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SONY SHIPS THIS APU IN A $200 PS5. BITCOIN OPERATIONS DUMPED IT ON EBAY FOR $40. HE 3D PRINTED A CASE OVERNIGHT AND KILLED $439 A MONTH IN ANTHROPIC AND OPENAI BILLS 00:34 he turns the board over and says "this was actually meant for bitcoin mining originally, and...

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Antid

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35,406 просмотров • 7 дней назад •via X (Twitter)

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INTEL SELLS THIS CHIP FOR $60 TO CASH REGISTERS. HE WIPED WINDOWS 11 WITH ONE COMMAND AND KILLED $200/MO CLAUDE CODE MAX AND $200/MO CHATGPT PRO FOR $5 OF ELECTRICITY 02:10 he drags the image file straight into the terminal window and says "next up is where the magic happens, we're going to use the dd command" $150 n97 mini pc -> one switch on the back, top panel off with no screws -> one screw and the 512gb windows drive comes out intact -> diskutil unmount /dev/disk9 -> sudo dd if=image of=/dev/disk9 bs=1m -> 9.13gb written -> secure boot disabled in the bios -> ubuntu and ollama up in 4 minutes microsoft says you need a 40 tops npu before it counts as an ai pc, this box has zero tops and no gpu, and the same $60 chip that scans your groceries now answers your prompts for less than one coffee a month the honest part: with no npu a 7b model runs on cpu at reading speed and nothing above 7b moves at all, this is not a frontier experience, it is a $5 one $150 n97 mini pc + 16gb ddr5 + 512gb nvme + one dd command + secure boot off + ubuntu + ollama + qwen 2.5 7b watch and save it, then kill your $439 stack this weekend, kimi does the same work at $19 flat and the whole map is in the article below
7:11

INTEL SELLS THIS CHIP FOR $60 TO CASH REGISTERS. HE WIPED WINDOWS 11 WITH ONE COMMAND AND KILLED $200/MO CLAUDE CODE MAX AND $200/MO CHATGPT PRO FOR $5 OF ELECTRICITY 02:10 he drags the image file straight into the terminal window and says "next up is where the magic happens, we're going to use the dd command" $150 n97 mini pc -> one switch on the back, top panel off with no screws -> one screw and the 512gb windows drive comes out intact -> diskutil unmount /dev/disk9 -> sudo dd if=image of=/dev/disk9 bs=1m -> 9.13gb written -> secure boot disabled in the bios -> ubuntu and ollama up in 4 minutes microsoft says you need a 40 tops npu before it counts as an ai pc, this box has zero tops and no gpu, and the same $60 chip that scans your groceries now answers your prompts for less than one coffee a month the honest part: with no npu a 7b model runs on cpu at reading speed and nothing above 7b moves at all, this is not a frontier experience, it is a $5 one $150 n97 mini pc + 16gb ddr5 + 512gb nvme + one dd command + secure boot off + ubuntu + ollama + qwen 2.5 7b watch and save it, then kill your $439 stack this weekend, kimi does the same work at $19 flat and the whole map is in the article below

Antid

23,161 просмотров • 6 дней назад

A $40 BC250 BOARD WITH 16GB GDDR6 GETS A GITHUB FIRMWARE FLASH, THE DEFAULT 8/8 CPU/GPU SPLIT REWRITES TO 0.5/15.5 AND OPENS 15.5GB OF UNIFIED MEMORY TO OLLAMA, DEAD CRYPTO HARDWARE JUST DOUBLED ITS AI CEILING 01:08 the operator points at the chart, "you only give 512 megs to the GPU part and that's reserved, that means all the rest of the RAM is available to either the CPU or the GPU" a BC250 ships from the factory with 16GB GDDR6 split 8/8 between Oberon CPU cores and the RDNA 2 iGPU, the iGPU only ever uses 4-5GB during inference, the other 3-4GB sits stranded SEC Bolt's firmware mod on the moth-enjoyer GitHub flashes a 0.5/15.5 split, the GPU reserves 512MB and 15.5GB falls into a unified pool that ollama treats as VRAM, qwen 3.6 14B at 4 bit fits with 2GB context headroom 15.5GB on a $40 board with a $40 CH347 flasher beats the $249 Jetson Orin Nano's 8GB by nearly 2x at 1/6th the price, the firmware is open source, the dump backup process takes 4 minutes per board your map's tier zero floor was the OptiPlex at $35-50 with iGPU only, the modded BC250 sits at the same $40 mark with 15.5GB of GDDR6 and an actual RDNA 2 GPU, the buyer who flashes once unlocks a 13B class local AI host for the price of a dinner the window is open, follow and bookmark before it closes
2:38

A $40 BC250 BOARD WITH 16GB GDDR6 GETS A GITHUB FIRMWARE FLASH, THE DEFAULT 8/8 CPU/GPU SPLIT REWRITES TO 0.5/15.5 AND OPENS 15.5GB OF UNIFIED MEMORY TO OLLAMA, DEAD CRYPTO HARDWARE JUST DOUBLED ITS AI CEILING 01:08 the operator points at the chart, "you only give 512 megs to the GPU part and that's reserved, that means all the rest of the RAM is available to either the CPU or the GPU" a BC250 ships from the factory with 16GB GDDR6 split 8/8 between Oberon CPU cores and the RDNA 2 iGPU, the iGPU only ever uses 4-5GB during inference, the other 3-4GB sits stranded SEC Bolt's firmware mod on the moth-enjoyer GitHub flashes a 0.5/15.5 split, the GPU reserves 512MB and 15.5GB falls into a unified pool that ollama treats as VRAM, qwen 3.6 14B at 4 bit fits with 2GB context headroom 15.5GB on a $40 board with a $40 CH347 flasher beats the $249 Jetson Orin Nano's 8GB by nearly 2x at 1/6th the price, the firmware is open source, the dump backup process takes 4 minutes per board your map's tier zero floor was the OptiPlex at $35-50 with iGPU only, the modded BC250 sits at the same $40 mark with 15.5GB of GDDR6 and an actual RDNA 2 GPU, the buyer who flashes once unlocks a 13B class local AI host for the price of a dinner the window is open, follow and bookmark before it closes

Antid

25,619 просмотров • 2 месяцев назад

NVIDIA KILLED DRIVER SUPPORT FOR THESE IN 2018. HE BOUGHT TWO OFF EBAY FOR $150 ANYWAY AND SPENT A WEEKEND WATCHING THEM REFUSE TO POST. KIMI DOES THE SAME WORK FOR $19/MO 03:11 he's holding a molex adapter he already knows is a mistake and says "this is so not a good idea, like this is a pretty foolish idea, I should not be doing this really" 2 tesla k80s for $150 -> 48gb of vram on paper -> no video out on either card -> no video out on the motherboard either -> hunt down a single-slot gpu just to see BIOS -> the y-splitter that shipped with them is bridged wrong -> improvise from three 6-pin rails -> 266 watts at idle -> 6 beeps -> nothing on screen kepler shipped in 2014, nvidia cut cuda support in 2018, and datacenters dumped millions of these onto ebay where they still list as "AI accelerator, 24GB" because 24 is a bigger number than 12 and nobody checks the compute capability the honest part: he swapped both cards, pulled the sata power, ran one alone off the correct rails, and neither one posted, the host boots fine with the slot empty, $150 gone and the weekend with it 2x tesla k80 + dual xeon host + 3d printed 120mm shroud + molex-to-8pin adapters + 6 bios beeps + zero tokens generated watch and save it, then kill your $439 stack this weekend, kimi does the same work at $19 flat and the whole map is in the article below
6:17

NVIDIA KILLED DRIVER SUPPORT FOR THESE IN 2018. HE BOUGHT TWO OFF EBAY FOR $150 ANYWAY AND SPENT A WEEKEND WATCHING THEM REFUSE TO POST. KIMI DOES THE SAME WORK FOR $19/MO 03:11 he's holding a molex adapter he already knows is a mistake and says "this is so not a good idea, like this is a pretty foolish idea, I should not be doing this really" 2 tesla k80s for $150 -> 48gb of vram on paper -> no video out on either card -> no video out on the motherboard either -> hunt down a single-slot gpu just to see BIOS -> the y-splitter that shipped with them is bridged wrong -> improvise from three 6-pin rails -> 266 watts at idle -> 6 beeps -> nothing on screen kepler shipped in 2014, nvidia cut cuda support in 2018, and datacenters dumped millions of these onto ebay where they still list as "AI accelerator, 24GB" because 24 is a bigger number than 12 and nobody checks the compute capability the honest part: he swapped both cards, pulled the sata power, ran one alone off the correct rails, and neither one posted, the host boots fine with the slot empty, $150 gone and the weekend with it 2x tesla k80 + dual xeon host + 3d printed 120mm shroud + molex-to-8pin adapters + 6 bios beeps + zero tokens generated watch and save it, then kill your $439 stack this weekend, kimi does the same work at $19 flat and the whole map is in the article below

Antid

51,310 просмотров • 4 дней назад

JENSEN HUANG STRIPPED NVLINK OUT OF CONSUMER CARDS IN 2021 TO PROTECT A $30K PRODUCT LINE. JIM KELLER PUT IT BACK IN A $1,400 CARD. HE MESHED TWO OFF A SINGLE PSU AND RUNS KIMI K3 FOR $6/MONTH 00:13 he holds up the green cable bundle, looks at the camera and says "we're not hooking team green up to these" 2 blackhole p150a for $2,800 -> skip the adapter chain entirely -> two 600w cables direct off one seasonic -> qsfp-dd 800g mesh card to card -> the pcie slot goes idle after model load -> kimi k3 at full 1m context for $6/month nvidia's whole $30k moat is the interconnect, keller shipped it on a card that costs 4.6% of an h100, tenstorrent's queue hit 11 weeks and the pcie bus that nvidia optimizes around stopped mattering in this build entirely the honest part: the software stack is 6 months behind cuda, you will lose a weekend to driver builds before the first token lands 2x tenstorrent blackhole p150a + qsfp-dd 800g + 1000w seasonic + ubuntu 26.04 + neo4j + kimi k3 watch and save it, then kill your $439 stack this weekend, kimi does the same work at $19 flat and the whole map is in the article below
1:04

JENSEN HUANG STRIPPED NVLINK OUT OF CONSUMER CARDS IN 2021 TO PROTECT A $30K PRODUCT LINE. JIM KELLER PUT IT BACK IN A $1,400 CARD. HE MESHED TWO OFF A SINGLE PSU AND RUNS KIMI K3 FOR $6/MONTH 00:13 he holds up the green cable bundle, looks at the camera and says "we're not hooking team green up to these" 2 blackhole p150a for $2,800 -> skip the adapter chain entirely -> two 600w cables direct off one seasonic -> qsfp-dd 800g mesh card to card -> the pcie slot goes idle after model load -> kimi k3 at full 1m context for $6/month nvidia's whole $30k moat is the interconnect, keller shipped it on a card that costs 4.6% of an h100, tenstorrent's queue hit 11 weeks and the pcie bus that nvidia optimizes around stopped mattering in this build entirely the honest part: the software stack is 6 months behind cuda, you will lose a weekend to driver builds before the first token lands 2x tenstorrent blackhole p150a + qsfp-dd 800g + 1000w seasonic + ubuntu 26.04 + neo4j + kimi k3 watch and save it, then kill your $439 stack this weekend, kimi does the same work at $19 flat and the whole map is in the article below

Antid

25,925 просмотров • 8 дней назад

WAREHOUSES THE SIZE OF A WALMART WITH 4,000 GPUS WERE EARNING $320K A MONTH MINING ETH, THE SAME RACKS NOW EARN $4M A MONTH RENTING TO AI STARTUPS ON VAST AI the warehouse in the clip is one of hundreds across the US, the operator at 6'6" tall for scale, electricity contracts and cooling already in place ethereum's merge in september 2022 killed gpu mining for everyone without a power plant, by 2025 alt coin mining was barely covering the electricity bill the same racks now host RTX 3090s and 4090s on vast ai, indie AI developers priced out of AWS rent them by the hour for inference and image generation a 4090 nets $500 to $1,000 a month renting to AI startups, the same card was clearing $80 to $150 mining, 4 to 7 times the revenue with zero new hardware core scientific, hut 8 and riot have all signed multi billion dollar AI hosting deals in 2025, the warehouses you scrolled past on tiktok are quietly becoming the inference backbone of every AI tool you use bookmark this and read the article below
1:19

WAREHOUSES THE SIZE OF A WALMART WITH 4,000 GPUS WERE EARNING $320K A MONTH MINING ETH, THE SAME RACKS NOW EARN $4M A MONTH RENTING TO AI STARTUPS ON VAST AI the warehouse in the clip is one of hundreds across the US, the operator at 6'6" tall for scale, electricity contracts and cooling already in place ethereum's merge in september 2022 killed gpu mining for everyone without a power plant, by 2025 alt coin mining was barely covering the electricity bill the same racks now host RTX 3090s and 4090s on vast ai, indie AI developers priced out of AWS rent them by the hour for inference and image generation a 4090 nets $500 to $1,000 a month renting to AI startups, the same card was clearing $80 to $150 mining, 4 to 7 times the revenue with zero new hardware core scientific, hut 8 and riot have all signed multi billion dollar AI hosting deals in 2025, the warehouses you scrolled past on tiktok are quietly becoming the inference backbone of every AI tool you use bookmark this and read the article below

starmex

427,680 просмотров • 2 месяцев назад

elon musk grabbed the source code openai open-sourced by accident, rewrote it in rust over a weekend, and shipped it as a free coding agent that does everything $200/mo chatgpt pro does. why pay $200 to openai and $200 to claude when this runs for $8 the swarm above is one weekend of exactly that: thousands of agents pouring through four endpoints, three paid seats billing $1.80 a task while the free fork bills $0. musk co-founded openai, walked out, and when they left codex on github under a permissive license, he forked it, stamped grok on it, and gave it away what the free version does that the $200 seat charges for: the agent · openai's own engine -> it reads your repo, writes patches, runs your tests, and loops until they pass, exactly like codex -> because under the hood it is codex, just faster and free. you are paying $200 for the paid skin of a tool now sitting on github the license · apache-2.0, un-revocable -> free to use, free to fork, free to ship inside your own product with zero strings -> openai cannot pull it back. musk made sure the license is the kind that never expires the switch · one line, no new tools -> point it at any openai-compatible or claude-compatible endpoint, including an $8 kimi backend -> same terminal, same workflow, gpt-5.6 and opus 5 just quietly lose the seat the bill · $400 down to $8 -> chatgpt pro plus claude max is $400 a month. the free agent plus an $8 kimi key does the same daily work -> that is a 98% cut, built out of openai's own source code, handed to you by the guy suing them here is the part they will fight me on: openai did not lose this to a better model, they lost it to their own license and an enemy with a weekend free. the $200 was never the tool, it was the toll, and musk just put openai's own logo on the road around it drop your $400/mo ai stack to $8. the run above is openai's own agent, rewritten free, doing the job it bills $200 a month for. the full breakdown is in the article below
0:26

elon musk grabbed the source code openai open-sourced by accident, rewrote it in rust over a weekend, and shipped it as a free coding agent that does everything $200/mo chatgpt pro does. why pay $200 to openai and $200 to claude when this runs for $8 the swarm above is one weekend of exactly that: thousands of agents pouring through four endpoints, three paid seats billing $1.80 a task while the free fork bills $0. musk co-founded openai, walked out, and when they left codex on github under a permissive license, he forked it, stamped grok on it, and gave it away what the free version does that the $200 seat charges for: the agent · openai's own engine -> it reads your repo, writes patches, runs your tests, and loops until they pass, exactly like codex -> because under the hood it is codex, just faster and free. you are paying $200 for the paid skin of a tool now sitting on github the license · apache-2.0, un-revocable -> free to use, free to fork, free to ship inside your own product with zero strings -> openai cannot pull it back. musk made sure the license is the kind that never expires the switch · one line, no new tools -> point it at any openai-compatible or claude-compatible endpoint, including an $8 kimi backend -> same terminal, same workflow, gpt-5.6 and opus 5 just quietly lose the seat the bill · $400 down to $8 -> chatgpt pro plus claude max is $400 a month. the free agent plus an $8 kimi key does the same daily work -> that is a 98% cut, built out of openai's own source code, handed to you by the guy suing them here is the part they will fight me on: openai did not lose this to a better model, they lost it to their own license and an enemy with a weekend free. the $200 was never the tool, it was the toll, and musk just put openai's own logo on the road around it drop your $400/mo ai stack to $8. the run above is openai's own agent, rewritten free, doing the job it bills $200 a month for. the full breakdown is in the article below

starmex

110,139 просмотров • 4 дней назад

THIS PORTABLE HACKER KIT PACKS A RASPBERRY PI 5 WITH 16GB OF RAM AND A 512GB NVME THAT ALSO RUNS LOCAL LLMs, KILLED $200 CLAUDE CODE MAX AND $200 CHATGPT PRO SUBSCRIPTIONS THE DAY IT WENT MOBILE 00:08 he sets down the pi and starts the tour, "this is my raspberry pi 5, 16 gigs of ram, 512 gigabyte nvme ssd storage, this thing means business" the kit stacks the pi next to a bluetooth analyzer, a 5g wifi router with a battery, and a pen-testing dongle for packet injection, the whole rig runs off usb-c and fits in a shoulder bag he uses it for evil-twin wifi tests and bluetooth device audits, and the same pi 5 also handles ollama with a 7b or 14b model locally at usable speed with every packet capture staying inside the case claude code points at localhost through a single environment variable, the cli behaves identically to the cloud version except every token generates on the pi in his hand and the api bill never arrives $200 chatgpt pro and $200 claude code max used to hit the same card that pays his internet, the whole subscription stack died the day the pi got mobile and ai bills went to zero because the model runs on the same box that runs his packet capture bookmark this and read the article below
1:03

THIS PORTABLE HACKER KIT PACKS A RASPBERRY PI 5 WITH 16GB OF RAM AND A 512GB NVME THAT ALSO RUNS LOCAL LLMs, KILLED $200 CLAUDE CODE MAX AND $200 CHATGPT PRO SUBSCRIPTIONS THE DAY IT WENT MOBILE 00:08 he sets down the pi and starts the tour, "this is my raspberry pi 5, 16 gigs of ram, 512 gigabyte nvme ssd storage, this thing means business" the kit stacks the pi next to a bluetooth analyzer, a 5g wifi router with a battery, and a pen-testing dongle for packet injection, the whole rig runs off usb-c and fits in a shoulder bag he uses it for evil-twin wifi tests and bluetooth device audits, and the same pi 5 also handles ollama with a 7b or 14b model locally at usable speed with every packet capture staying inside the case claude code points at localhost through a single environment variable, the cli behaves identically to the cloud version except every token generates on the pi in his hand and the api bill never arrives $200 chatgpt pro and $200 claude code max used to hit the same card that pays his internet, the whole subscription stack died the day the pi got mobile and ai bills went to zero because the model runs on the same box that runs his packet capture bookmark this and read the article below

starmex

25,094 просмотров • 1 месяц назад

JENSEN HUANG SOLD A $249 AI COMPUTER ON STAGE THAT KILLS YOUR $200/MONTH OPENAI BILL. THE VIDEO HAS 217,000 LIKES the box is called the jetson orin nano super. 70 trillion ai operations per second, 25 watts, smaller than a wallet. it runs llama 3, mistral, gemma and deepseek locally with no api fees and no data leaving your house a developer running automations and coding assistants pays $200 a month to openai. the same workload on this box costs $2 a month in electricity and breaks even on the hardware in 10 weeks you install ollama with one command. change one line in your code. point it at localhost instead of openai. everything else works identically 7 billion parameter models handle 80% of what people use chatgpt for. summarization, drafting, coding, document q&a, automation pipelines. the hard 20% you keep claude or gpt for. total monthly cost drops from $200 to $22 cloud subscriptions keep getting more expensive and rate limits keep getting tighter. the people who set this up in 2025 are going to look very smart in 2027 bookmark this and read the article below
1:18

JENSEN HUANG SOLD A $249 AI COMPUTER ON STAGE THAT KILLS YOUR $200/MONTH OPENAI BILL. THE VIDEO HAS 217,000 LIKES the box is called the jetson orin nano super. 70 trillion ai operations per second, 25 watts, smaller than a wallet. it runs llama 3, mistral, gemma and deepseek locally with no api fees and no data leaving your house a developer running automations and coding assistants pays $200 a month to openai. the same workload on this box costs $2 a month in electricity and breaks even on the hardware in 10 weeks you install ollama with one command. change one line in your code. point it at localhost instead of openai. everything else works identically 7 billion parameter models handle 80% of what people use chatgpt for. summarization, drafting, coding, document q&a, automation pipelines. the hard 20% you keep claude or gpt for. total monthly cost drops from $200 to $22 cloud subscriptions keep getting more expensive and rate limits keep getting tighter. the people who set this up in 2025 are going to look very smart in 2027 bookmark this and read the article below

starmex

1,998,810 просмотров • 3 месяцев назад

EVERYONE BUYING A $4,200 MAC STUDIO FOR LOCAL AI MISSED THAT TESLA V100s FROM DGX SERVERS ARE DUMPED ON EBAY FOR $250, AND ONE JUST RAN GPT-OSS 20B AT HOME a Tesla V100 SXM2 16GB shipped inside nvidia DGX-1 nodes at $10,000 per card in 2017, eight per chassis. those same cards now retire from cloud datacenters as H100s land, dumped on ebay at $200 to $300. drop a $50 SXM2 to PCIe adapter into a Z8 G4, slot the card with thermal pad, total bill $330. GPT-OSS 20B runs at 87°C and 180W the article calls the $700 used RTX 3090 the best memory per dollar. this V100 hack does the same job for one third the price with HBM2. the catch: HP Z620 fails on AVX2, install CUDA 11 not 12, flip above 4G decoding in BIOS the V100 pulls 250W and the blower screams. the mac mini from the article pulls 30W and runs silent. $300 versus $4,200 buys a lot of electricity and earplugs over four years
1:24

EVERYONE BUYING A $4,200 MAC STUDIO FOR LOCAL AI MISSED THAT TESLA V100s FROM DGX SERVERS ARE DUMPED ON EBAY FOR $250, AND ONE JUST RAN GPT-OSS 20B AT HOME a Tesla V100 SXM2 16GB shipped inside nvidia DGX-1 nodes at $10,000 per card in 2017, eight per chassis. those same cards now retire from cloud datacenters as H100s land, dumped on ebay at $200 to $300. drop a $50 SXM2 to PCIe adapter into a Z8 G4, slot the card with thermal pad, total bill $330. GPT-OSS 20B runs at 87°C and 180W the article calls the $700 used RTX 3090 the best memory per dollar. this V100 hack does the same job for one third the price with HBM2. the catch: HP Z620 fails on AVX2, install CUDA 11 not 12, flip above 4G decoding in BIOS the V100 pulls 250W and the blower screams. the mac mini from the article pulls 30W and runs silent. $300 versus $4,200 buys a lot of electricity and earplugs over four years

Shadow Nick

103,257 просмотров • 2 месяцев назад

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.
0:41

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 просмотров • 19 дней назад

This man bought 50 umbrellas for ₹5,000 at the rate of ₹100 each. Then he went and stood outside a metro station gate during the rain. People coming out of the station immediately bought umbrellas from him because of the heavy rainfall. He sold each umbrella for ₹200 and sold all 50 umbrellas within just one hour. He bought the umbrellas for ₹5,000 and sold them for ₹10,000, making a ₹5,000 profit in just one hour. He does this every day by going to a rainy location for one hour and selling all his umbrellas, earning a lot of money. He earns more than many people who work regular jobs by spending just one hour a day at a rainy location. A perfect example of how smart thinking can create opportunities and profits.
0:45

This man bought 50 umbrellas for ₹5,000 at the rate of ₹100 each. Then he went and stood outside a metro station gate during the rain. People coming out of the station immediately bought umbrellas from him because of the heavy rainfall. He sold each umbrella for ₹200 and sold all 50 umbrellas within just one hour. He bought the umbrellas for ₹5,000 and sold them for ₹10,000, making a ₹5,000 profit in just one hour. He does this every day by going to a rainy location for one hour and selling all his umbrellas, earning a lot of money. He earns more than many people who work regular jobs by spending just one hour a day at a rainy location. A perfect example of how smart thinking can create opportunities and profits.

Saffron Chargers

1,391,876 просмотров • 1 месяц назад

Valve is selling a $1,349 machine the internet already prints for $247. Look at this guy. He just fired up a 3D printer and watched it lay down the entire Steam Machine shell, layer by layer, in his room. No factory. No supply chain. No release date. Just a spool of plastic and a printer humming on his desk. It cost him $247. Meanwhile Valve spent months engineering this thing, building the hype, planning the June 29 launch. And they're charging the community $1,049 to $1,349 for it. No subsidy. Pure PC margins. One of them took a print file and a weekend. The other took a corporation. Same box. Same idea. One costs a quarter of the price, and it's sitting on his desk right now.
1:04

Valve is selling a $1,349 machine the internet already prints for $247. Look at this guy. He just fired up a 3D printer and watched it lay down the entire Steam Machine shell, layer by layer, in his room. No factory. No supply chain. No release date. Just a spool of plastic and a printer humming on his desk. It cost him $247. Meanwhile Valve spent months engineering this thing, building the hype, planning the June 29 launch. And they're charging the community $1,049 to $1,349 for it. No subsidy. Pure PC margins. One of them took a print file and a weekend. The other took a corporation. Same box. Same idea. One costs a quarter of the price, and it's sitting on his desk right now.

John Doe

343,017 просмотров • 2 месяцев назад

the CEO of NVIDIA just said the PC you use today will be gone, replaced by an AI supercomputer that lives in your house Jensen Huang stood on stage holding the machine and said it becomes less like a computer and more like R2-D2, a thing in your home that just does work for you all day he put it bluntly, this is as big as the day the phone became the smartphone and the wild part is the hardware to do it already exists and ships this year here is what he actually unveiled: > a desktop that runs a one trillion parameter AI model locally, 768GB of memory, sitting by your desk > agents that run 24/7 with no meter, no cloud bill, no rental, doing work while you sleep > NVIDIA and Microsoft rebuilding the PC from the ground up for the first time in 40 years > a full lineup, from a $249 chip to enterprise monsters, and almost nobody knows which one they actually need the hype is going to push everyone toward the biggest most expensive machine i wrote the honest breakdown, every NVIDIA AI box, what each really does, the real math, and which one is actually yours the full guide is in the article below
2:00

the CEO of NVIDIA just said the PC you use today will be gone, replaced by an AI supercomputer that lives in your house Jensen Huang stood on stage holding the machine and said it becomes less like a computer and more like R2-D2, a thing in your home that just does work for you all day he put it bluntly, this is as big as the day the phone became the smartphone and the wild part is the hardware to do it already exists and ships this year here is what he actually unveiled: > a desktop that runs a one trillion parameter AI model locally, 768GB of memory, sitting by your desk > agents that run 24/7 with no meter, no cloud bill, no rental, doing work while you sleep > NVIDIA and Microsoft rebuilding the PC from the ground up for the first time in 40 years > a full lineup, from a $249 chip to enterprise monsters, and almost nobody knows which one they actually need the hype is going to push everyone toward the biggest most expensive machine i wrote the honest breakdown, every NVIDIA AI box, what each really does, the real math, and which one is actually yours the full guide is in the article below

John Doe

194,375 просмотров • 3 месяцев назад

One guy built this app in a month and now it makes him more than $1,000,000 a year. No team. No investors. No marketing department. One developer. One month. One clever idea. The app is a camera for events. In its first month it got 100,000 downloads and he did not spend a single dollar on ads. Here is how he did it because the most interesting part is the growth itself. He did not bolt marketing onto the product. He made using the product the marketing itself. After that things kick in that almost nobody figures out. 1. You cannot use the app alone. For it to work the host has to pull every guest into it. Each install drags in dozens more right away. 2. One wedding is not one user but a whole crowd at once. 200 people scan one code in an evening and install the app. No ad brings that many for the same money and here the money is zero. 3. The guest becomes the host. He liked it at someone else's wedding and a month later he throws his own event and brings his own people. The loop spins itself and for free. 4. It does not look like an ad. To the guest it is a gift not some app forced on him. So they install it gladly and all of them do. 5. It all runs on emotion. A wedding. Memories. Shared shots. People film it and show their own people and a new wave comes in. Now let us count the money plain and honest. The subscription runs from 2 to 50 dollars. Say only every 20th person pays. That is 5,000 people out of 100,000. The average check a modest 20 dollars. 5,000 times 20 is 100,000 dollars a month. More than 3,000 a day. More than $1,000,000 a year. And all of this is one guy in a month without a single dollar on ads. He did not win on budget and not on a team. He won by sewing distribution into the very use of the product. You can lift almost any product this way. Could you build something like this on your own or is it just luck?
0:23

One guy built this app in a month and now it makes him more than $1,000,000 a year. No team. No investors. No marketing department. One developer. One month. One clever idea. The app is a camera for events. In its first month it got 100,000 downloads and he did not spend a single dollar on ads. Here is how he did it because the most interesting part is the growth itself. He did not bolt marketing onto the product. He made using the product the marketing itself. After that things kick in that almost nobody figures out. 1. You cannot use the app alone. For it to work the host has to pull every guest into it. Each install drags in dozens more right away. 2. One wedding is not one user but a whole crowd at once. 200 people scan one code in an evening and install the app. No ad brings that many for the same money and here the money is zero. 3. The guest becomes the host. He liked it at someone else's wedding and a month later he throws his own event and brings his own people. The loop spins itself and for free. 4. It does not look like an ad. To the guest it is a gift not some app forced on him. So they install it gladly and all of them do. 5. It all runs on emotion. A wedding. Memories. Shared shots. People film it and show their own people and a new wave comes in. Now let us count the money plain and honest. The subscription runs from 2 to 50 dollars. Say only every 20th person pays. That is 5,000 people out of 100,000. The average check a modest 20 dollars. 5,000 times 20 is 100,000 dollars a month. More than 3,000 a day. More than $1,000,000 a year. And all of this is one guy in a month without a single dollar on ads. He did not win on budget and not on a team. He won by sewing distribution into the very use of the product. You can lift almost any product this way. Could you build something like this on your own or is it just luck?

Blaze

10,703 просмотров • 1 месяц назад

🎙The Future of Africa’s CBDC & Bitcoin Ep. 59 with Abubakar Nur Khalil on You’re The Voice | Podcast by Efrat Fenigson My guest today is Abubakar Nur Khalil, a Nigerian Bitcoin Core contributor, CEO of the Bitcoin venture fund Recursive Capital Recursive Capital, and one of only four board members of Btrust Btrust - a nonprofit supporting Bitcoin development in Africa. At just 25 years old, Abubakar is transforming the African Bitcoin ecosystem by training developers, advancing Bitcoin adoption, and supporting decentralized financial solutions. In this episode, we explore Nigeria’s CBDC rollout of the eNaira, why it failed, the cash shortages, and the growing Bitcoin adoption. Abubkar shares his journey from contributing to Bitcoin Core to leading Btrust's mission of decentralizing Bitcoin development in the Global South. He also shares about the challenges of scaling Bitcoin adoption in Africa, the revolutionary role of Bitcoin mining in electrifying rural communities, and the untapped potential of Bitcoin in empowering Africa’s youth and businesses. ► If you got value, please like, comment, share, follow and support my work. Thank you! (00:00) Coming Up… (00:57) Introduction to Abubakar (03:48) The Journey to Becoming a Board Member of Btrust (09:08) Btrust’s Vision & Support for African Bitcoin Developers (12:58) Being Young & Successful (15:48) The eNaira - Nigeria’s CBDC (21:58) Cash Shortages in Nigeria (25:58) eNaira’s Failure & Speeding up Bitcoin Adoption (32:41) The CNGN - Nigeria's Stablecoin Initiative (35:01) Africa's Economic Landscape and Bitcoin Mining (40:15) Corruption and Governance Challenges in Africa (42:32) How Common Struggles Unify Africa (44:32) Non-Smartphones Can Use The Lightning Network (46:53) Ethiopia's Energy and Bitcoin Mining Potential (48:20) Why Are Most Bitcoin Transactions in Africa B2B (50:25) Regulatory Developments for Bitcoin Exchanges in Nigeria (52:54) Promising Future Projects in Bitcoin (56:58) Message of Hope >>
58:30

🎙The Future of Africa’s CBDC & Bitcoin Ep. 59 with Abubakar Nur Khalil on You’re The Voice | Podcast by Efrat Fenigson My guest today is Abubakar Nur Khalil, a Nigerian Bitcoin Core contributor, CEO of the Bitcoin venture fund Recursive Capital Recursive Capital, and one of only four board members of Btrust Btrust - a nonprofit supporting Bitcoin development in Africa. At just 25 years old, Abubakar is transforming the African Bitcoin ecosystem by training developers, advancing Bitcoin adoption, and supporting decentralized financial solutions. In this episode, we explore Nigeria’s CBDC rollout of the eNaira, why it failed, the cash shortages, and the growing Bitcoin adoption. Abubkar shares his journey from contributing to Bitcoin Core to leading Btrust's mission of decentralizing Bitcoin development in the Global South. He also shares about the challenges of scaling Bitcoin adoption in Africa, the revolutionary role of Bitcoin mining in electrifying rural communities, and the untapped potential of Bitcoin in empowering Africa’s youth and businesses. ► If you got value, please like, comment, share, follow and support my work. Thank you! (00:00) Coming Up… (00:57) Introduction to Abubakar (03:48) The Journey to Becoming a Board Member of Btrust (09:08) Btrust’s Vision & Support for African Bitcoin Developers (12:58) Being Young & Successful (15:48) The eNaira - Nigeria’s CBDC (21:58) Cash Shortages in Nigeria (25:58) eNaira’s Failure & Speeding up Bitcoin Adoption (32:41) The CNGN - Nigeria's Stablecoin Initiative (35:01) Africa's Economic Landscape and Bitcoin Mining (40:15) Corruption and Governance Challenges in Africa (42:32) How Common Struggles Unify Africa (44:32) Non-Smartphones Can Use The Lightning Network (46:53) Ethiopia's Energy and Bitcoin Mining Potential (48:20) Why Are Most Bitcoin Transactions in Africa B2B (50:25) Regulatory Developments for Bitcoin Exchanges in Nigeria (52:54) Promising Future Projects in Bitcoin (56:58) Message of Hope >>

Efrat Fenigson

28,032 просмотров • 1 год назад

FREE and open-source Bitcoin mining hardware: Don’t throw away or sell your S19j, S19k, or S19 Pro units just yet, developing something tailored for our Bitcoin-mining HeatHarvest greenhouse, semi-waterproof, moisture-resistant, and packed with some intriguing extras. Securing the hashboard with lock mechanisms was a priority, along with a tough and durable 3d printable frame that ties cleanly into other materials after printing. Working in mounts for alternative thermal-management modules, currently prototyping. Beyond the core functions, kept the pleb #Bitcoin miner in mind with this design, many pleb miners have small print area 3D printers, parts are kept within ranges to fit smaller printer beds. This is Prototype 1, the basic concept. Logged a dozen mod notes, now it’s back to CAD and reprints. Stay tuned, this is shaping up to be perfect for solo plebs mining at home and DIY Bitcoin heat capture projects.
0:26

FREE and open-source Bitcoin mining hardware: Don’t throw away or sell your S19j, S19k, or S19 Pro units just yet, developing something tailored for our Bitcoin-mining HeatHarvest greenhouse, semi-waterproof, moisture-resistant, and packed with some intriguing extras. Securing the hashboard with lock mechanisms was a priority, along with a tough and durable 3d printable frame that ties cleanly into other materials after printing. Working in mounts for alternative thermal-management modules, currently prototyping. Beyond the core functions, kept the pleb #Bitcoin miner in mind with this design, many pleb miners have small print area 3D printers, parts are kept within ranges to fit smaller printer beds. This is Prototype 1, the basic concept. Logged a dozen mod notes, now it’s back to CAD and reprints. Stay tuned, this is shaping up to be perfect for solo plebs mining at home and DIY Bitcoin heat capture projects.

Bee Evolved

10,948 просмотров • 10 месяцев назад

THIS $1,300 CARD HAS THE SAME 32GB OF VRAM AS A $2,000+ RTX 5090 - FOR LOCAL AI, THAT'S THE SPEC THAT DECIDES EVERYTHING. that clip is the gigabyte radeon ai pro r9700 ai top, 32gb of vram, built for local ai. the pitch is simple: the same memory capacity as an rtx 5090, for roughly a third of what a 5090 actually sells for. here's why that matters, and where it doesn't. for ai, vram is the gate. a model either fits in memory or it doesn't. 32gb loads models a 16gb card can't touch, full stop. so for running local llms and image models, this card does the one thing that counts, cheap. honest line: this is not a 5090 for gaming. the 5090 is far faster at raster and ray tracing. they only match on how much vram they carry. if you want frames, buy the 5090. if you want to fit big models locally, you just found the same 32gb for a third of the money. no $2,000+ price tag, no cloud gpu rental, no model too big for 16gb. the uncomfortable part isn't that amd is cheaper. it's that for local ai you were about to overpay for gaming power you'd never use. follow RetroChainer for more on paying for the spec that matters, and bookmark this before your next gpu.
1:52

THIS $1,300 CARD HAS THE SAME 32GB OF VRAM AS A $2,000+ RTX 5090 - FOR LOCAL AI, THAT'S THE SPEC THAT DECIDES EVERYTHING. that clip is the gigabyte radeon ai pro r9700 ai top, 32gb of vram, built for local ai. the pitch is simple: the same memory capacity as an rtx 5090, for roughly a third of what a 5090 actually sells for. here's why that matters, and where it doesn't. for ai, vram is the gate. a model either fits in memory or it doesn't. 32gb loads models a 16gb card can't touch, full stop. so for running local llms and image models, this card does the one thing that counts, cheap. honest line: this is not a 5090 for gaming. the 5090 is far faster at raster and ray tracing. they only match on how much vram they carry. if you want frames, buy the 5090. if you want to fit big models locally, you just found the same 32gb for a third of the money. no $2,000+ price tag, no cloud gpu rental, no model too big for 16gb. the uncomfortable part isn't that amd is cheaper. it's that for local ai you were about to overpay for gaming power you'd never use. follow RetroChainer for more on paying for the spec that matters, and bookmark this before your next gpu.

RetroChainer

38,844 просмотров • 22 дней назад

AMD CEO LISA SU HELD A MINI PC ON STAGE THAT RUNS A 235B MODEL AND REPLACES YOUR $440/MONTH AI STACK amd's ryzen ai max+ 395 is the first x86 chip that runs a 200 billion parameter model on one piece of silicon. cpu and gpu share 128gb of unified memory, no separate graphics card needed the gmktec evo-x2 runs qwen3 235b fully, deepseek v3 comfortably and llama 3.3 70b with headroom. on linux you get 110gb of usable vram out of 128gb amd claimed the chip beat an nvidia rtx 5080 by more than 3x on deepseek r1 inference. a lunchbox sized pc outrunning a $1,000 discrete gpu on a real ai workload a heavy ai user pays $200 for claude code max, $200 for chatgpt pro, $20 for cursor and $20 for gemini. that's $5,280 a year and the box pays itself off in 9 to 10 months install ollama, pull the model, point claude code at localhost. same interface, nothing leaves the machine, nothing costs per request bookmark this and read the article below
0:59

AMD CEO LISA SU HELD A MINI PC ON STAGE THAT RUNS A 235B MODEL AND REPLACES YOUR $440/MONTH AI STACK amd's ryzen ai max+ 395 is the first x86 chip that runs a 200 billion parameter model on one piece of silicon. cpu and gpu share 128gb of unified memory, no separate graphics card needed the gmktec evo-x2 runs qwen3 235b fully, deepseek v3 comfortably and llama 3.3 70b with headroom. on linux you get 110gb of usable vram out of 128gb amd claimed the chip beat an nvidia rtx 5080 by more than 3x on deepseek r1 inference. a lunchbox sized pc outrunning a $1,000 discrete gpu on a real ai workload a heavy ai user pays $200 for claude code max, $200 for chatgpt pro, $20 for cursor and $20 for gemini. that's $5,280 a year and the box pays itself off in 9 to 10 months install ollama, pull the model, point claude code at localhost. same interface, nothing leaves the machine, nothing costs per request bookmark this and read the article below

starmex

980,353 просмотров • 2 месяцев назад

NVIDIA'S BIGGEST COMPETITOR AMD BUILT A BOX THAT RUNS A 235B MODEL AND KILLS $200 OPENAI AND $200 CLAUDE CODE FOR $9 A MONTH amd's ryzen ai max+ 395 is the first x86 chip that runs a 200 billion parameter model on a single piece of silicon with 128gb of unified memory the gmktec evo-x2 runs qwen3 235b fully, deepseek v3 comfortably and llama 3.3 70b with headroom. on linux you get 110gb of usable vram out of 128gb amd claimed the chip beat an nvidia rtx 5080 by more than 3x on deepseek r1 inference. a lunchbox sized pc outrunning a $1,000 discrete gpu on a real ai workload a heavy ai user pays $200 for claude code max, $200 for chatgpt pro, $20 for cursor and $20 for gemini. that's $5,280 a year and the box pays itself off in 9 to 10 months ollama installs in one command and claude code points at localhost so nothing leaves the machine and nothing costs per request bookmark this and read the article below
1:06

NVIDIA'S BIGGEST COMPETITOR AMD BUILT A BOX THAT RUNS A 235B MODEL AND KILLS $200 OPENAI AND $200 CLAUDE CODE FOR $9 A MONTH amd's ryzen ai max+ 395 is the first x86 chip that runs a 200 billion parameter model on a single piece of silicon with 128gb of unified memory the gmktec evo-x2 runs qwen3 235b fully, deepseek v3 comfortably and llama 3.3 70b with headroom. on linux you get 110gb of usable vram out of 128gb amd claimed the chip beat an nvidia rtx 5080 by more than 3x on deepseek r1 inference. a lunchbox sized pc outrunning a $1,000 discrete gpu on a real ai workload a heavy ai user pays $200 for claude code max, $200 for chatgpt pro, $20 for cursor and $20 for gemini. that's $5,280 a year and the box pays itself off in 9 to 10 months ollama installs in one command and claude code points at localhost so nothing leaves the machine and nothing costs per request bookmark this and read the article below

starmex

93,465 просмотров • 2 месяцев назад

Bitcoin ETFs saw their biggest weekly inflow in 10 months "The fact that Bitcoin started pushing towards 80 was not just because shorts were being liquidated. That was not a leverage squeeze at all. What we can now see is that a big part of it was Bitcoin ETFs having their biggest weekly inflow in 10 months during the rally" "Bitcoin ETFs attracted $1.92 billion in the week. Ether ETFs added another $697 million, which is a very large number" "I had Alex Thorn from Galaxy on Macro Monday this morning, and he pointed out that this was effectively the most volume we've seen on Bitcoin ETFs since the all time high for Bitcoin in price and for ETFs back in October" "So that cannot be ignored. People buying ETFs is not part of a short squeeze. It is general belief that the bottom is likely in, and this is the time to re-enter the asset class"
0:59

Bitcoin ETFs saw their biggest weekly inflow in 10 months "The fact that Bitcoin started pushing towards 80 was not just because shorts were being liquidated. That was not a leverage squeeze at all. What we can now see is that a big part of it was Bitcoin ETFs having their biggest weekly inflow in 10 months during the rally" "Bitcoin ETFs attracted $1.92 billion in the week. Ether ETFs added another $697 million, which is a very large number" "I had Alex Thorn from Galaxy on Macro Monday this morning, and he pointed out that this was effectively the most volume we've seen on Bitcoin ETFs since the all time high for Bitcoin in price and for ETFs back in October" "So that cannot be ignored. People buying ETFs is not part of a short squeeze. It is general belief that the bottom is likely in, and this is the time to re-enter the asset class"

The Wolf Of All Streets

25,347 просмотров • 6 дней назад