David Lev Wilson

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David Lev Wilson

David Lev Wilson

@DavyPoosky

Learning Linux and AI from the ground up and sharing the progress. Occasional ukulele legerdemain.

Austin, TX Katılım Haziran 2026
171 Takip Edilen7 Takipçiler
David Lev Wilson
David Lev Wilson@DavyPoosky·
the 6000 pro will give you considerably better inference speed, but you won't be able to run nearly as large of models. What I've been asking myself, also trying to make this decision: would you rather sit there and wait a little longer for shit to generate, or get billions more parameters?
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Rider Harrison
Rider Harrison@RiderHarrison1·
@0xSero But the real question is 2 or 3 of these or a 6000 pro?
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0xSero
0xSero@0xSero·
Elite device. Stacks amazing Low power High memory Decent price
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PicoCreator - AI builder @ 🇸🇬 🔜 🌉
Surprised we have yet to see a robotics startup pitching a household rail system, which skips all the current hardware problems of batteries and legs This lets it focus on the MVP, doing chores (in house), and hands.
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Chamath Palihapitiya
@bryan_johnson Challenging yourself, feeding yourself, growing yourself, crushing your enemies’ hopes and dreams.
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Spencer Shulem
Spencer Shulem@Spshulem·
“So you spent $40K to run GLM 5.2 locally?” “Yes, Dave” “And you did all this to save $20 a month on Cursor” “Thats right, Dave”
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David Lev Wilson
David Lev Wilson@DavyPoosky·
@mike64_t Is this still mostly true on architectures that have more unified memory between the CPU and GPU?
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mike
mike@mike64_t·
Everybody should read this because it tells you how opinionated the GPU is about how exactly it wants work to be run, and taken to its logical conclusion it implies that e.g. your CPU-offloaded optimizer is not at liberty to run eagerly, but sit behind a message pump waiting for QMD sem-sets. It's perversely the *GPU* driving the *CPU*, not the other way around. The CPU has dispatched work statically, yielded control to the GPU and then aiding to preserve the CUDA graph dependency model facade as best as possible. cuGraphAddBatchMemOpNode with WRITE/WAIT_VALUE is really all you need here from an api perspective.
SzymonOzog@SzymonOzog_

Saturday reading: "What happens when you run a CUDA kernel" - very cool blogpost on the details about the CPU<->GPU communications required for lauching a kernel

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Ehsan Pajouheshgar
Ehsan Pajouheshgar@Esychology·
Neural CAs are amazing, but they've never scaled past low resolution. We propose a simple solution that allows an ~8x resolution boost with minimal extra parameters. The core idea: Treat cells as local neural fields instead of pixels. Try the demo: cells2pixels.github.io 🧵
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Naval
Naval@naval·
Happy Birthday America, Land of the Free. Don’t give up on the First, Second, Fourth, and Ninth Amendments. They’re unique, and your freedom - and the worlds’ - depends on them.
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David Lev Wilson
David Lev Wilson@DavyPoosky·
Hi! I’m Dave. Follow me along my journey of making music and learning AI
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