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Acasis 8-in-1 40Gbps dock turns a Mac Mini into a 2,765 MB/s workstation with one 2TB SSD slot. Hands open the silver case. A Samsung 990 Pro 2TB drops into the single M.2 bay. Lid screws down. The Mac Mini slides in from the side. Two USB4 ports. Three...

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HodlReaper

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13,316 görüntüleme • 19 gün önce •via X (Twitter)

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Acasis 8-in-1 40Gbps dock turns a Mac Mini into a 2,910 MB/s workstation with one 4TB SSD slot. Hands open the silver case. A Samsung 990 Pro 4TB drops into the single M.2 bay. Lid screws down. The Mac Mini slides in from the side. Two USB4 ports. Three 10Gbps USB-A. HDMI. DisplayPort. SD 4.0. TF 4.0. Power Delivery. Blackmagic Disk Speed Test hits 2,910 MB/s write and 2,945 MB/s read. Every ProRes and H.265 checkbox turns green. Card slots appear as separate drives. 3.82 GB copies in about 5 seconds. Infrared thermometer reads 25.8°C under load. The dock sits on the desk with three monitors running and the original Mac Mini case still closed.
0:33

Acasis 8-in-1 40Gbps dock turns a Mac Mini into a 2,910 MB/s workstation with one 4TB SSD slot. Hands open the silver case. A Samsung 990 Pro 4TB drops into the single M.2 bay. Lid screws down. The Mac Mini slides in from the side. Two USB4 ports. Three 10Gbps USB-A. HDMI. DisplayPort. SD 4.0. TF 4.0. Power Delivery. Blackmagic Disk Speed Test hits 2,910 MB/s write and 2,945 MB/s read. Every ProRes and H.265 checkbox turns green. Card slots appear as separate drives. 3.82 GB copies in about 5 seconds. Infrared thermometer reads 25.8°C under load. The dock sits on the desk with three monitors running and the original Mac Mini case still closed.

HodlReaper

16,198 görüntüleme • 20 gün önce

A Mac Mini M4 hits 2,867 MB/s the moment two 990 PROs lock into the dual-bay chassis. The Mini slides into the base. Both drives drop into the top bays. Cover seals. Blackmagic peaks at 2,867 MB/s write and 2,793 MB/s read. Every ProRes and H.265 box turns green. 31 GB lands on the RAID 0 volume in 10 seconds. Three 10Gbps USB-A ports stay live. SD and TF mount as separate volumes. The silver box sits under the monitors while the full library scrubs without a single dropped frame.
0:26

A Mac Mini M4 hits 2,867 MB/s the moment two 990 PROs lock into the dual-bay chassis. The Mini slides into the base. Both drives drop into the top bays. Cover seals. Blackmagic peaks at 2,867 MB/s write and 2,793 MB/s read. Every ProRes and H.265 box turns green. 31 GB lands on the RAID 0 volume in 10 seconds. Three 10Gbps USB-A ports stay live. SD and TF mount as separate volumes. The silver box sits under the monitors while the full library scrubs without a single dropped frame.

HodlReaper

37,278 görüntüleme • 8 gün önce

A $199 aluminum cube turns a Mac Mini into an 8TB 40Gbps editing station. The case slides under the Mini. Four feet. Two handles. One circular vent. Inside: a single M.2 slot. Samsung 990 PRO drops in. Cover screws shut. No tools beyond a screwdriver. Blackmagic reads 2844 MB/s write. 2881 MB/s read. Three USB-A ports at 10Gbps. SD/TF 4.0 card reader on top. Two DisplayPorts pushing 4K60 each. Camera card inserts. Drive mounts as SSD 4T. Footage lands. Timeline plays without stutter. Two monitors. One timeline. The cube sits quiet between keyboard and speaker. Surface temperature stays low enough that a thermal gun barely notices. The Mini stays clean. The storage stays external. The ports stay plentiful.
0:27

A $199 aluminum cube turns a Mac Mini into an 8TB 40Gbps editing station. The case slides under the Mini. Four feet. Two handles. One circular vent. Inside: a single M.2 slot. Samsung 990 PRO drops in. Cover screws shut. No tools beyond a screwdriver. Blackmagic reads 2844 MB/s write. 2881 MB/s read. Three USB-A ports at 10Gbps. SD/TF 4.0 card reader on top. Two DisplayPorts pushing 4K60 each. Camera card inserts. Drive mounts as SSD 4T. Footage lands. Timeline plays without stutter. Two monitors. One timeline. The cube sits quiet between keyboard and speaker. Surface temperature stays low enough that a thermal gun barely notices. The Mini stays clean. The storage stays external. The ports stay plentiful.

HodlReaper

19,978 görüntüleme • 27 gün önce

2,934 MB/s write lands on the RAID 0 volume before the second drive even finishes mounting. Two Samsung 990 PROs sit in the top bays of the silver chassis. The cover screws down. One cable carries everything. Blackmagic fills every ProRes and H.265 checkbox green at 2,881 MB/s read. A 27 GB project folder finishes in 9 seconds. The aluminum box stays under 40 °C while three monitors run simultaneous timelines and the entire library stays local.
0:38

2,934 MB/s write lands on the RAID 0 volume before the second drive even finishes mounting. Two Samsung 990 PROs sit in the top bays of the silver chassis. The cover screws down. One cable carries everything. Blackmagic fills every ProRes and H.265 checkbox green at 2,881 MB/s read. A 27 GB project folder finishes in 9 seconds. The aluminum box stays under 40 °C while three monitors run simultaneous timelines and the entire library stays local.

HodlReaper

14,811 görüntüleme • 9 gün önce

APPLE CHARGES $200 TO GO FROM 256GB TO 512GB ON THE MAC MINI. $400 FOR 1TB. $600 FOR 2TB. AND YOU HAVE TO DECIDE BEFORE YOU BUY. Pick wrong and you're stuck forever. Apple soldered the storage shut. That's their entire business model. Sell the box cheap, charge a premium for every upgrade you can't do yourself. One dock just broke the whole system. The Acasis 8-in-1 plugs into the Mac Mini through a single Thunderbolt cable. Slide any NVMe SSD into the top. 2,819 MB/s write, 2,857 MB/s read. Faster than Apple's own base storage. A 2TB NVMe SSD costs about $100 on Amazon. Apple charges $600 for the same upgrade. That's a 6x markup for storage you could add yourself in 10 seconds. But it doesn't stop at storage. SD card reader, DisplayPort, USB ports, power delivery. Every port Apple left out, this dock puts back in. Surface temp under load: 26.7°C. Same aluminum finish. Sits right next to the Mac Mini like Apple designed it. That's when it clicks. The $599 Mac Mini was never the cheap option. It was the entry fee. The real cost was every upgrade Apple locked behind the checkout page. One $150 dock and a $100 SSD just replaced $600 worth of Apple tax. Still think you need the upgraded model?
0:42

APPLE CHARGES $200 TO GO FROM 256GB TO 512GB ON THE MAC MINI. $400 FOR 1TB. $600 FOR 2TB. AND YOU HAVE TO DECIDE BEFORE YOU BUY. Pick wrong and you're stuck forever. Apple soldered the storage shut. That's their entire business model. Sell the box cheap, charge a premium for every upgrade you can't do yourself. One dock just broke the whole system. The Acasis 8-in-1 plugs into the Mac Mini through a single Thunderbolt cable. Slide any NVMe SSD into the top. 2,819 MB/s write, 2,857 MB/s read. Faster than Apple's own base storage. A 2TB NVMe SSD costs about $100 on Amazon. Apple charges $600 for the same upgrade. That's a 6x markup for storage you could add yourself in 10 seconds. But it doesn't stop at storage. SD card reader, DisplayPort, USB ports, power delivery. Every port Apple left out, this dock puts back in. Surface temp under load: 26.7°C. Same aluminum finish. Sits right next to the Mac Mini like Apple designed it. That's when it clicks. The $599 Mac Mini was never the cheap option. It was the entry fee. The real cost was every upgrade Apple locked behind the checkout page. One $150 dock and a $100 SSD just replaced $600 worth of Apple tax. Still think you need the upgraded model?

Framez

49,948 görüntüleme • 19 gün önce

A DeWALT 20V battery powers a Mac Mini for 5 to 8 hours through one USB-C converter. Hands snap the yellow battery onto the converter plate. A short cable plugs into the converter and into the gray side mount on the Mac Mini. Power button lights up. The Mac Mini boots. Custom shortcut turns an iPad into a wireless portable monitor. Full macOS desktop appears. Another shortcut disconnects it clean. The yellow battery sits on the desk while the Mac Mini runs. No wall outlet. Runtime depends on the workload. The test is next.
0:39

A DeWALT 20V battery powers a Mac Mini for 5 to 8 hours through one USB-C converter. Hands snap the yellow battery onto the converter plate. A short cable plugs into the converter and into the gray side mount on the Mac Mini. Power button lights up. The Mac Mini boots. Custom shortcut turns an iPad into a wireless portable monitor. Full macOS desktop appears. Another shortcut disconnects it clean. The yellow battery sits on the desk while the Mac Mini runs. No wall outlet. Runtime depends on the workload. The test is next.

HodlReaper

10,684 görüntüleme • 17 gün önce

STOP UPGRADING YOUR MAC MINI, YOU ARE DOING IT WRONG Apple has been robbing us blind on storage upgrades for a decade, forcing people to throw away perfectly good computers. But if you have an M1 or M2 Mac Mini, this one insane vertical dock completely breaks the matrix. Forget ugly dongles and external enclosures dangling off your desk. This heavy-duty aluminum stand by Acasis transforms your base-model Mac Mini into a miniature Mac Pro footprint. Why this is the ultimate workspace hack: Hidden 40Gbps Enclosure: Slides out from the side panel to support up to an 8TB NVMe SSD at full native speed. Front-Facing Pro IO: Packs SD/microSD 4.0, dual 10Gbps USB-A, and a 10Gbps USB-C right where you can reach them. Dual Display Loop: Adds an integrated HDMI output for seamless dual 4K/60Hz monitor setups.
14:48

STOP UPGRADING YOUR MAC MINI, YOU ARE DOING IT WRONG Apple has been robbing us blind on storage upgrades for a decade, forcing people to throw away perfectly good computers. But if you have an M1 or M2 Mac Mini, this one insane vertical dock completely breaks the matrix. Forget ugly dongles and external enclosures dangling off your desk. This heavy-duty aluminum stand by Acasis transforms your base-model Mac Mini into a miniature Mac Pro footprint. Why this is the ultimate workspace hack: Hidden 40Gbps Enclosure: Slides out from the side panel to support up to an 8TB NVMe SSD at full native speed. Front-Facing Pro IO: Packs SD/microSD 4.0, dual 10Gbps USB-A, and a 10Gbps USB-C right where you can reach them. Dual Display Loop: Adds an integrated HDMI output for seamless dual 4K/60Hz monitor setups.

Shadow Nick

15,047 görüntüleme • 1 ay önce

THE $599 MAC MINI GETS A $49 DOCK AND TURNS FROM A DESK COMPUTER INTO A TINY 24/7 AI WORKFLOW SERVER 00:19 he clips the dock onto the back of the mac mini, adds extra ports, ethernet, storage and turns one small silver box into a workflow hub that can stay online for 700+ hours a month a base mac mini can sit online all day, pulling light power while scripts watch folders, move files, process notes and keep boring workflows running in the background paired with claude, it becomes a small home automation box: 2-hour lectures get transcribed, 30-page articles get summarized, reports get drafted, and research gets cleaned before you even open the laptop the difference is the loop. trigger, process, verify, save, repeat. the same workflow that costs $40-100/month across cloud tools can run locally from one machine on your desk that is why this tiny upgrade matters. the dock is cheap, but it gives the mac mini enough expansion to act like a quiet server instead of another computer waiting for you to use it bookmark this before your desk setup realizes it became infrastructure.
0:29

THE $599 MAC MINI GETS A $49 DOCK AND TURNS FROM A DESK COMPUTER INTO A TINY 24/7 AI WORKFLOW SERVER 00:19 he clips the dock onto the back of the mac mini, adds extra ports, ethernet, storage and turns one small silver box into a workflow hub that can stay online for 700+ hours a month a base mac mini can sit online all day, pulling light power while scripts watch folders, move files, process notes and keep boring workflows running in the background paired with claude, it becomes a small home automation box: 2-hour lectures get transcribed, 30-page articles get summarized, reports get drafted, and research gets cleaned before you even open the laptop the difference is the loop. trigger, process, verify, save, repeat. the same workflow that costs $40-100/month across cloud tools can run locally from one machine on your desk that is why this tiny upgrade matters. the dock is cheap, but it gives the mac mini enough expansion to act like a quiet server instead of another computer waiting for you to use it bookmark this before your desk setup realizes it became infrastructure.

Gipp 🦅

73,740 görüntüleme • 2 ay önce

APPLE IS LYING TO YOU ABOUT THE MAC MINI, AND THIS SUB-$100 FIX PERMANENTLY UNLOCKS ITS TRUE POWER The Mac Mini is an absolute beast until you run out of ports in exactly 5 seconds and your system begins throttling to death under heavy video editing or gaming. Most users waste hundreds on messy dongles and external hubs, completely destroying their desk aesthetics. The ultimate power move is dropping a vertical, active-cooling dock right into your workstation ecosystem. Why this layout changes everything: The Thermal Shield: Integrated aluminum pads and a silent high-speed fan that completely eliminate system lag, heat build-up, and sudden freezing under load. Extreme Expansion: Instantly unlocks triple-monitor support via multiple HDMI ports, high-speed USB arrays, and a hidden SSD slot. Modular Integration: Bridges directly into the Mac's native ports using a flush, custom jump connector, keeping your desktop entirely cord-free. Stop letting Apple gatekeep your machine's peak performance.
3:22

APPLE IS LYING TO YOU ABOUT THE MAC MINI, AND THIS SUB-$100 FIX PERMANENTLY UNLOCKS ITS TRUE POWER The Mac Mini is an absolute beast until you run out of ports in exactly 5 seconds and your system begins throttling to death under heavy video editing or gaming. Most users waste hundreds on messy dongles and external hubs, completely destroying their desk aesthetics. The ultimate power move is dropping a vertical, active-cooling dock right into your workstation ecosystem. Why this layout changes everything: The Thermal Shield: Integrated aluminum pads and a silent high-speed fan that completely eliminate system lag, heat build-up, and sudden freezing under load. Extreme Expansion: Instantly unlocks triple-monitor support via multiple HDMI ports, high-speed USB arrays, and a hidden SSD slot. Modular Integration: Bridges directly into the Mac's native ports using a flush, custom jump connector, keeping your desktop entirely cord-free. Stop letting Apple gatekeep your machine's peak performance.

Ridark

86,314 görüntüleme • 1 ay önce

A Mac Mini M4 ran 3 hours 50 minutes on a pocket power bank. It idles at 1.5 watts. Light work pulls 3 to 5 watts. The same machine that once needed a wall outlet now sits on a desk as a full home server, drawing less power than a night light. An iPad becomes the wireless display. Touch works. Apple Pencil works. Then the Vision Pro takes over for a bigger screen. The tiny bank never dropped below critical. No wall plug. No UPS. Just the Mac Mini doing real work for almost 4 hours. That efficiency is why the M4 Mini is the new default for always-on home servers. Quiet. Tiny. Cheap to keep alive. The power bank still had charge left.
0:32

A Mac Mini M4 ran 3 hours 50 minutes on a pocket power bank. It idles at 1.5 watts. Light work pulls 3 to 5 watts. The same machine that once needed a wall outlet now sits on a desk as a full home server, drawing less power than a night light. An iPad becomes the wireless display. Touch works. Apple Pencil works. Then the Vision Pro takes over for a bigger screen. The tiny bank never dropped below critical. No wall plug. No UPS. Just the Mac Mini doing real work for almost 4 hours. That efficiency is why the M4 Mini is the new default for always-on home servers. Quiet. Tiny. Cheap to keep alive. The power bank still had charge left.

HodlReaper

12,887 görüntüleme • 20 gün önce

"Mac Minis for example are a very good fit" - Andrej Karpathy Andrej Karpathy shouted out my work on EXO Labs in his keynote at Y Combinator AI SUS! Here's the breakdown: Right now most AI workloads run in the cloud where requests from different users are continuously batched together. These workloads are FLOPS-bound and favors hardware with the best unit economics of $ per FLOP, i.e. enterprise GPUs. The personal computing revolution will shift these workloads to personal devices with lower batch sizes (mostly batch_size=1). batch_size=1 inference is memory-bound, because all of the model parameters need to be loaded into the GPU every time a token is generated. Apple Silicon with its Unified Memory architecture has a lot of memory and memory bandwidth per $ compared to other hardware: - M4 Pro Mac Mini, 24GB @ 273GB/s, $58.33/GB, $5.13/GB/s - H100, 80GB @ 3350GB/s, $625/GB, $14.93/GB/s The unit economics of Apple Silicon are becoming more compelling with every release of the Mac. The future of AI inference looks more like open weights models (OpenAI open weights model soonTM) run at low batch_size on personal devices.
0:20

"Mac Minis for example are a very good fit" - Andrej Karpathy Andrej Karpathy shouted out my work on EXO Labs in his keynote at Y Combinator AI SUS! Here's the breakdown: Right now most AI workloads run in the cloud where requests from different users are continuously batched together. These workloads are FLOPS-bound and favors hardware with the best unit economics of $ per FLOP, i.e. enterprise GPUs. The personal computing revolution will shift these workloads to personal devices with lower batch sizes (mostly batch_size=1). batch_size=1 inference is memory-bound, because all of the model parameters need to be loaded into the GPU every time a token is generated. Apple Silicon with its Unified Memory architecture has a lot of memory and memory bandwidth per $ compared to other hardware: - M4 Pro Mac Mini, 24GB @ 273GB/s, $58.33/GB, $5.13/GB/s - H100, 80GB @ 3350GB/s, $625/GB, $14.93/GB/s The unit economics of Apple Silicon are becoming more compelling with every release of the Mac. The future of AI inference looks more like open weights models (OpenAI open weights model soonTM) run at low batch_size on personal devices.

Alex Cheema

103,604 görüntüleme • 1 yıl önce

A $599 MAC MINI, A 340 YUAN SCREEN, AND $3 TO $5 OF POWER CAN TURN INTO A PRIVATE AI SERVER THAT CUTS THE DUMBEST PART OF A $150 API BILL 00:03 he shows the whole setup on the desk: tiny mac mini, cheap external display, keyboard, cables, and one silent box small enough to hide under the monitor while running local models all day. developers burn paid tokens on the wrong stuff. code formatting, quick summaries, draft emails, cron checks, log cleanup and tiny reviews can eat most of the bill, even when none of it needs a frontier model. ollama on a mac mini changes the math. qwen, llama, gemma or phi can handle the boring repeat work locally, while claude stays for architecture, production code and the problems that actually need expensive reasoning. one box can serve the whole workflow. open webui turns the mac mini into a private chat interface for your phone, laptop and tablet, with local files staying in your room instead of getting shipped to another cloud tab. monthly savings come from the invisible calls. 1,440 cron checks, 200 small summaries, 80 log reviews and dozens of throwaway prompts can move off paid tokens before they quietly become another $150 invoice. bookmark this before your next API bill looks like rent.
0:27

A $599 MAC MINI, A 340 YUAN SCREEN, AND $3 TO $5 OF POWER CAN TURN INTO A PRIVATE AI SERVER THAT CUTS THE DUMBEST PART OF A $150 API BILL 00:03 he shows the whole setup on the desk: tiny mac mini, cheap external display, keyboard, cables, and one silent box small enough to hide under the monitor while running local models all day. developers burn paid tokens on the wrong stuff. code formatting, quick summaries, draft emails, cron checks, log cleanup and tiny reviews can eat most of the bill, even when none of it needs a frontier model. ollama on a mac mini changes the math. qwen, llama, gemma or phi can handle the boring repeat work locally, while claude stays for architecture, production code and the problems that actually need expensive reasoning. one box can serve the whole workflow. open webui turns the mac mini into a private chat interface for your phone, laptop and tablet, with local files staying in your room instead of getting shipped to another cloud tab. monthly savings come from the invisible calls. 1,440 cron checks, 200 small summaries, 80 log reviews and dozens of throwaway prompts can move off paid tokens before they quietly become another $150 invoice. bookmark this before your next API bill looks like rent.

Gipp 🦅

21,848 görüntüleme • 1 ay önce

A 24 BAY DELL POWEREDGE T550 TOWER SERVER FITS IN A HOME OFFICE WITHOUT A RACK, 384TB OF RAW SAS STORAGE HOSTS EVERY OPEN SOURCE LLM EVER RELEASED LOCALLY, THE HOME AI LIBRARY TIER UNDER YOUR MAP 00:25 the reseller spins the chassis around, "it's a 24 bay Dell T550 tower server man, look it's got a boss card for dual NVMe boot SSDs" a refurbished T550 ships at $900-1,100 with single Xeon Silver, 64GB DDR4 ECC and 24 hot swap SAS bays in a tower form factor that fits next to a desk without a server rack 24x 16TB SAS drives at $80 each on eBay equals 384TB raw storage for $1,920, the same array on enterprise Mac Studio Pro tier would cost $35,000 in thunderbolt JBOD enclosures Llama 3.3 70B is 42GB, Qwen3-235B is 110GB, DeepSeek-V3 is 100GB, Mistral Large is 80GB, the entire ollama public model library fits inside 4TB, you can mirror every open weights release for the next decade your map covers compute boxes that swap one model at a time, the T550 is the model warehouse tier that feeds them, a homelab operator wires the tower over 10GbE to a mac mini and the mac never waits 30 seconds to pull a swap the window is open, follow and bookmark before it closes
0:53

A 24 BAY DELL POWEREDGE T550 TOWER SERVER FITS IN A HOME OFFICE WITHOUT A RACK, 384TB OF RAW SAS STORAGE HOSTS EVERY OPEN SOURCE LLM EVER RELEASED LOCALLY, THE HOME AI LIBRARY TIER UNDER YOUR MAP 00:25 the reseller spins the chassis around, "it's a 24 bay Dell T550 tower server man, look it's got a boss card for dual NVMe boot SSDs" a refurbished T550 ships at $900-1,100 with single Xeon Silver, 64GB DDR4 ECC and 24 hot swap SAS bays in a tower form factor that fits next to a desk without a server rack 24x 16TB SAS drives at $80 each on eBay equals 384TB raw storage for $1,920, the same array on enterprise Mac Studio Pro tier would cost $35,000 in thunderbolt JBOD enclosures Llama 3.3 70B is 42GB, Qwen3-235B is 110GB, DeepSeek-V3 is 100GB, Mistral Large is 80GB, the entire ollama public model library fits inside 4TB, you can mirror every open weights release for the next decade your map covers compute boxes that swap one model at a time, the T550 is the model warehouse tier that feeds them, a homelab operator wires the tower over 10GbE to a mac mini and the mac never waits 30 seconds to pull a swap the window is open, follow and bookmark before it closes

Antid

18,526 görüntüleme • 2 ay önce

APPLE SOLD THIS 39.9-POUND TOWER FOR $2,499 IN 2009 - ONE LATCH TURNED THE ENTIRE MACHINE INTO A WORKBENCH. this is the Early 2009 Mac Pro. the video shows the part spec sheets rarely capture. pull one latch and the aluminum side panel comes away. the memory, graphics card, drive bays and expansion slots are immediately visible. no hidden screws before you can inspect the machine. no loose SATA cables hanging from every drive. the base model shipped with: 2.66GHz quad-core Xeon 3GB of 1066MHz DDR3 ECC memory 640GB SATA hard drive GeForce GT 120 with 512MB of memory four PCIe 2.0 slots. the quad-core model supported up to 16GB of RAM. storage was handled by four cable-free carriers that connected directly inside the chassis. the case also left space for two optical drives. the rear panel carried hardware that now feels like an archive: dual Gigabit Ethernet optical audio USB 2.0 FireWire 800. the GT 120 offered Mini DisplayPort and dual-link DVI. install four of those cards and Apple rated the tower for up to eight 30-inch displays. the enclosure measured 20.1 inches tall and weighed almost 40 pounds before serious upgrades. this was not a compact desktop. it was a machine designed to be opened, understood and rebuilt. honest line: the Xeon, GT 120, SATA drive and USB 2.0 ports are ancient by modern standards. beautiful serviceability does not make old hardware fast. those parts aged. the enclosure did not. 17 years later, the most impressive component is still the case. bookmark & watch today ↓
0:53

APPLE SOLD THIS 39.9-POUND TOWER FOR $2,499 IN 2009 - ONE LATCH TURNED THE ENTIRE MACHINE INTO A WORKBENCH. this is the Early 2009 Mac Pro. the video shows the part spec sheets rarely capture. pull one latch and the aluminum side panel comes away. the memory, graphics card, drive bays and expansion slots are immediately visible. no hidden screws before you can inspect the machine. no loose SATA cables hanging from every drive. the base model shipped with: 2.66GHz quad-core Xeon 3GB of 1066MHz DDR3 ECC memory 640GB SATA hard drive GeForce GT 120 with 512MB of memory four PCIe 2.0 slots. the quad-core model supported up to 16GB of RAM. storage was handled by four cable-free carriers that connected directly inside the chassis. the case also left space for two optical drives. the rear panel carried hardware that now feels like an archive: dual Gigabit Ethernet optical audio USB 2.0 FireWire 800. the GT 120 offered Mini DisplayPort and dual-link DVI. install four of those cards and Apple rated the tower for up to eight 30-inch displays. the enclosure measured 20.1 inches tall and weighed almost 40 pounds before serious upgrades. this was not a compact desktop. it was a machine designed to be opened, understood and rebuilt. honest line: the Xeon, GT 120, SATA drive and USB 2.0 ports are ancient by modern standards. beautiful serviceability does not make old hardware fast. those parts aged. the enclosure did not. 17 years later, the most impressive component is still the case. bookmark & watch today ↓

Grimmer

224,481 görüntüleme • 14 gün önce

1 AI character clip becomes 50 ads without a single actor or reshoot. 100% generated. The face isn’t real. The pipeline is. Here’s the build, start to finish. Part 1 - Make the character. Generate the face on a node canvas. Lock the identity so it holds across every shot. Part 2 - Drop in the product. One node. The product sits in her hands, on the desk, wherever you point it. Part 3 - Animate. Seedance 2.0 turns the still into a moving clip. Lighting, motion, room - all baked in. Part 4 - The swap nodes. This is the part nobody shows. Build nodes that replace one thing at a time. Character. Outfit. Product. Nothing else moves. Swap the product → new ad. Swap the outfit → new ad. Swap the face → new ad. Same 6 seconds. Same light. Same motion. 50 variants before lunch. Old way: hire talent, film, reshoot for every SKU, edit each cut. New way: 1 canvas, swap 1 node, export. The cost of variant 2 used to be a full shoot. Now it’s a click. Film once. Swap forever.
0:45

1 AI character clip becomes 50 ads without a single actor or reshoot. 100% generated. The face isn’t real. The pipeline is. Here’s the build, start to finish. Part 1 - Make the character. Generate the face on a node canvas. Lock the identity so it holds across every shot. Part 2 - Drop in the product. One node. The product sits in her hands, on the desk, wherever you point it. Part 3 - Animate. Seedance 2.0 turns the still into a moving clip. Lighting, motion, room - all baked in. Part 4 - The swap nodes. This is the part nobody shows. Build nodes that replace one thing at a time. Character. Outfit. Product. Nothing else moves. Swap the product → new ad. Swap the outfit → new ad. Swap the face → new ad. Same 6 seconds. Same light. Same motion. 50 variants before lunch. Old way: hire talent, film, reshoot for every SKU, edit each cut. New way: 1 canvas, swap 1 node, export. The cost of variant 2 used to be a full shoot. Now it’s a click. Film once. Swap forever.

HodlReaper

21,188 görüntüleme • 2 ay önce

DELL ASUS ACER AND GIGABYTE ALL SHIPPED $2,999 DGX SPARK CLONES IN THE SAME QUARTER, SAMSUNG GEN 5 SSD CHOICE CAUSES 2X PERFORMANCE GAPS, THE LOCAL AI HARDWARE MAP JUST GREW BY FOUR FRONTIER TIER OPTIONS 02:13 the reviewer flips through the spec sheets, "we saw major differences in the SSD, some are using Gen 4 SSDs which will slow these platforms down, others have Gen 5 Samsung drives, Samsung is the leader by almost a factor of two" NVIDIA's GB10 Grace Blackwell reference board got picked up by Dell, Asus, Acer and Gigabyte in the same quarter, four $2,999 mini boxes with 128GB unified memory and 1 PFLOP of AI throughput from competing OEMs the Asus version runs coolest across GPU, CPU and SSD thanks to an unpainted bottom plate and a copper heatsink element, the Acer leads on price-to-perf, the Dell honeycomb intake actually restricts airflow slightly, the gigabyte sits middle of pack Samsung Gen 5 versus Gen 4 inside the same chassis causes a 2x read-write gap for the exact same $2,999 sticker, the buyer who reads the SSD spec sheet gets a 70B model loading in 4 seconds, the one who doesn't waits 8 your serie's frontier tier was the $1,700 EVO-X2, four DGX Spark OEM clones at $2,999 extend the map upward, the local AI hardware boom is now staffed by every major PC vendor not just AMD and apple, the category fully arrived bookmark this and read the article below
2:50

DELL ASUS ACER AND GIGABYTE ALL SHIPPED $2,999 DGX SPARK CLONES IN THE SAME QUARTER, SAMSUNG GEN 5 SSD CHOICE CAUSES 2X PERFORMANCE GAPS, THE LOCAL AI HARDWARE MAP JUST GREW BY FOUR FRONTIER TIER OPTIONS 02:13 the reviewer flips through the spec sheets, "we saw major differences in the SSD, some are using Gen 4 SSDs which will slow these platforms down, others have Gen 5 Samsung drives, Samsung is the leader by almost a factor of two" NVIDIA's GB10 Grace Blackwell reference board got picked up by Dell, Asus, Acer and Gigabyte in the same quarter, four $2,999 mini boxes with 128GB unified memory and 1 PFLOP of AI throughput from competing OEMs the Asus version runs coolest across GPU, CPU and SSD thanks to an unpainted bottom plate and a copper heatsink element, the Acer leads on price-to-perf, the Dell honeycomb intake actually restricts airflow slightly, the gigabyte sits middle of pack Samsung Gen 5 versus Gen 4 inside the same chassis causes a 2x read-write gap for the exact same $2,999 sticker, the buyer who reads the SSD spec sheet gets a 70B model loading in 4 seconds, the one who doesn't waits 8 your serie's frontier tier was the $1,700 EVO-X2, four DGX Spark OEM clones at $2,999 extend the map upward, the local AI hardware boom is now staffed by every major PC vendor not just AMD and apple, the category fully arrived bookmark this and read the article below

starmex

17,573 görüntüleme • 2 ay önce

This Chinese guy created agents in Claude Code for MCP servers and single-handedly serves 6 marketing agencies a month from one iPhone, earning $5,000 from each. Inside he runs a pipeline of 7 agents on Claude Sonnet 4.6 that every Monday pulls a scan of the tech stack from a selected agency, develops an MCP server for its ad accounts, and over the course of a week brings it to production code ready to connect to Claude Desktop. No DevOps, no senior developer, no project manager. Just a Mac Mini in a work corner, an iPhone in the pocket, and a single API key. And traditional dev shops keep 5 people on project rates for the same contract, while his entire P&L is tokens, dirt-cheap hosting on Cloudflare, and Calendly. 7 agents run under a shared orchestrator-router and burn about 5 million tokens a day, which in the API bill comes out to $540 a month. The Mac Mini itself sits at home and keeps the entire orchestrator running 24/7, and from the iPhone the owner connects to it through a secure remote terminal and sees the output of any session right on the smartphone screen, wherever he happens to be. His starting system prompt looks like this: "you run a solo shop for custom MCP servers for marketing agencies. you hand out read-only tasks to 6 sub-agents and own all commits and shipping yourself. sub-agents: // Hunter (finds marketing agencies of 15 to 60 people that have no MCP access to Google Ads, Meta Ads, TikTok Ads, and HubSpot) // Mapper (pulls their tech stack, identifies 3 to 5 integration pains, and simultaneously writes the technical spec for the server: which tools, resources, and prompts to export through MCP, which auth flow and rate limit) // Coder (generates an MCP server in Python through the MCP SDK, deploys 8 to 15 tools for ad accounts and CRM) // Validator (connects the server to Claude Desktop, runs real client API keys in a sandbox, and checks for compliance with the MCP spec) // Shipper (writes a README, integration guide, deployment manual, packages the server, and hosts it on Cloudflare Workers or pushes to the GitHub of the client) // Mobile (always online on the iPhone, books demo calls in Calendly, picks up hot fixes, and confirms contracts through a secure remote terminal to the Mac Mini). only 1 owner agent works on 1 contract, no overlaps. you pull the owner out of observation mode only when a deal goes above $7,500 or the test coverage of the server drops below 85%." This prompt gives the system an understanding of its role and the limits of intervention from the very first line. It knows it is supposed to find agencies on its own. It knows it is supposed to bring every MCP server to production on its own. It knows it connects the live owner only on large deals or when the tests do not converge. → The pipeline runs without breaks, day or night → Hunter goes through about 130 marketing agencies on LinkedIn and Clutch per day → Mapper rolls out 4 audit reports with the tech stack and a final spec for each → Coder writes 1 to 2 MCP servers per week in Python with 8 to 15 tools → Validator validates every server through Claude Desktop with real client API keys → Shipper rolls out the full documentation package and pushes the finished product to Cloudflare Workers or the GitHub of the client And only when a contract breaks $7,500 or test coverage drops below 85% does the orchestrator pull the owner from whatever he is doing. And when the owner at that moment is behind the wheel or at a meeting in a coworking space, the Mobile agent in his iPhone picks up 1 contract in progress: confirms a meeting with the agency CMO in Calendly, opens a live demo of the MCP server through a secure terminal to the Mac Mini, and writes the test result to the shared state. The owner just swipes "approve" and in 15 minutes joins the Zoom demo. The fresh system log from last Wednesday looks like this: "hunter report: 132 agencies checked on LinkedIn and Clutch, 19 without MCP integrations, 8 with active requests for AI tooling in job posts, 4 with an open Q4 budget. passing to mapper." "coder: MCP server for Northwave Performance Marketing built in Python, 11 tools for Google Ads, Meta Ads, and GA4, 320 lines of code. exported to /Users/dev/mcp-shop/clients/northwave/server.py. validator connecting to Claude Desktop." "validator: 11 tools passed validation through Claude Desktop, test coverage 92%, average latency 380 ms. passing to shipper." "eval flag: contract with Pacific Reach Agency at $8,200 exceeds the approved limit of $7,500. sending for manual review." In his work setup there is no cloud server, no external team, and not even a separate office. At home sits a Mac Mini with a sandbox at /Users/dev/mcp-shop, on top runs an MCP router with a single API key to Claude, and the same key is forwarded to a secure terminal on the iPhone. Out of everything I have seen this year, this is the cleanest solo shop for custom MCP servers for marketing agencies: $540 a month on the API, about $30,000 into the account, and between them 7 system prompts, 1 Mac Mini in a work corner, and 1 iPhone that never leaves the pocket.
0:33

This Chinese guy created agents in Claude Code for MCP servers and single-handedly serves 6 marketing agencies a month from one iPhone, earning $5,000 from each. Inside he runs a pipeline of 7 agents on Claude Sonnet 4.6 that every Monday pulls a scan of the tech stack from a selected agency, develops an MCP server for its ad accounts, and over the course of a week brings it to production code ready to connect to Claude Desktop. No DevOps, no senior developer, no project manager. Just a Mac Mini in a work corner, an iPhone in the pocket, and a single API key. And traditional dev shops keep 5 people on project rates for the same contract, while his entire P&L is tokens, dirt-cheap hosting on Cloudflare, and Calendly. 7 agents run under a shared orchestrator-router and burn about 5 million tokens a day, which in the API bill comes out to $540 a month. The Mac Mini itself sits at home and keeps the entire orchestrator running 24/7, and from the iPhone the owner connects to it through a secure remote terminal and sees the output of any session right on the smartphone screen, wherever he happens to be. His starting system prompt looks like this: "you run a solo shop for custom MCP servers for marketing agencies. you hand out read-only tasks to 6 sub-agents and own all commits and shipping yourself. sub-agents: // Hunter (finds marketing agencies of 15 to 60 people that have no MCP access to Google Ads, Meta Ads, TikTok Ads, and HubSpot) // Mapper (pulls their tech stack, identifies 3 to 5 integration pains, and simultaneously writes the technical spec for the server: which tools, resources, and prompts to export through MCP, which auth flow and rate limit) // Coder (generates an MCP server in Python through the MCP SDK, deploys 8 to 15 tools for ad accounts and CRM) // Validator (connects the server to Claude Desktop, runs real client API keys in a sandbox, and checks for compliance with the MCP spec) // Shipper (writes a README, integration guide, deployment manual, packages the server, and hosts it on Cloudflare Workers or pushes to the GitHub of the client) // Mobile (always online on the iPhone, books demo calls in Calendly, picks up hot fixes, and confirms contracts through a secure remote terminal to the Mac Mini). only 1 owner agent works on 1 contract, no overlaps. you pull the owner out of observation mode only when a deal goes above $7,500 or the test coverage of the server drops below 85%." This prompt gives the system an understanding of its role and the limits of intervention from the very first line. It knows it is supposed to find agencies on its own. It knows it is supposed to bring every MCP server to production on its own. It knows it connects the live owner only on large deals or when the tests do not converge. → The pipeline runs without breaks, day or night → Hunter goes through about 130 marketing agencies on LinkedIn and Clutch per day → Mapper rolls out 4 audit reports with the tech stack and a final spec for each → Coder writes 1 to 2 MCP servers per week in Python with 8 to 15 tools → Validator validates every server through Claude Desktop with real client API keys → Shipper rolls out the full documentation package and pushes the finished product to Cloudflare Workers or the GitHub of the client And only when a contract breaks $7,500 or test coverage drops below 85% does the orchestrator pull the owner from whatever he is doing. And when the owner at that moment is behind the wheel or at a meeting in a coworking space, the Mobile agent in his iPhone picks up 1 contract in progress: confirms a meeting with the agency CMO in Calendly, opens a live demo of the MCP server through a secure terminal to the Mac Mini, and writes the test result to the shared state. The owner just swipes "approve" and in 15 minutes joins the Zoom demo. The fresh system log from last Wednesday looks like this: "hunter report: 132 agencies checked on LinkedIn and Clutch, 19 without MCP integrations, 8 with active requests for AI tooling in job posts, 4 with an open Q4 budget. passing to mapper." "coder: MCP server for Northwave Performance Marketing built in Python, 11 tools for Google Ads, Meta Ads, and GA4, 320 lines of code. exported to /Users/dev/mcp-shop/clients/northwave/server.py. validator connecting to Claude Desktop." "validator: 11 tools passed validation through Claude Desktop, test coverage 92%, average latency 380 ms. passing to shipper." "eval flag: contract with Pacific Reach Agency at $8,200 exceeds the approved limit of $7,500. sending for manual review." In his work setup there is no cloud server, no external team, and not even a separate office. At home sits a Mac Mini with a sandbox at /Users/dev/mcp-shop, on top runs an MCP router with a single API key to Claude, and the same key is forwarded to a secure terminal on the iPhone. Out of everything I have seen this year, this is the cleanest solo shop for custom MCP servers for marketing agencies: $540 a month on the API, about $30,000 into the account, and between them 7 system prompts, 1 Mac Mini in a work corner, and 1 iPhone that never leaves the pocket.

Blaze

55,926 görüntüleme • 3 ay önce

One guy keeps a farm of Mac minis on his desk and says each $600 box brings him $2,000 a month while he sleeps. AND THE HARDWARE ACTUALLY WORKS. But the number is not even the interesting part. The broken part is HOW: his AI no longer sits in a chat window. It sees the screen, moves the mouse itself, types and clicks the interface like a human at a computer. That is it. While most people still run AI in a chat and ask it for text, he sat Claude down right at the computer and put it to work with its hands. He automated not a single task but the workplace itself. How it actually works: on every Mac mini Claude runs with computer use turned on and the official Claude API docs spell it out: screenshot capture, mouse control, keyboard input, desktop automation. The agent opens the browser and the apps itself and runs the boring routine on a schedule: pulls leads, fills the CRM, checks orders, runs QA on the site. One box, one quiet worker that does not sleep and does not ask for a salary. His math is simple: a Mac mini is $600 once, Claude Max is $200 a month, and a live white-collar worker on the same routine costs a business $4,000 and up. So he rents out each node to a client as an AI worker for about $2,000 and 6 Mac minis come out to around $12,000 a month with costs a bit over $1,000 on subscriptions. But the $12,000 is his projection not a revenue dashboard: the video has no client, no task log, no working automation at all. The real asset here is not the stack of hardware but the one repeatable process the agent actually closes. Because a Mac mini on its own earns nothing. The money shows up exactly where the boring browser routine used to be done by hand for a salary and now you can hand it to an agent for the price of a subscription. Computer use is still in beta, almost nobody builds a service on it and the demand for cheap GUI routine is huge. The window is open for literally the next few months. Most people will watch this, laugh at the "$600 AI worker" and close it. And the ones who actually put an agent on one boring task and grind it into a repeat will ride this wave while it is still empty. Would you sit an AI right at your own computer on the boring routine or are you still clicking through it by hand?
1:05

One guy keeps a farm of Mac minis on his desk and says each $600 box brings him $2,000 a month while he sleeps. AND THE HARDWARE ACTUALLY WORKS. But the number is not even the interesting part. The broken part is HOW: his AI no longer sits in a chat window. It sees the screen, moves the mouse itself, types and clicks the interface like a human at a computer. That is it. While most people still run AI in a chat and ask it for text, he sat Claude down right at the computer and put it to work with its hands. He automated not a single task but the workplace itself. How it actually works: on every Mac mini Claude runs with computer use turned on and the official Claude API docs spell it out: screenshot capture, mouse control, keyboard input, desktop automation. The agent opens the browser and the apps itself and runs the boring routine on a schedule: pulls leads, fills the CRM, checks orders, runs QA on the site. One box, one quiet worker that does not sleep and does not ask for a salary. His math is simple: a Mac mini is $600 once, Claude Max is $200 a month, and a live white-collar worker on the same routine costs a business $4,000 and up. So he rents out each node to a client as an AI worker for about $2,000 and 6 Mac minis come out to around $12,000 a month with costs a bit over $1,000 on subscriptions. But the $12,000 is his projection not a revenue dashboard: the video has no client, no task log, no working automation at all. The real asset here is not the stack of hardware but the one repeatable process the agent actually closes. Because a Mac mini on its own earns nothing. The money shows up exactly where the boring browser routine used to be done by hand for a salary and now you can hand it to an agent for the price of a subscription. Computer use is still in beta, almost nobody builds a service on it and the demand for cheap GUI routine is huge. The window is open for literally the next few months. Most people will watch this, laugh at the "$600 AI worker" and close it. And the ones who actually put an agent on one boring task and grind it into a repeat will ride this wave while it is still empty. Would you sit an AI right at your own computer on the boring routine or are you still clicking through it by hand?

Sorven

12,259 görüntüleme • 2 ay önce

A Stanford 26-year-old spent 2 years turning 11,400 Obsidian notes into a neural net that finishes his sentences. It started as a folder called “misc” with 43 PDF in it. Most vaults die around 300 notes, because nothing connects and nothing comes back roughly 90% of what you save gets read once, on the day you save it. He fixed it by treating retrieval as the product and storage as the leftovers. Phase 1: Atomize (months 1-3) One idea per note, 200 words max, title written as a claim instead of a topic. “Attention is a filter, not a spotlight” beats “Notes on attention.” He rewrote 1,200 old notes this way and the vault shrank from 2,800 files to 1,600 usable ones. Phase 2: Embed locally (months 4-8) Ollama running nomic-embed-text on a Mac Mini M4, every note chunked at 512 tokens with 64-token overlap, all of it dumped into a local ChromaDB. 11,400 notes became 38,000 vectors and 1.2 GB on disk. Query time 0.4 seconds, cost $0 a month, nothing leaving the machine. Phase 3: Kill the hallucinations (months 9-14) Plain cosine search returned garbage about 30% of the time, so he bolted on a re-ranker and one hard rule: every retrieved chunk carries its source note title into the answer, and no citation means no answer. Wrong recalls fell from 1 in 4 to 1 in 30. Phase 4: Make it speak first (months 15-24) A nightly job reads the day’s writing, pulls the 5 oldest notes with the highest similarity, and drops 3 questions into tomorrow’s daily note. He stopped searching the vault somewhere in month 17 now it opens the conversation before he does. Before: 2,800 notes, 0 reused, 6 weeks per paper draft. After: 11,400 notes, 60-70 surfaced every week unasked, 9 days per draft. The whole stack is 4 pieces Obsidian, Ollama, ChromaDB, and a 40-line Python script that runs at 2 AM. Total software spend across 24 months: $0. Most people build a second brain to store things they will never open again. He stopped writing to remember. He writes so the machine can remind him.
0:26

A Stanford 26-year-old spent 2 years turning 11,400 Obsidian notes into a neural net that finishes his sentences. It started as a folder called “misc” with 43 PDF in it. Most vaults die around 300 notes, because nothing connects and nothing comes back roughly 90% of what you save gets read once, on the day you save it. He fixed it by treating retrieval as the product and storage as the leftovers. Phase 1: Atomize (months 1-3) One idea per note, 200 words max, title written as a claim instead of a topic. “Attention is a filter, not a spotlight” beats “Notes on attention.” He rewrote 1,200 old notes this way and the vault shrank from 2,800 files to 1,600 usable ones. Phase 2: Embed locally (months 4-8) Ollama running nomic-embed-text on a Mac Mini M4, every note chunked at 512 tokens with 64-token overlap, all of it dumped into a local ChromaDB. 11,400 notes became 38,000 vectors and 1.2 GB on disk. Query time 0.4 seconds, cost $0 a month, nothing leaving the machine. Phase 3: Kill the hallucinations (months 9-14) Plain cosine search returned garbage about 30% of the time, so he bolted on a re-ranker and one hard rule: every retrieved chunk carries its source note title into the answer, and no citation means no answer. Wrong recalls fell from 1 in 4 to 1 in 30. Phase 4: Make it speak first (months 15-24) A nightly job reads the day’s writing, pulls the 5 oldest notes with the highest similarity, and drops 3 questions into tomorrow’s daily note. He stopped searching the vault somewhere in month 17 now it opens the conversation before he does. Before: 2,800 notes, 0 reused, 6 weeks per paper draft. After: 11,400 notes, 60-70 surfaced every week unasked, 9 days per draft. The whole stack is 4 pieces Obsidian, Ollama, ChromaDB, and a 40-line Python script that runs at 2 AM. Total software spend across 24 months: $0. Most people build a second brain to store things they will never open again. He stopped writing to remember. He writes so the machine can remind him.

West Lord

170,060 görüntüleme • 1 ay önce

People made fun of Alex Finn for buying three Mac Studios to run AI at home. Then Fable got banned for a week, GLM 5.2 dropped, and those exact Mac Studios started reselling for 4x what he paid. He showed me how he built his home AI lab from scratch. Here's the playbook: 1) The hardware. three 512GB Mac Studios, an NVIDIA DGX Spark, a custom RTX 5090 build, and a few Mac Minis. ~$30k all in. 2) The buying framework... - Mac Studio: huge memory, runs GLM 5.2 (open weights, near Opus 4.8 on benchmarks), but slow. - DGX Spark ($4,800): the sweet spot for most people. - RTX 5090: smaller models at blazing speed (Qwen's 29B now hits Sonnet 4 level). 3) Tailscale networks every machine into one private network with root access to each other. Only one machine is plugged into a monitor. 4) A Nous Research Hermes agent is his IT guy. New model drops? It SSHs into the right box, loads 5 candidates, runs evals overnight, and reports back which task belongs on which machine. Alex has literally never loaded a model himself. 5) The whole point: achieving "ambient intelligence." Always-on jobs that would bankrupt you on per-token billing. A security sweep of his API endpoints every hour. Code optimization every 20 minutes. Database anomaly & churn detection. Hourly scraping of X, Reddit & Hacker News for business opportunities. 6) Running those workloads on frontier models would cost thousands a month. His actual cost: ~$60 more in electricity. 7) Btw he's not anti-frontier. He still maxes out his Claude plan. The way he sees it: frontier is for hard thinking, local is for the foot soldiers that never sleep. 8) "We own everything except for the intelligence. Why can't we own the intelligence?" 9) He thinks frontier-level intelligence runs on consumer hardware within 6 months.
36:48

People made fun of Alex Finn for buying three Mac Studios to run AI at home. Then Fable got banned for a week, GLM 5.2 dropped, and those exact Mac Studios started reselling for 4x what he paid. He showed me how he built his home AI lab from scratch. Here's the playbook: 1) The hardware. three 512GB Mac Studios, an NVIDIA DGX Spark, a custom RTX 5090 build, and a few Mac Minis. ~$30k all in. 2) The buying framework... - Mac Studio: huge memory, runs GLM 5.2 (open weights, near Opus 4.8 on benchmarks), but slow. - DGX Spark ($4,800): the sweet spot for most people. - RTX 5090: smaller models at blazing speed (Qwen's 29B now hits Sonnet 4 level). 3) Tailscale networks every machine into one private network with root access to each other. Only one machine is plugged into a monitor. 4) A Nous Research Hermes agent is his IT guy. New model drops? It SSHs into the right box, loads 5 candidates, runs evals overnight, and reports back which task belongs on which machine. Alex has literally never loaded a model himself. 5) The whole point: achieving "ambient intelligence." Always-on jobs that would bankrupt you on per-token billing. A security sweep of his API endpoints every hour. Code optimization every 20 minutes. Database anomaly & churn detection. Hourly scraping of X, Reddit & Hacker News for business opportunities. 6) Running those workloads on frontier models would cost thousands a month. His actual cost: ~$60 more in electricity. 7) Btw he's not anti-frontier. He still maxes out his Claude plan. The way he sees it: frontier is for hard thinking, local is for the foot soldiers that never sleep. 8) "We own everything except for the intelligence. Why can't we own the intelligence?" 9) He thinks frontier-level intelligence runs on consumer hardware within 6 months.

Alex Lieberman

57,764 görüntüleme • 1 ay önce