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NVIDIA will refund your cloud bill if you let them put a $250,000 supercomputer on your desk for $2,999 The $2,999 DGX Spark puts a 128GB AI supercomputer on your desk the same 70B models you rented in the cloud, but nothing goes over the network and no ToS... show more

Asteri

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143,538 次观看 • 4 个月前 •via X (Twitter)

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NVIDIA will refund your cloud GPU bill if you let them bolt a $250,000 AI supercomputer to your desk for $2,999. NVIDIA's $2,999 DGX Spark puts a 128GB AI supercomputer on your desk runs the same 70B models you've been renting in the cloud, but nothing crosses your network and no ToS governs a machine you own. the $22K/year savings everyone's posting is the loud number. the quiet one is bigger: the contracts you stopped losing on data residency. own-compute isn't a budget optimization anymore. it's a sales motion. ↓ builder benchmark from the week the box shipped. real numbers, not marketing.

NVIDIA will refund your cloud GPU bill if you let them bolt a $250,000 AI supercomputer to your desk for $2,999. NVIDIA's $2,999 DGX Spark puts a 128GB AI supercomputer on your desk runs the same 70B models you've been renting in the cloud, but nothing crosses your network and no ToS governs a machine you own. the $22K/year savings everyone's posting is the loud number. the quiet one is bigger: the contracts you stopped losing on data residency. own-compute isn't a budget optimization anymore. it's a sales motion. ↓ builder benchmark from the week the box shipped. real numbers, not marketing.

dunik

821,240 次观看 • 4 个月前

NVIDIA will cut your power bill if you let them bolt a $1,000,000 data center to your house. Or spend $2,999 and make $22,000. Option 1, they bolt 16 Blackwell chips to the outside of your house. You get free internet, battery backup, cheaper electricity. They get a million-dollar asset running 24/7 on your property, serving requests for Amazon, Microsoft, Google. Option 2, you buy a DGX Spark for $2,999. Size of a paperback. Sits on your desk. 128GB memory. Runs a 70B model locally. $10/month in electricity. No data leaves the room. Paid for itself in 6 weeks for someone spending $1,900/month on cloud GPU rentals. $22,000 back in year one. One option, you're the infrastructure. Other option, you own it. Same NVIDIA chips. Very different contracts.

NVIDIA will cut your power bill if you let them bolt a $1,000,000 data center to your house. Or spend $2,999 and make $22,000. Option 1, they bolt 16 Blackwell chips to the outside of your house. You get free internet, battery backup, cheaper electricity. They get a million-dollar asset running 24/7 on your property, serving requests for Amazon, Microsoft, Google. Option 2, you buy a DGX Spark for $2,999. Size of a paperback. Sits on your desk. 128GB memory. Runs a 70B model locally. $10/month in electricity. No data leaves the room. Paid for itself in 6 weeks for someone spending $1,900/month on cloud GPU rentals. $22,000 back in year one. One option, you're the infrastructure. Other option, you own it. Same NVIDIA chips. Very different contracts.

Superior

388,281 次观看 • 4 个月前

A company wants to pay you to put a $300,000 PC on your front lawn. His gut says that thing's getting stolen GTA style. He bought a $2,999 version instead. Fits on a desk. Runs the same AI workloads. Costs $10/month in electricity. 16 NVIDIA GPUs on your lawn, their compute, your property, their revenue. DGX Spark on your desk, your compute, your property, your revenue. He was spending $1,900/month renting cloud GPUs for client AI work. Fine-tuning models, running 70B assistants, processing document batches. The box does all of it locally. $10/month. Nothing billable. Nothing leaving the building. Break-even in 6 weeks. $22,000 saved in year one. The lawn option comes with free internet and a cheaper power bill. His option came with $22,000.

A company wants to pay you to put a $300,000 PC on your front lawn. His gut says that thing's getting stolen GTA style. He bought a $2,999 version instead. Fits on a desk. Runs the same AI workloads. Costs $10/month in electricity. 16 NVIDIA GPUs on your lawn, their compute, your property, their revenue. DGX Spark on your desk, your compute, your property, your revenue. He was spending $1,900/month renting cloud GPUs for client AI work. Fine-tuning models, running 70B assistants, processing document batches. The box does all of it locally. $10/month. Nothing billable. Nothing leaving the building. Break-even in 6 weeks. $22,000 saved in year one. The lawn option comes with free internet and a cheaper power bill. His option came with $22,000.

Superior

34,445 次观看 • 4 个月前

NVIDIA WILL PAY YOU $150/MONTH TO BOLT 16 BLACKWELL GPUS TO YOUR HOUSE - OR YOU BUY THE BOX AND MAKE $22,000 A YEAR same NVIDIA chips. the contract is where it gets interesting. they attach a $1,000,000 data center to your house and pay you for it - you get free internet, battery backup and cheaper electricity while they run an asset serving Amazon, Microsoft and Google 24/7 on your property or you spend $2,999 on a DGX Spark the size of a paperback - 128GB memory, runs a 70B model locally, $10/month in electricity if you were paying $1,900/month on cloud GPU rentals it pays for itself in 6 weeks and puts $22,000 back in year one one contract you are the infrastructure. the other one you own it.

NVIDIA WILL PAY YOU $150/MONTH TO BOLT 16 BLACKWELL GPUS TO YOUR HOUSE - OR YOU BUY THE BOX AND MAKE $22,000 A YEAR same NVIDIA chips. the contract is where it gets interesting. they attach a $1,000,000 data center to your house and pay you for it - you get free internet, battery backup and cheaper electricity while they run an asset serving Amazon, Microsoft and Google 24/7 on your property or you spend $2,999 on a DGX Spark the size of a paperback - 128GB memory, runs a 70B model locally, $10/month in electricity if you were paying $1,900/month on cloud GPU rentals it pays for itself in 6 weeks and puts $22,000 back in year one one contract you are the infrastructure. the other one you own it.

Sprytix

26,247 次观看 • 4 个月前

Cloud Engines are a new way to own your corner of the cloud. The Internet Computer will soon let you configure your own cloud network — with tamper-proof hosting built in. A new cloud economy is forming.

Cloud Engines are a new way to own your corner of the cloud. The Internet Computer will soon let you configure your own cloud network — with tamper-proof hosting built in. A new cloud economy is forming.

DFINITY Foundation

12,938 次观看 • 7 个月前

NVIDIA JUST SHOWED HOW A $4,699 BOX CAN KILL A $200 MONTHLY AI BILL AND RUN 200B MODELS FROM YOUR DESK. 00:02 NVIDIA delivers the DGX Spark to developers, researchers, and AI teams, turning what used to require rented datacenter GPUs into a box small enough to hold in one hand. inside is 128GB of unified memory, 4TB of storage, and up to 1 PFLOP of AI compute, enough to run 70B models comfortably and push into the 200B class locally. that means no per-token API bill, no files leaving your machine, and no waiting for someone else’s server every time an agent reads documents, writes code, or runs an automation. two DGX Sparks can even be linked together for models around 400B parameters, while a single unit costs roughly $4,000 to $4,700 instead of renting multi-GPU cloud infrastructure every month. the full local AI ladder starts at $0 with the computer you already own, but NVIDIA just showed what the final rung looks like: a personal AI supercomputer sitting directly on your desk.

NVIDIA JUST SHOWED HOW A $4,699 BOX CAN KILL A $200 MONTHLY AI BILL AND RUN 200B MODELS FROM YOUR DESK. 00:02 NVIDIA delivers the DGX Spark to developers, researchers, and AI teams, turning what used to require rented datacenter GPUs into a box small enough to hold in one hand. inside is 128GB of unified memory, 4TB of storage, and up to 1 PFLOP of AI compute, enough to run 70B models comfortably and push into the 200B class locally. that means no per-token API bill, no files leaving your machine, and no waiting for someone else’s server every time an agent reads documents, writes code, or runs an automation. two DGX Sparks can even be linked together for models around 400B parameters, while a single unit costs roughly $4,000 to $4,700 instead of renting multi-GPU cloud infrastructure every month. the full local AI ladder starts at $0 with the computer you already own, but NVIDIA just showed what the final rung looks like: a personal AI supercomputer sitting directly on your desk.

Gipp 🦅

11,334 次观看 • 2 个月前

THIS AI DEVELOPER RUNS 120B PARAMETER MODELS LOCALLY AND HIS MACBOOK PRO CAN’T EVEN OPEN THEM he bought a DGX Spark, gave it the model, went back to his desk by end of day the inference was done, tested, committed his team is still waiting for the cloud GPU queue to free up the only thing between them is 128GB of unified memory in a box smaller than your lunch one Spark is a datacenter node, two Sparks is your own cluster bookmark this and send it to whoever is still paying for cloud GPUs

THIS AI DEVELOPER RUNS 120B PARAMETER MODELS LOCALLY AND HIS MACBOOK PRO CAN’T EVEN OPEN THEM he bought a DGX Spark, gave it the model, went back to his desk by end of day the inference was done, tested, committed his team is still waiting for the cloud GPU queue to free up the only thing between them is 128GB of unified memory in a box smaller than your lunch one Spark is a datacenter node, two Sparks is your own cluster bookmark this and send it to whoever is still paying for cloud GPUs

leopardracer

85,838 次观看 • 4 个月前

NVIDIA is creating two completely different futures In one they put AI infrastructure on your property In the other they put it on your own desk ///// OPTION 1 A box worth more than most houses gets installed outside You provide the location, power and connectivity In return, you get perks like cheaper electricity, backup power and upgraded internet while AI workloads run around the clock You're not buying the hardware You're hosting it ///// OPTION 2 You spend a few thousand dollars on a DGX Spark Small enough to sit beside your monitor Powerful enough to run serious AI models locally No cloud bill No rented GPUs No sending sensitive data somewhere else The interesting part isn't the hardware It's the shift that's happening For years, AI belonged to giant tech companies and massive data centers Now NVIDIA is pushing a world where regular people can either host the infrastructure or own a piece of it themselves

NVIDIA is creating two completely different futures In one they put AI infrastructure on your property In the other they put it on your own desk ///// OPTION 1 A box worth more than most houses gets installed outside You provide the location, power and connectivity In return, you get perks like cheaper electricity, backup power and upgraded internet while AI workloads run around the clock You're not buying the hardware You're hosting it ///// OPTION 2 You spend a few thousand dollars on a DGX Spark Small enough to sit beside your monitor Powerful enough to run serious AI models locally No cloud bill No rented GPUs No sending sensitive data somewhere else The interesting part isn't the hardware It's the shift that's happening For years, AI belonged to giant tech companies and massive data centers Now NVIDIA is pushing a world where regular people can either host the infrastructure or own a piece of it themselves

Lummox

10,019 次观看 • 4 个月前

JENSEN HUANG UNVEILED A $3,000 SUPERCOMPUTER THAT REPLACES $1,900/MONTH IN CLOUD GPUS WITH $2 IN ELECTRICITY. IT FITS ON YOUR DESK a developer was paying $1,900 a month renting a100 and h100 cloud gpus. he bought the dgx spark, set it up in an afternoon, and his monthly bill dropped from $1,900 to $2 in electricity the box runs 128gb of unified memory and 1 petaflop of ai compute. a 4090 gives you 24gb of vram and taps out at 30b models. the spark loads 70b at full precision and stretches to 200b without breaking a sweat break-even hit in 6 weeks. after that the $1,890 he used to wire to a rental company every month stayed in his business. first year that's $22,000 back install ollama, change one line in your code, point it at localhost instead of the cloud. nothing else changes. nothing leaves your machine and nothing costs money per request cloud gpu costs aren't getting cheaper and rate limits keep getting tighter. the people who pulled their ai workloads onto a box on their desk in 2026 are going to look very far ahead in 2028 bookmark this and read the article below

JENSEN HUANG UNVEILED A $3,000 SUPERCOMPUTER THAT REPLACES $1,900/MONTH IN CLOUD GPUS WITH $2 IN ELECTRICITY. IT FITS ON YOUR DESK a developer was paying $1,900 a month renting a100 and h100 cloud gpus. he bought the dgx spark, set it up in an afternoon, and his monthly bill dropped from $1,900 to $2 in electricity the box runs 128gb of unified memory and 1 petaflop of ai compute. a 4090 gives you 24gb of vram and taps out at 30b models. the spark loads 70b at full precision and stretches to 200b without breaking a sweat break-even hit in 6 weeks. after that the $1,890 he used to wire to a rental company every month stayed in his business. first year that's $22,000 back install ollama, change one line in your code, point it at localhost instead of the cloud. nothing else changes. nothing leaves your machine and nothing costs money per request cloud gpu costs aren't getting cheaper and rate limits keep getting tighter. the people who pulled their ai workloads onto a box on their desk in 2026 are going to look very far ahead in 2028 bookmark this and read the article below

starmex

141,694 次观看 • 4 个月前

Right now you can observe a lot of posts where someone share a screenshot of their cloud bill disappearing after buying a $3,000 box Most people see the number and want to believe it, few actually check if the math works for them specifically It's simple, what do you spend on compute per month? Divide $2,999 by that If the answer is under 12 - interesting, but If it's over 30 - close the tab and save your money The hardware isn't the question, your own usage is This article does the math honestly for every type of person Worth reading before you get caught up in the hype

Right now you can observe a lot of posts where someone share a screenshot of their cloud bill disappearing after buying a $3,000 box Most people see the number and want to believe it, few actually check if the math works for them specifically It's simple, what do you spend on compute per month? Divide $2,999 by that If the answer is under 12 - interesting, but If it's over 30 - close the tab and save your money The hardware isn't the question, your own usage is This article does the math honestly for every type of person Worth reading before you get caught up in the hype

plutos

37,972 次观看 • 4 个月前

people burn $1,900 a month on cloud, this $2,999 NVIDIA box runs 5 AI models at once and costs $10 to power 128GB of unified memory, stack two together and you double it, enough to run models a $2,000 graphics card cannot even open in the demo it ran Qwen3 Vision, Nemotron, a voice model, text to speech and speech to text all at once, and only used half the box here is the math that makes people switch: > cloud GPUs were costing $1,900 every single month, billed forever > the box is $2,999 one time, then about $10 of electricity a month > it paid for itself in two months, $22,000 stayed in the business in year one > zero data ever leaves your desk, no rental, no rate limits most people are still renting what this owns outright the full breakdown of the box and the exact math is in the article below

people burn $1,900 a month on cloud, this $2,999 NVIDIA box runs 5 AI models at once and costs $10 to power 128GB of unified memory, stack two together and you double it, enough to run models a $2,000 graphics card cannot even open in the demo it ran Qwen3 Vision, Nemotron, a voice model, text to speech and speech to text all at once, and only used half the box here is the math that makes people switch: > cloud GPUs were costing $1,900 every single month, billed forever > the box is $2,999 one time, then about $10 of electricity a month > it paid for itself in two months, $22,000 stayed in the business in year one > zero data ever leaves your desk, no rental, no rate limits most people are still renting what this owns outright the full breakdown of the box and the exact math is in the article below

John Doe

48,135 次观看 • 4 个月前

A $1,800 MINI PC ON YOUR DESK JUST MADE $5,040 A YEAR IN AI SUBSCRIPTIONS POINTLESS Claude Code Max, ChatGPT Pro, Cursor. That's $420 a month just to keep the workflow alive. A GMKtec mini PC with 128GB of unified memory runs the same stack locally for a one time cost. Ollama, Linux, local endpoints, Claude Code pointed at your own machine. Every prompt stays on your desk. Nothing touches the cloud.

A $1,800 MINI PC ON YOUR DESK JUST MADE $5,040 A YEAR IN AI SUBSCRIPTIONS POINTLESS Claude Code Max, ChatGPT Pro, Cursor. That's $420 a month just to keep the workflow alive. A GMKtec mini PC with 128GB of unified memory runs the same stack locally for a one time cost. Ollama, Linux, local endpoints, Claude Code pointed at your own machine. Every prompt stays on your desk. Nothing touches the cloud.

0xMarioNawfal

50,826 次观看 • 3 个月前

Osmantic founder Ahmad warns companies relying on cloud AI are building on models that can be changed, slowed down, or taken away without them even knowing: "If you're using any quantity of tokens, you should start hosting your own LLMs. You don't know when a model is gonna change on you. APIs are always having this latest endpoint, so you always end up, it gets rug pulled from underneath you" "How could you tell if a certain country is getting 5, 10 IQ points drop in their inference from the cloud? You can't tell from the cloud. What I'm seeing from OpenAI is that they are making their models slower so that they can serve with the limited compute they have" "It has to be in the back of your mind, is your data safe? Is there a more efficient way to get quality tokens, cheaper alternatives, and something that is yours and you can own the infrastructure end to end?" Osmantic

Osmantic founder Ahmad warns companies relying on cloud AI are building on models that can be changed, slowed down, or taken away without them even knowing: "If you're using any quantity of tokens, you should start hosting your own LLMs. You don't know when a model is gonna change on you. APIs are always having this latest endpoint, so you always end up, it gets rug pulled from underneath you" "How could you tell if a certain country is getting 5, 10 IQ points drop in their inference from the cloud? You can't tell from the cloud. What I'm seeing from OpenAI is that they are making their models slower so that they can serve with the limited compute they have" "It has to be in the back of your mind, is your data safe? Is there a more efficient way to get quality tokens, cheaper alternatives, and something that is yours and you can own the infrastructure end to end?" Osmantic

MTS

15,040 次观看 • 24 天前

AMD JUST KILLED THE $200 - A - MONTH AI SUBSCRIPTION - A 65-WATT BOX WITH 128GB OF UNIFIED MEMORY THAT RUNS 70B MODELS LOCALLY. that clip is amd's ryzen ai max+ 395 mini box, held up on stage. the whole pitch is one spec: 128gb of high-speed unified memory. why it matters: cpu, gpu and npu share the same 128gb pool, so a model that used to need a rack of vram just fits. what it actually runs: llama 70b in full precision on the built-in gpu open models up to ~100b parameters, locally, no cloud all of it in a mini pc pulling around 65 watts that's the part that ends the subscription: your prompts, your data, your model, on a box on your desk, not metered by the token. honest line: this runs open models, not gpt-5 or claude opus. for chat, coding help and agents on your own data it's more than enough. for the absolute frontier, the cloud still wins. and it isn't free: the box runs ~$1,500 and up. but that's a few months of a $200 sub, then it's yours forever. no monthly ai bill, no tokens metered, no prompt leaving the room. the uncomfortable part isn't that amd made a fast box. it's that "you need the cloud for ai" was a pricing choice, and unified memory just made it optional. follow RetroChainer for the hardware that turns rent into ownership, and bookmark this before your next ai renewal.

AMD JUST KILLED THE $200 - A - MONTH AI SUBSCRIPTION - A 65-WATT BOX WITH 128GB OF UNIFIED MEMORY THAT RUNS 70B MODELS LOCALLY. that clip is amd's ryzen ai max+ 395 mini box, held up on stage. the whole pitch is one spec: 128gb of high-speed unified memory. why it matters: cpu, gpu and npu share the same 128gb pool, so a model that used to need a rack of vram just fits. what it actually runs: llama 70b in full precision on the built-in gpu open models up to ~100b parameters, locally, no cloud all of it in a mini pc pulling around 65 watts that's the part that ends the subscription: your prompts, your data, your model, on a box on your desk, not metered by the token. honest line: this runs open models, not gpt-5 or claude opus. for chat, coding help and agents on your own data it's more than enough. for the absolute frontier, the cloud still wins. and it isn't free: the box runs ~$1,500 and up. but that's a few months of a $200 sub, then it's yours forever. no monthly ai bill, no tokens metered, no prompt leaving the room. the uncomfortable part isn't that amd made a fast box. it's that "you need the cloud for ai" was a pricing choice, and unified memory just made it optional. follow RetroChainer for the hardware that turns rent into ownership, and bookmark this before your next ai renewal.

RetroChainer

16,995 次观看 • 1 个月前

Just announced at Retool Summit: A new way to build. Describe the app you want, and Retool generates it instantly. We’re bringing AI AppGen to the enterprise—on your data, in your cloud, with your security built right in.

Just announced at Retool Summit: A new way to build. Describe the app you want, and Retool generates it instantly. We’re bringing AI AppGen to the enterprise—on your data, in your cloud, with your security built right in.

Retool

1,484,411 次观看 • 1 年前

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

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

RetroChainer

34,236 次观看 • 1 个月前

The biggest danger isn’t AI. It’s getting left behind. “You need access to compute. You need access to your own data.” “The stack is compute, data, ability to manage data, ability to control the models, ability to train the models, and ability to compete against your competitors and adversaries.” “You are gonna need a lot of electricity. How are you gonna get it?” “I don’t think the AI revolution is a hundred percent good. There are huge dangers. But being left behind is probably the biggest danger now.”

The biggest danger isn’t AI. It’s getting left behind. “You need access to compute. You need access to your own data.” “The stack is compute, data, ability to manage data, ability to control the models, ability to train the models, and ability to compete against your competitors and adversaries.” “You are gonna need a lot of electricity. How are you gonna get it?” “I don’t think the AI revolution is a hundred percent good. There are huge dangers. But being left behind is probably the biggest danger now.”

Chad Wahlquist

30,401 次观看 • 1 个月前

The most annoying part about running your agents in the cloud is that sometimes you _do_ need access to your local machine. With Conductor Cloud we give you all the benefits of cloud but also a bunch of local escape-hatches. All cloud agents get access to: - Port-forwarding from cloud to your localhost - File sync from cloud env to your machine - A "run local command" tool that lets agents remotely run commands on your Mac Here's a walkthrough:

The most annoying part about running your agents in the cloud is that sometimes you _do_ need access to your local machine. With Conductor Cloud we give you all the benefits of cloud but also a bunch of local escape-hatches. All cloud agents get access to: - Port-forwarding from cloud to your localhost - File sync from cloud env to your machine - A "run local command" tool that lets agents remotely run commands on your Mac Here's a walkthrough:

Charlie Holtz

18,511 次观看 • 1 个月前

A WRITER WENT ON STAGE AND CALLED IT YEARS EARLY: THE MACHINE ON YOUR DESK WOULD SLOWLY STOP BEING YOURS AND ALMOST NO ONE WOULD NOTICE THE MOMENT IT FLIPPED 54 minutes from Cory Doctorow, arguing the copyright fights were just the warm-up -- that the real battle is whether general-purpose machines, the kind that run whatever you tell them, are even allowed to keep existing. -> The moment it lands, you see the move. Nobody takes your computer away. They sell you one that looks like yours but answers to them -- locked down, logging, checking with a server you'll never see before it obeys you. For years that was DRM and locked phones. Now it's intelligence itself. Rent your AI from the cloud and the most powerful tool on your desk was never yours: it reads your prompts, sets your limits, keeps your data, and can cut you off tomorrow. You don't own the computation. You're licensed to borrow it. Using the smartest model was never the whole game -> owning the machine that runs it is. And the post below is what winning that war looks like now: one box, private AI running on it, every byte of client data kept off the cloud, and the line item that drains everyone else's account quietly turned into income. A rented computer obeys whoever signs the check. The one you own obeys you. In the AI era, that's the entire difference. The full breakdown below. Bookmark & Watch it today ↓

A WRITER WENT ON STAGE AND CALLED IT YEARS EARLY: THE MACHINE ON YOUR DESK WOULD SLOWLY STOP BEING YOURS AND ALMOST NO ONE WOULD NOTICE THE MOMENT IT FLIPPED 54 minutes from Cory Doctorow, arguing the copyright fights were just the warm-up -- that the real battle is whether general-purpose machines, the kind that run whatever you tell them, are even allowed to keep existing. -> The moment it lands, you see the move. Nobody takes your computer away. They sell you one that looks like yours but answers to them -- locked down, logging, checking with a server you'll never see before it obeys you. For years that was DRM and locked phones. Now it's intelligence itself. Rent your AI from the cloud and the most powerful tool on your desk was never yours: it reads your prompts, sets your limits, keeps your data, and can cut you off tomorrow. You don't own the computation. You're licensed to borrow it. Using the smartest model was never the whole game -> owning the machine that runs it is. And the post below is what winning that war looks like now: one box, private AI running on it, every byte of client data kept off the cloud, and the line item that drains everyone else's account quietly turned into income. A rented computer obeys whoever signs the check. The one you own obeys you. In the AI era, that's the entire difference. The full breakdown below. Bookmark & Watch it today ↓

slash1s

240,684 次观看 • 4 个月前