the process over email and chat, with full automation. Thus the legacy systems and SaaS markets shall also be addressed by cloud engines. Zooming out, and reasoning in a more metaphysical way, we believe, as we always have, that there is room for a new kind of cloud created by mathematical networks, that provides seminal advances in the fields of security and resilience, as well as true sovereignty and freedom from lock-in. That this same technology, with the help of additional technologies like orthogonal persistence and Motoko, enables AI to build for us without the need for so much oversight, and to create more backend sophistication while consuming fewer AI API tokens, enables ICP to bring game-changing advances to the world. Cloud engines will work synergistically with the Intelligence Gateway, which will enable apps and services running on engines to seamlessly leverage AI, wherever that AI is running, while providing verifiability at extremely low cost for open weights frontier models. We believe that cloud engines represent an inflection point in the storied history of the Internet Computer project, and I'm very proud to be sharing the details with you on the network's fifth birthday 💪 I'll be back with more news soon!!

dom | icp

268,830 просмотров • 2 месяцев назад

I ask myself, “What do I buy that is really the picks and shovels? And what do I buy that is actually a direct ownership of the tech equivalent to, let's say a stable coin or Bitcoin itself?" My conclusion has been if I wanna play the long-term, the next five years or even 10 years in AI, I need to own data centers. I need to own real estate where data centers are built. I need to own power contracts that power the data centers. I've seen this movie so many times before, once you convinced as an investor that this is gonna be here for a while.

I ask myself, “What do I buy that is really the picks and shovels? And what do I buy that is actually a direct ownership of the tech equivalent to, let's say a stable coin or Bitcoin itself?" My conclusion has been if I wanna play the long-term, the next five years or even 10 years in AI, I need to own data centers. I need to own real estate where data centers are built. I need to own power contracts that power the data centers. I've seen this movie so many times before, once you convinced as an investor that this is gonna be here for a while.

Kevin O'Leary aka Mr. Wonderful

45,121 просмотров • 11 месяцев назад

Maine is set to implement a full statewide temporary BAN on all Data Centers More than a dozen other states are also considering this same ban on Data Centers too “The ban would halt construction until November, 2027. That would give a newly created council time to review and suggest guidelines to ensure data centers don't do things like lead to skyrocketing energy prices and water usage, which are some concerns for supporters of this measure. — The bill is expected to pass the State Senate as soon as today with bipartisan support. It will then be headed to Governor Janet Mills for her signature or her veto. Now, Mills did want an exemption for certain sites where data centers are already planned, but lawmakers voted down an amendment to make that change”

Maine is set to implement a full statewide temporary BAN on all Data Centers More than a dozen other states are also considering this same ban on Data Centers too “The ban would halt construction until November, 2027. That would give a newly created council time to review and suggest guidelines to ensure data centers don't do things like lead to skyrocketing energy prices and water usage, which are some concerns for supporters of this measure. — The bill is expected to pass the State Senate as soon as today with bipartisan support. It will then be headed to Governor Janet Mills for her signature or her veto. Now, Mills did want an exemption for certain sites where data centers are already planned, but lawmakers voted down an amendment to make that change”

Wall Street Apes

32,327 просмотров • 3 месяцев назад

Georgia is basically turning into one large data center Get ready for this, there is no legal obligation for data centers to disclose how much water they will be using - Georgia currently has about 162 data centers already - They have an additional 141 new data centers planned - Combined these data centers will use 12+ GW or more of power, this is equivalent to the usage of 10 MILLION homes - Combined water usage estimate of 35+ billion gallons per year or higher Absolutely insane There is no comprehensive federal requirement for data centers to publicly report detailed water usage. A bill was introduced called “the Data Center Water and Energy Transparency Act” to mandate reporting of energy and water consumption to states and the EPA This is an issue, here’s one example The Quality Technology Services data center in Fayette County used 29–30 million gallons of water went unmetered and unbilled for months without initial detection. Residents complained about low pressure during drought conditions. The company later paid retroactively $150,000 but faced no fines

Georgia is basically turning into one large data center Get ready for this, there is no legal obligation for data centers to disclose how much water they will be using - Georgia currently has about 162 data centers already - They have an additional 141 new data centers planned - Combined these data centers will use 12+ GW or more of power, this is equivalent to the usage of 10 MILLION homes - Combined water usage estimate of 35+ billion gallons per year or higher Absolutely insane There is no comprehensive federal requirement for data centers to publicly report detailed water usage. A bill was introduced called “the Data Center Water and Energy Transparency Act” to mandate reporting of energy and water consumption to states and the EPA This is an issue, here’s one example The Quality Technology Services data center in Fayette County used 29–30 million gallons of water went unmetered and unbilled for months without initial detection. Residents complained about low pressure during drought conditions. The company later paid retroactively $150,000 but faced no fines

Wall Street Apes

147,241 просмотров • 2 месяцев назад

In the next 15 years, data centers are expected to add an additional $160 billion to grid costs in the US Estimate say electricity rates for average households will spike by as much as 70% Data centers are projected to triple their share of US electricity demand in the next few years The main driver is the explosive growth of data centers built by Big Tech companies like Amazon, Meta, Microsoft, Google, OpenAI and more to power artificial intelligence Places like Northern Virginia already has over 200 data centers with massive new ones planned. Utilities are striking secret proprietary deals with Big Tech companies. These are hidden behind NDAs that shift much of the infrastructure costs onto regular residential customers Just in the PJM energy market of 13 states covering 65 million people, data centers were responsible for 63% of last year’s record 800% spike in capacity prices (This is INSANE) Residential customers in places like Virginia and Louisiana are being forced to subsidize billions in new power plants and grid upgrades for data centers. An Examples of this is in Louisiana, Meta’s data center deal leaves the public potentially on the hook for half or more of a $3–4 billion power plant Again, without major policy changes, average household electricity bills could rise by up to 70% over the next 15 years due to data center demand. There is only one real way we can stop this, we must create a separate customer class for data centers Maryland and Oregon have already passed laws doing this Forces data centers to pay for the specific infrastructure they need instead of spreading the costs to everyone else. More states need to do the same Ban secret sweetheart deals Require full public disclosure of all contracts between utilities and Big Tech Prohibit deals where data centers pay below the actual cost of service Make data centers pay the full cost of new power plants and grid upgrades Change regulations so utilities cannot socialize the cost of data-center-driven infrastructure to residential and small business ratepayers This needs to be done immediately

In the next 15 years, data centers are expected to add an additional $160 billion to grid costs in the US Estimate say electricity rates for average households will spike by as much as 70% Data centers are projected to triple their share of US electricity demand in the next few years The main driver is the explosive growth of data centers built by Big Tech companies like Amazon, Meta, Microsoft, Google, OpenAI and more to power artificial intelligence Places like Northern Virginia already has over 200 data centers with massive new ones planned. Utilities are striking secret proprietary deals with Big Tech companies. These are hidden behind NDAs that shift much of the infrastructure costs onto regular residential customers Just in the PJM energy market of 13 states covering 65 million people, data centers were responsible for 63% of last year’s record 800% spike in capacity prices (This is INSANE) Residential customers in places like Virginia and Louisiana are being forced to subsidize billions in new power plants and grid upgrades for data centers. An Examples of this is in Louisiana, Meta’s data center deal leaves the public potentially on the hook for half or more of a $3–4 billion power plant Again, without major policy changes, average household electricity bills could rise by up to 70% over the next 15 years due to data center demand. There is only one real way we can stop this, we must create a separate customer class for data centers Maryland and Oregon have already passed laws doing this Forces data centers to pay for the specific infrastructure they need instead of spreading the costs to everyone else. More states need to do the same Ban secret sweetheart deals Require full public disclosure of all contracts between utilities and Big Tech Prohibit deals where data centers pay below the actual cost of service Make data centers pay the full cost of new power plants and grid upgrades Change regulations so utilities cannot socialize the cost of data-center-driven infrastructure to residential and small business ratepayers This needs to be done immediately

Wall Street Apes

57,720 просмотров • 1 месяц назад

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 просмотров • 6 месяцев назад

I got update from Econet's Deputy CEO Roy Chimanikire on their new Industrial Park. Key features of this will include enhanced power and a major data center. This is not just infrastructure. It is the foundation for an AI ready Zimbabwe. Reliable power + robust data centers = the engine for AI innovation.This strategic private investment aligns with our national vision.We need to continue building the backbone for a smarter, data driven future. Econet's new Industrial Park is a game changer. It is the critical infrastructure needed to fuel AI adoption and innovation in Zimbabwe. A strategic leap forward for our digital economy. #DigitalizeZimbabwe #AI @EconetWirelessZW

I got update from Econet's Deputy CEO Roy Chimanikire on their new Industrial Park. Key features of this will include enhanced power and a major data center. This is not just infrastructure. It is the foundation for an AI ready Zimbabwe. Reliable power + robust data centers = the engine for AI innovation.This strategic private investment aligns with our national vision.We need to continue building the backbone for a smarter, data driven future. Econet's new Industrial Park is a game changer. It is the critical infrastructure needed to fuel AI adoption and innovation in Zimbabwe. A strategic leap forward for our digital economy. #DigitalizeZimbabwe #AI @EconetWirelessZW

Hon Tatenda.A. Mavetera

19,402 просмотров • 6 месяцев назад

Could $ICP & $DAG Power the Future of X? DFINITY Foundation was proposed as a decentralized infrastructure solution for X, offering dedicated subnets, enhanced security and on-chain X token integration Combined with Starlink’s satellite internet, this setup aimed to create a scalable, censorship-resistant, and globally accessible platform. Internet Computer is now a cloud service provider (CSP) for National DigiFoundry (NDF) NDF’s Space Working Group (SWG)—built on Constellation Network Hypergraph (HGTP)—is already proving how blockchain can power secure, AI-driven applications for NASA, the Space Force, and the commercial space industry In the audio clip, Kevin Jackson from the National DigiFoundry describes how they will be securing data for the Space Development Agency for all low-Earth orbit satellites If NDF is already deploying decentralized cloud infrastructure, why shouldn’t X leverage the same battle-tested frameworks for: ✅ On-Chain X Tokens → Feeless payments, tips & rewards ✅ Censorship-Resistant Hosting → Subnets & HGTP for tamper-proof data storage ✅ AI Model Integrity → Secure moderation & algorithmic transparency ✅ Starlink-Powered Transactions → Seamless payments & data access without banking roadblocks X has a choice: follow legacy models or lead the Web3 revolution

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Could $ICP & $DAG Power the Future of X? DFINITY Foundation was proposed as a decentralized infrastructure solution for X, offering dedicated subnets, enhanced security and on-chain X token integration Combined with Starlink’s satellite internet, this setup aimed to create a scalable, censorship-resistant, and globally accessible platform. Internet Computer is now a cloud service provider (CSP) for National DigiFoundry (NDF) NDF’s Space Working Group (SWG)—built on Constellation Network Hypergraph (HGTP)—is already proving how blockchain can power secure, AI-driven applications for NASA, the Space Force, and the commercial space industry In the audio clip, Kevin Jackson from the National DigiFoundry describes how they will be securing data for the Space Development Agency for all low-Earth orbit satellites If NDF is already deploying decentralized cloud infrastructure, why shouldn’t X leverage the same battle-tested frameworks for: ✅ On-Chain X Tokens → Feeless payments, tips & rewards ✅ Censorship-Resistant Hosting → Subnets & HGTP for tamper-proof data storage ✅ AI Model Integrity → Secure moderation & algorithmic transparency ✅ Starlink-Powered Transactions → Seamless payments & data access without banking roadblocks X has a choice: follow legacy models or lead the Web3 revolution

Dagnum P.I.

32,431 просмотров • 1 год назад

I made this video back in January based on the research I was doing last year to tell everyone that all Nuclear Powered AI Data Centers would be coming, and that they would all roll into a "Queen Bee" along with Global Satellite Connections, a Global "Cloud" of interconnected Cloud Servers, AI, Cryptocurrency, and more. The "Queen Bee" is shaping up to just be Palantir. I believe that once all of these systems are integrated and operating as desired, that will be the "Third Temple".

I made this video back in January based on the research I was doing last year to tell everyone that all Nuclear Powered AI Data Centers would be coming, and that they would all roll into a "Queen Bee" along with Global Satellite Connections, a Global "Cloud" of interconnected Cloud Servers, AI, Cryptocurrency, and more. The "Queen Bee" is shaping up to just be Palantir. I believe that once all of these systems are integrated and operating as desired, that will be the "Third Temple".

7SEES

43,615 просмотров • 1 год назад

One of the biggest Driving Forces in the Future for Jobs, are Data Centers. They are big, strong, bold, and Money Machines for the State in which they are built. Governor Kathy Hochul, for political reasons, has terminated all Data Centers being built, or to be built, in New York State. These Companies are now being sought in Alabama, Florida, Texas, Arizona, and many other States. Both the Taxes and the Jobs amount to LIQUID GOLD! New York State has made a terrible decision. All of this Income, and other Benefits, will be going to Red States, and some Blue, where Data Centers are sought as Cash Cows, with Lower Taxes and Record Setting Jobs. They must pay for their own Water and Power, and any leftover goes back to the State and local Community. Data Centers are tremendous WINS for the States and Communities that are lucky enough to get them. New York should change its Policy, IMMEDIATELY. The Radical Left Dumocrats must not be allowed to cause us to lose Data Centers, AI, and all of this incredible new Technology, to China, and other countries! President DONALD J. TRUMP ( TS: Jul 15 2026, 12:39 PM ET )‍‌‍‍‌‍‍‍‍‍‌‌‍‌‌‌‍‌‌‌‍‍‍

One of the biggest Driving Forces in the Future for Jobs, are Data Centers. They are big, strong, bold, and Money Machines for the State in which they are built. Governor Kathy Hochul, for political reasons, has terminated all Data Centers being built, or to be built, in New York State. These Companies are now being sought in Alabama, Florida, Texas, Arizona, and many other States. Both the Taxes and the Jobs amount to LIQUID GOLD! New York State has made a terrible decision. All of this Income, and other Benefits, will be going to Red States, and some Blue, where Data Centers are sought as Cash Cows, with Lower Taxes and Record Setting Jobs. They must pay for their own Water and Power, and any leftover goes back to the State and local Community. Data Centers are tremendous WINS for the States and Communities that are lucky enough to get them. New York should change its Policy, IMMEDIATELY. The Radical Left Dumocrats must not be allowed to cause us to lose Data Centers, AI, and all of this incredible new Technology, to China, and other countries! President DONALD J. TRUMP ( TS: Jul 15 2026, 12:39 PM ET )‍‌‍‍‌‍‍‍‍‍‌‌‍‌‌‌‍‌‌‌‍‍‍

Commentary Donald J. Trump Truth Social Posts On X

159,832 просмотров • 12 дней назад

MoistCr1TiKaL comes out strongly against data centers in recent video and ponders if they're making people sicker due to hoarding clean water "AI data centers are actually the boogeyman..a scourge on this planet and a stain on civilized society..no normal ppl with functioning frontal lobes want data centers in their community, it is bad for them" "I've been getting conspiratorial..I was reading something that someone was sharing about like when a AI data center came through, and the impact it had on their water, cause that's a very common thing" "I'm not fully bought into it..but it's an interesting theory..what if the reason there's been seemingly so much more sickness, like it feels like ppl are getting sick more frequently now and a wide variety of illnesses just seem more common..what if AI data centers are hoarding all of the clean water..what if all the clean water is being diverted to the AI data centers and the normal civilians are just getting the sludge runoff..I don't think it's out of the realm of possibility..they are evil enough to do that" (Via penguinz0 on YT)

MoistCr1TiKaL comes out strongly against data centers in recent video and ponders if they're making people sicker due to hoarding clean water "AI data centers are actually the boogeyman..a scourge on this planet and a stain on civilized society..no normal ppl with functioning frontal lobes want data centers in their community, it is bad for them" "I've been getting conspiratorial..I was reading something that someone was sharing about like when a AI data center came through, and the impact it had on their water, cause that's a very common thing" "I'm not fully bought into it..but it's an interesting theory..what if the reason there's been seemingly so much more sickness, like it feels like ppl are getting sick more frequently now and a wide variety of illnesses just seem more common..what if AI data centers are hoarding all of the clean water..what if all the clean water is being diverted to the AI data centers and the normal civilians are just getting the sludge runoff..I don't think it's out of the realm of possibility..they are evil enough to do that" (Via penguinz0 on YT)

yeet

3,008,892 просмотров • 13 дней назад

Billion-Dollar Data Centers Are Taking Over the World | Lauren Goode, WIRED When Sam Altman said one year ago that OpenAI’s Roman Empire is the actual Roman Empire, he wasn’t kidding. In the same way that the Romans gradually amassed an empire of land spanning three continents and one-ninth of the Earth’s circumference, the CEO and his cohort are now dotting the planet with their own latifundia—not agricultural estates, but AI data centers. Tech executives like Altman, Nvidia CEO Jensen Huang, Microsoft CEO Satya Nadella, and Oracle cofounder Larry Ellison are fully bought in to the idea that the future of the American (and possibly global) economy are these new warehouses stocked with IT infrastructure. But data centers, of course, aren’t actually new. In the earliest days of computing there were giant power-sucking mainframes in climate-controlled rooms, with co-ax cables moving information from the mainframe to a terminal computer. Then the consumer internet boom of the late 1990s spawned a new era of infrastructure. Massive buildings began popping up in the backyard of Washington, DC, with racks and racks of computers that stored and processed data for tech companies. A decade later, “the cloud” became the squishy infrastructure of the internet. Storage got cheaper. Some companies, like Amazon, capitalized on this. Giant data centers continued to proliferate, but instead of a tech company using some combination of on-premise servers and rented data center racks, they offloaded their computing needs to a bunch of virtualized environments. (“What is the cloud?” a perfectly intelligent family member asked me in the mid-2010s, “and why am I paying for 17 different subscriptions to it?”) All the while tech companies were hoovering up petabytes of data, data that people willingly shared online, in enterprise workspaces, and through mobile apps. Firms began finding new ways to mine and structure this “Big Data,” and promised that it would change lives. In many ways, it did. You had to know where this was going. Now the tech industry is in the fever-dream days of generative AI, which requires new levels of computing resources. Big Data is tired; big data centers are here, and wired—for AI. Faster, more efficient chips are needed to power AI data centers, and chipmakers like Nvidia and AMD have been jumping up and down on the proverbial couch, proclaiming their love for AI. The industry has entered an unprecedented era of capital investments in AI infrastructure, tilting the US into positive GDP territory. These are massive, swirling deals that might as well be cocktail party handshakes, greased with gigawatts and exuberance, while the rest of us try to track real contracts and dollars. OpenAI, Microsoft, Nvidia, Oracle, and SoftBank have struck some of the biggest deals. This year an earlier supercomputing project between OpenAI and Microsoft, called Stargate, became the vehicle for a massive AI infrastructure project in the US. (President Donald Trump called it the largest AI infrastructure project in history, because of course he did, but that may not have been hyperbolic.) Altman, Ellison, and SoftBank CEO Masayoshi Son were all in on the deal, pledging $100 billion to start, with plans to invest up to $500 billion into Stargate in the coming years. Nvidia GPUs would be deployed. Later, in July, OpenAI and Oracle announced an additional Stargate partnership—SoftBank curiously absent—measured in gigawatts of capacity (4.5) and expected job creation (around 100,000). Microsoft, Amazon, and Meta have also shared plans for multibillion-dollar data projects. Microsoft said at the start of 2025 that it was on track to invest “approximately $80 billion to build out AI-enabled data centers to train AI models and deploy AI and cloud-based applications around the world.” Then, in September, Nvidia said it would invest up to $100 billion in OpenAI, provided that OpenAI made good on a deal to use up to 10 gigawatts of Nvidia’s systems for OpenAI’s infrastructure plans, which means essentially that OpenAI has to pay Nvidia in order to get paid by Nvidia. The following month AMD said it would give OpenAI as much as 10 percent of the chip company if OpenAI purchased and deployed up to 6 gigawatts of AMD GPUs between now and 2030. It’s the circular nature of these investments that have the general public, and bearish analysts, wondering if we’re headed for an AI bubble burst. What’s clear is that the near-term downstream effects of these data center build-outs are real. The energy, resource, and labor demands of AI infrastructure are enormous. By some estimates, worldwide AI energy demand is set to surpass demand from bitcoin mining by the end of this year, WIRED has reported. The processors in data centers run hot and need to be cooled, so big tech companies are pulling from municipal water supplies to make that happen—and aren’t always disclosing how much water they’re using. Local wells are running dry or seem unsafe to drink from. Residents who live near data center construction sites are noting that traffic delays, and in some cases car crashes, are increasing. One corner of Richland Parish, Louisiana, home of Meta’s $27 billion Hyperion data center, has seen a 600 percent spike in vehicle crashes this year. Major proponents of AI seem to suggest that all of this will be worth it. Few top tech executives will publicly entertain the notion that this might be an overshoot, either ecologically or economically. “Emphatically … no,” Lisa Su, the chief executive of AMD, said earlier this month when asked if the AI froth has runneth over. Su, like other execs, cited overwhelming demand for AI as justification for these enormous capital expenditures. Demand from whom? Harder to pin down. In their mind, it’s everyone. All of us. The 800 million people who use ChatGPT on a weekly basis. The evolution from those 1990s data centers to the 2000s era of cloud computing to new AI data centers wasn’t just one continuum. The world has concurrently moved from the tiny internet to the big internet to the AI internet, and realistically speaking, there’s no going back. Generative AI is out of the bottle. The Sams and Jensens and Larrys and Lisas of the world aren’t wrong about this. It doesn’t mean they aren’t wrong about the math, though. About their economic predictions. Or their ideas about AI-powered productivity and the labor market. Or the availability of natural and material resources for these data centers. Or who will come once they build them. Or the timing of it all. Even Rome eventually collapsed.

Billion-Dollar Data Centers Are Taking Over the World | Lauren Goode, WIRED When Sam Altman said one year ago that OpenAI’s Roman Empire is the actual Roman Empire, he wasn’t kidding. In the same way that the Romans gradually amassed an empire of land spanning three continents and one-ninth of the Earth’s circumference, the CEO and his cohort are now dotting the planet with their own latifundia—not agricultural estates, but AI data centers. Tech executives like Altman, Nvidia CEO Jensen Huang, Microsoft CEO Satya Nadella, and Oracle cofounder Larry Ellison are fully bought in to the idea that the future of the American (and possibly global) economy are these new warehouses stocked with IT infrastructure. But data centers, of course, aren’t actually new. In the earliest days of computing there were giant power-sucking mainframes in climate-controlled rooms, with co-ax cables moving information from the mainframe to a terminal computer. Then the consumer internet boom of the late 1990s spawned a new era of infrastructure. Massive buildings began popping up in the backyard of Washington, DC, with racks and racks of computers that stored and processed data for tech companies. A decade later, “the cloud” became the squishy infrastructure of the internet. Storage got cheaper. Some companies, like Amazon, capitalized on this. Giant data centers continued to proliferate, but instead of a tech company using some combination of on-premise servers and rented data center racks, they offloaded their computing needs to a bunch of virtualized environments. (“What is the cloud?” a perfectly intelligent family member asked me in the mid-2010s, “and why am I paying for 17 different subscriptions to it?”) All the while tech companies were hoovering up petabytes of data, data that people willingly shared online, in enterprise workspaces, and through mobile apps. Firms began finding new ways to mine and structure this “Big Data,” and promised that it would change lives. In many ways, it did. You had to know where this was going. Now the tech industry is in the fever-dream days of generative AI, which requires new levels of computing resources. Big Data is tired; big data centers are here, and wired—for AI. Faster, more efficient chips are needed to power AI data centers, and chipmakers like Nvidia and AMD have been jumping up and down on the proverbial couch, proclaiming their love for AI. The industry has entered an unprecedented era of capital investments in AI infrastructure, tilting the US into positive GDP territory. These are massive, swirling deals that might as well be cocktail party handshakes, greased with gigawatts and exuberance, while the rest of us try to track real contracts and dollars. OpenAI, Microsoft, Nvidia, Oracle, and SoftBank have struck some of the biggest deals. This year an earlier supercomputing project between OpenAI and Microsoft, called Stargate, became the vehicle for a massive AI infrastructure project in the US. (President Donald Trump called it the largest AI infrastructure project in history, because of course he did, but that may not have been hyperbolic.) Altman, Ellison, and SoftBank CEO Masayoshi Son were all in on the deal, pledging $100 billion to start, with plans to invest up to $500 billion into Stargate in the coming years. Nvidia GPUs would be deployed. Later, in July, OpenAI and Oracle announced an additional Stargate partnership—SoftBank curiously absent—measured in gigawatts of capacity (4.5) and expected job creation (around 100,000). Microsoft, Amazon, and Meta have also shared plans for multibillion-dollar data projects. Microsoft said at the start of 2025 that it was on track to invest “approximately $80 billion to build out AI-enabled data centers to train AI models and deploy AI and cloud-based applications around the world.” Then, in September, Nvidia said it would invest up to $100 billion in OpenAI, provided that OpenAI made good on a deal to use up to 10 gigawatts of Nvidia’s systems for OpenAI’s infrastructure plans, which means essentially that OpenAI has to pay Nvidia in order to get paid by Nvidia. The following month AMD said it would give OpenAI as much as 10 percent of the chip company if OpenAI purchased and deployed up to 6 gigawatts of AMD GPUs between now and 2030. It’s the circular nature of these investments that have the general public, and bearish analysts, wondering if we’re headed for an AI bubble burst. What’s clear is that the near-term downstream effects of these data center build-outs are real. The energy, resource, and labor demands of AI infrastructure are enormous. By some estimates, worldwide AI energy demand is set to surpass demand from bitcoin mining by the end of this year, WIRED has reported. The processors in data centers run hot and need to be cooled, so big tech companies are pulling from municipal water supplies to make that happen—and aren’t always disclosing how much water they’re using. Local wells are running dry or seem unsafe to drink from. Residents who live near data center construction sites are noting that traffic delays, and in some cases car crashes, are increasing. One corner of Richland Parish, Louisiana, home of Meta’s $27 billion Hyperion data center, has seen a 600 percent spike in vehicle crashes this year. Major proponents of AI seem to suggest that all of this will be worth it. Few top tech executives will publicly entertain the notion that this might be an overshoot, either ecologically or economically. “Emphatically … no,” Lisa Su, the chief executive of AMD, said earlier this month when asked if the AI froth has runneth over. Su, like other execs, cited overwhelming demand for AI as justification for these enormous capital expenditures. Demand from whom? Harder to pin down. In their mind, it’s everyone. All of us. The 800 million people who use ChatGPT on a weekly basis. The evolution from those 1990s data centers to the 2000s era of cloud computing to new AI data centers wasn’t just one continuum. The world has concurrently moved from the tiny internet to the big internet to the AI internet, and realistically speaking, there’s no going back. Generative AI is out of the bottle. The Sams and Jensens and Larrys and Lisas of the world aren’t wrong about this. It doesn’t mean they aren’t wrong about the math, though. About their economic predictions. Or their ideas about AI-powered productivity and the labor market. Or the availability of natural and material resources for these data centers. Or who will come once they build them. Or the timing of it all. Even Rome eventually collapsed.

Owen Gregorian

55,427 просмотров • 7 месяцев назад

🚨 BREAKING: Secretary of Defense Pete Hegseth has just CANCELED the US Department of Defense's reliance on "cheap Chinese labor" for their cloud services, an Obama-era program... ...WHY ON EARTH WAS THE US RELYING ON CHINA FOR OUR MILITARY COMPUTER INFRASTRUCTURE?!?! "It turns out that some tech companies have been using cheap Chinese labor to assist with DoD cloud services. This is obviously unacceptable, especially in today's digital threat environment." "Now, this was a legacy system created over a decade ago during the Obama administration...that's why today I'm announcing that China will no longer have any involvement whatsoever in our cloud services effective immediately." It is INSANE that Pete Hegseth had to do this.

🚨 BREAKING: Secretary of Defense Pete Hegseth has just CANCELED the US Department of Defense's reliance on "cheap Chinese labor" for their cloud services, an Obama-era program... ...WHY ON EARTH WAS THE US RELYING ON CHINA FOR OUR MILITARY COMPUTER INFRASTRUCTURE?!?! "It turns out that some tech companies have been using cheap Chinese labor to assist with DoD cloud services. This is obviously unacceptable, especially in today's digital threat environment." "Now, this was a legacy system created over a decade ago during the Obama administration...that's why today I'm announcing that China will no longer have any involvement whatsoever in our cloud services effective immediately." It is INSANE that Pete Hegseth had to do this.

Q STORM RIDER

575,774 просмотров • 3 месяцев назад

🚨 BREAKING: Secretary of Defense Pete Hegseth has just CANCELED the US Department of Defense's reliance on "cheap Chinese labor" for their cloud services, an Obama-era program... ...WHY ON EARTH WAS THE US RELYING ON CHINA FOR OUR MILITARY COMPUTER INFRASTRUCTURE?!?! "It turns out that some tech companies have been using cheap Chinese labor to assist with DoD cloud services. This is obviously unacceptable, especially in today's digital threat environment." "Now, this was a legacy system created over a decade ago during the Obama administration...that's why today I'm announcing that China will no longer have any involvement whatsoever in our cloud services effective immediately." It is INSANE that Pete Hegseth had to do this.

🚨 BREAKING: Secretary of Defense Pete Hegseth has just CANCELED the US Department of Defense's reliance on "cheap Chinese labor" for their cloud services, an Obama-era program... ...WHY ON EARTH WAS THE US RELYING ON CHINA FOR OUR MILITARY COMPUTER INFRASTRUCTURE?!?! "It turns out that some tech companies have been using cheap Chinese labor to assist with DoD cloud services. This is obviously unacceptable, especially in today's digital threat environment." "Now, this was a legacy system created over a decade ago during the Obama administration...that's why today I'm announcing that China will no longer have any involvement whatsoever in our cloud services effective immediately." It is INSANE that Pete Hegseth had to do this.

WWG1WGA🇺🇸♥️

130,389 просмотров • 2 месяцев назад

🚨 BREAKING: Secretary of Defense Pete Hegseth has just CANCELED the US Department of Defense's reliance on "cheap Chinese labor" for their cloud services, an Obama-era program... ...WHY ON EARTH WAS THE US RELYING ON CHINA FOR OUR MILITARY COMPUTER INFRASTRUCTURE?!?! "It turns out that some tech companies have been using cheap Chinese labor to assist with DoD cloud services. This is obviously unacceptable, especially in today's digital threat environment." "Now, this was a legacy system created over a decade ago during the Obama administration...that's why today I'm announcing that China will no longer have any involvement whatsoever in our cloud services effective immediately." It is INSANE that Pete Hegseth had to do this.

🚨 BREAKING: Secretary of Defense Pete Hegseth has just CANCELED the US Department of Defense's reliance on "cheap Chinese labor" for their cloud services, an Obama-era program... ...WHY ON EARTH WAS THE US RELYING ON CHINA FOR OUR MILITARY COMPUTER INFRASTRUCTURE?!?! "It turns out that some tech companies have been using cheap Chinese labor to assist with DoD cloud services. This is obviously unacceptable, especially in today's digital threat environment." "Now, this was a legacy system created over a decade ago during the Obama administration...that's why today I'm announcing that China will no longer have any involvement whatsoever in our cloud services effective immediately." It is INSANE that Pete Hegseth had to do this.

Eric Daugherty

1,037,215 просмотров • 1 год назад

Cyber Resilience: Staying Ahead, Not Just Bouncing Back! Cyber resilience isn't just about bouncing back—it's about keeping your momentum going, no matter what. Let's face it: in today's always-connected world, downtime isn't an option. Traditional cyber recovery methods often feel painfully slow, fragmented, and incomplete. Simply recovering data doesn't guarantee you'll get back to business fast enough. That's why Commvault Cloud Rewind caught my attention: Here's What Makes It Stand Out: ✅ Real-Time Recovery: Imagine rebuilding your entire environment—apps, workloads, and all—within minutes instead of days. (Yes, that's about 10x faster than most solutions out there.) ✅ Complete Environment Restoration: It’s about swiftly and seamlessly restoring your full infrastructure, from cloud applications to entire AI stacks. ✅ AI-Driven Automation: Cloud Rewind smartly leverages AI to "rewind" your business operations precisely to the moment before a breach, ensuring zero data loss and minimal disruption. ✅ Safe, Isolated Testing Environments: Air-gapped cloud spaces provide a safe environment to thoroughly test and perfect your recovery strategy before a crisis hits. ✅ Rapid Identity Restoration: Quickly rebuild Active Directory services, restoring identity and access management within minutes. With AI-driven decision-making accelerating and cybersecurity threats evolving, true resilience means uninterrupted business continuity. Commvault is stepping up to help businesses confidently manage cyber risks, ensuring minimal downtime and maximum operational stability. How prepared is your organization for its next cyber challenge? #ZeroLossRecovery #CyberResilience #Commvault #CloudRewind #CyberSecurity #DataRecovery #AI #RSAC

Cyber Resilience: Staying Ahead, Not Just Bouncing Back! Cyber resilience isn't just about bouncing back—it's about keeping your momentum going, no matter what. Let's face it: in today's always-connected world, downtime isn't an option. Traditional cyber recovery methods often feel painfully slow, fragmented, and incomplete. Simply recovering data doesn't guarantee you'll get back to business fast enough. That's why Commvault Cloud Rewind caught my attention: Here's What Makes It Stand Out: ✅ Real-Time Recovery: Imagine rebuilding your entire environment—apps, workloads, and all—within minutes instead of days. (Yes, that's about 10x faster than most solutions out there.) ✅ Complete Environment Restoration: It’s about swiftly and seamlessly restoring your full infrastructure, from cloud applications to entire AI stacks. ✅ AI-Driven Automation: Cloud Rewind smartly leverages AI to "rewind" your business operations precisely to the moment before a breach, ensuring zero data loss and minimal disruption. ✅ Safe, Isolated Testing Environments: Air-gapped cloud spaces provide a safe environment to thoroughly test and perfect your recovery strategy before a crisis hits. ✅ Rapid Identity Restoration: Quickly rebuild Active Directory services, restoring identity and access management within minutes. With AI-driven decision-making accelerating and cybersecurity threats evolving, true resilience means uninterrupted business continuity. Commvault is stepping up to help businesses confidently manage cyber risks, ensuring minimal downtime and maximum operational stability. How prepared is your organization for its next cyber challenge? #ZeroLossRecovery #CyberResilience #Commvault #CloudRewind #CyberSecurity #DataRecovery #AI #RSAC

Evan Kirstel #B2B #TechFluencer

29,820 просмотров • 1 год назад

🚀 We just raised $40 million to build infrastructure for Physical AI! 🦾 AI is rapidly transforming critical industries like manufacturing, logistics, transportation, agriculture, construction, aerospace, and defense. Teams that win in the physical world are those who can create a data flywheel, leveraging infrastructure to capture, ingest, analyze, and evaluate the vast quantities of data generated by real-world systems. Robotics data is multimodal, time-synchronized, and bandwidth‑constrained at the edge. Traditional data and observability platforms were only designed to store and query text and time-series data, not petabyte-scale 3D, video, audio, GNSS, and proprioceptive data. The ability to efficiently capture, ingest, search, visualize, and evaluate multimodal data is critical to Physical AI development. Foxglove is a modern data engine for Physical AI, enabling you to record logs or capture demonstrations at the edge, sync recordings to the cloud or on-premises storage, find critical events across petabytes of data, evaluate robot performance, and watch a 3D frame-by-frame replay using our advanced visualization tool. 👉 Today is still Day 1 for Physical AI, and we're hiring for dozens of roles to assemble the best team in the industry. If you've built ML platforms, data infrastructure, dataset curation, evaluation and validation, or visualization tools at a leading robotics or autonomous vehicle company, let's chat – drop me a note or tag a friend below and I'll follow up personally! Thank you to Alexandra Sukin and Jeremy Levine at Bessemer, Seth Winterroth 🤖 at Eclipse, David Beyer and Sunil Dhaliwal at Amplify Partners, and Icehouse Ventures for joining us on this mission. Also a special shoutout to our angels tobi lutke Alex Kendall Kyle Vogt Milan Kovac Hussein Mehanna Pieter Abbeel Brad Porter Boris Sofman Kevin Peterson Chris Walti Lindon Gao Daniel Kan Adam Draper ⏻ Fred Ehrsam and Karri Saarinen!

🚀 We just raised $40 million to build infrastructure for Physical AI! 🦾 AI is rapidly transforming critical industries like manufacturing, logistics, transportation, agriculture, construction, aerospace, and defense. Teams that win in the physical world are those who can create a data flywheel, leveraging infrastructure to capture, ingest, analyze, and evaluate the vast quantities of data generated by real-world systems. Robotics data is multimodal, time-synchronized, and bandwidth‑constrained at the edge. Traditional data and observability platforms were only designed to store and query text and time-series data, not petabyte-scale 3D, video, audio, GNSS, and proprioceptive data. The ability to efficiently capture, ingest, search, visualize, and evaluate multimodal data is critical to Physical AI development. Foxglove is a modern data engine for Physical AI, enabling you to record logs or capture demonstrations at the edge, sync recordings to the cloud or on-premises storage, find critical events across petabytes of data, evaluate robot performance, and watch a 3D frame-by-frame replay using our advanced visualization tool. 👉 Today is still Day 1 for Physical AI, and we're hiring for dozens of roles to assemble the best team in the industry. If you've built ML platforms, data infrastructure, dataset curation, evaluation and validation, or visualization tools at a leading robotics or autonomous vehicle company, let's chat – drop me a note or tag a friend below and I'll follow up personally! Thank you to Alexandra Sukin and Jeremy Levine at Bessemer, Seth Winterroth 🤖 at Eclipse, David Beyer and Sunil Dhaliwal at Amplify Partners, and Icehouse Ventures for joining us on this mission. Also a special shoutout to our angels tobi lutke Alex Kendall Kyle Vogt Milan Kovac Hussein Mehanna Pieter Abbeel Brad Porter Boris Sofman Kevin Peterson Chris Walti Lindon Gao Daniel Kan Adam Draper ⏻ Fred Ehrsam and Karri Saarinen!

Adrian Macneil — 🤖/acc

46,580 просмотров • 8 месяцев назад

Premier of Manitoba in Canada Wab Kinew says the quiet part out loud He’s rejecting data center projects because the real reason behind them is “surveillance capitalism” “We're not gonna move ahead with the data centre — I reject the idea that we have to be slaves to surveillance capitalism in order to participate in the modern economy” “So the message to any company out there should be, if you wanna have a thoughtful, human-centered approach to technology, come to Manitoba 'cause that's what we're interested in” This really should make you wonder about all the thousands of data centers being rapidly put up in America. You don’t need that many data centers for AI… The surveillance state is being built, right now I show in the video there are already hundreds of hyper scale data centers in America where they are either dedicated to, or a portion of them is dedicated to, surveillance of American for things like purchases It’s already happening

Premier of Manitoba in Canada Wab Kinew says the quiet part out loud He’s rejecting data center projects because the real reason behind them is “surveillance capitalism” “We're not gonna move ahead with the data centre — I reject the idea that we have to be slaves to surveillance capitalism in order to participate in the modern economy” “So the message to any company out there should be, if you wanna have a thoughtful, human-centered approach to technology, come to Manitoba 'cause that's what we're interested in” This really should make you wonder about all the thousands of data centers being rapidly put up in America. You don’t need that many data centers for AI… The surveillance state is being built, right now I show in the video there are already hundreds of hyper scale data centers in America where they are either dedicated to, or a portion of them is dedicated to, surveillance of American for things like purchases It’s already happening

Wall Street Apes

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Elon Musk on building data centers in Space: "We don't think this is a particularly difficult thing to do. In fact, we think it's easier than our communication satellites. The Starlink V3 communication satellite is an incredibly complex machine. The AI data center would be much simpler by comparison, because it's really just solar power plus radiator basic equipment for operating satellite, and then the laser links, which would connect to the Starlink communications constellation and then back to the ground the connection would happen no matter what the weather is because once you connect to the Starlink communication constellation the Starlink communicates the ground with frequencies that are cloud penetrating, so that in fact even roof penetrating some degree, so you would always be able to close link with the data centers."

Elon Musk on building data centers in Space: "We don't think this is a particularly difficult thing to do. In fact, we think it's easier than our communication satellites. The Starlink V3 communication satellite is an incredibly complex machine. The AI data center would be much simpler by comparison, because it's really just solar power plus radiator basic equipment for operating satellite, and then the laser links, which would connect to the Starlink communications constellation and then back to the ground the connection would happen no matter what the weather is because once you connect to the Starlink communication constellation the Starlink communicates the ground with frequencies that are cloud penetrating, so that in fact even roof penetrating some degree, so you would always be able to close link with the data centers."

DogeDesigner

38,116 просмотров • 1 месяц назад