[re: war]
@whitequark oh wtf that's, that's not a smol one,,
also uhhhh.. huh?? those sure are two results
Val Packett 🧉
@val.packett.cool
62 followers 0 following 812 posts
Purple is my natural hair color. I have strong opinions about software and sometime I even get to make them reality. Same for the state of the world in […] 🌉 bridged from ⁂ social.treehouse.systems/@valpackett, follow @ap.brid.gy to interact
!["NSFW ASS KNUCCLES" (white-on-red NSFW badge covering part of the "BRASS KNUCCLES" [sic] label inside of the image)](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:sikj6mz3b3oee7dhnjveokn6/bafkreig2ax3vhfkfh2o6rhhnp32i7bu3a5cuzzlrwjb6o2jqjxkgrmihyq)
![PulseView window showing decoded USB packets, with SETUP ADDR 0 EP 0 and DATA0 [ 80 06 00 01 00 00 40 00 ] and then short weird things that show up with "Packet: Invalid: Invalid packet (shorter than 8 bits)" before another repeat of that data](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:sikj6mz3b3oee7dhnjveokn6/bafkreifoylpjade3e3re4w4obe5nh4an2xmxrc4tsmujlf7s5ekq73b7xm)
![March 23, 2026 by Jean-Luc Aufranc (CNXSoft) - 3 Comments
CIX ClawCore Armv9.2 CPU family targets OpenClaw deployments
OpenClaw was just introduced a few months ago, but we’ve already seen several low-footprint implementations, and some companies even ship mini PCs preloaded with OpenClaw. But today, I was just informed that CIX had gone further, and introduced the ClawCore Armv9.2 CPU family specifically designed/optimized for OpenClaw. The family will be comprised of three main SKUs: ClawCore-P (勁螯芯 “Powerful Claw”) – High-performance model with 12-core CPU @ 3.2GHz, Immortalis-G720 GPU, 45 TOPS AI compute, and support for up to 64GB LPDDR5 RAM. Aimed at high-parallelism, large-capacity scenarios. Shipping starts now in March 2026. ClawCore-A (智螯芯 “AI/Smart Claw”) – Octa-core CPU @ 3.0GHz, 80 TOPS AI compute (expandable to 200 TOPS via PCIe AI card), up to 64GB LPDDR5. It’s designed for 24/7 use, supports full-chain ECC, hardware security (encryption/key management), and enables up to 50% reduction in model token costs via local inference. In practise, 80 to 90% of requests […]](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:sikj6mz3b3oee7dhnjveokn6/bafkreiggjifjypqoprgmqg753ps6g4egrwdcvmdgaphxrbb452gwwboy5e)
