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@jtk@infosec.exchange
2026-03-02 01:08:41

A few of DoD's BGP withdrawals I looked at are covered by larger prefixes. I am not intimately familiar with these networks, but I think it would be a good guess to say these BGP updates reflect something related to the Israel-US strikes on Iran.
noc.social/@dataplane/11615528

@jtk@infosec.exchange
2026-03-31 22:08:16

New blog post: Journeys in Hosting 2/x - OS template considerations
dataplane.org/jtk/blog/2026/03

@aredridel@kolektiva.social
2026-01-22 02:57:16

How it started:
Too many authentication failures
How it's going:
create mode 120000 dotfiles/ssh/SHA256:APNBDduY7Wz2GYjHV9OJlRl4SegLIJinpdKwb7rqTSM.pub
create mode 100644 dotfiles/ssh/SHA256:PR6dOdv4BeIa_Bgln8GVISrgS2OPoC_S8ptW_x9_x_Y.pub
create mode 100644 dotfiles/ssh/SHA256:b9lcI3kl4Grt7_T8H463HD6vOIuc0DRn0KJOvtfZLgU.pub
create mode 100644 dotfiles/ssh/SHA256:oLXRyMj8qKf5eyHLADbSD8L-xNQrAq0QblnC8O0xu1M.pub
create mode 100644 dotfiles/ssh/SHA256:pnd4AkiTzyAifh3RI8hkPfgMNLBVoyz9MCJBWTYO1qE.pub

@BBC6MusicBot@mastodonapp.uk
2026-03-01 20:08:51

πŸ‡ΊπŸ‡¦ #NowPlaying on #BBC6Music's #StuartMaconiesFreakZone
Datblygu:
🎡 Santa a Barbara
#Datblygu
open.spotify.com/track/30Vrvpu

@arXiv_csCL_bot@mastoxiv.page
2026-03-31 10:11:22

Structural-Ambiguity-Aware Translation from Natural Language to Signal Temporal Logic
Kosei Fushimi, Kazunobu Serizawa, Junya Ikemoto, Kazumune Hashimoto
arxiv.org/abs/2603.28426 arxiv.org/pdf/2603.28426 arxiv.org/html/2603.28426
arXiv:2603.28426v1 Announce Type: new
Abstract: Signal Temporal Logic (STL) is widely used to specify timed and safety-critical tasks for cyber-physical systems, but writing STL formulas directly is difficult for non-expert users. Natural language (NL) provides a convenient interface, yet its inherent structural ambiguity makes one-to-one translation into STL unreliable. In this paper, we propose an \textit{ambiguity-preserving} method for translating NL task descriptions into STL candidate formulas. The key idea is to retain multiple plausible syntactic analyses instead of forcing a single interpretation at the parsing stage. To this end, we develop a three-stage pipeline based on Combinatory Categorial Grammar (CCG): ambiguity-preserving $n$-best parsing, STL-oriented template-based semantic composition, and canonicalization with score aggregation. The proposed method outputs a deduplicated set of STL candidates with plausibility scores, thereby explicitly representing multiple possible formal interpretations of an ambiguous instruction. In contrast to existing one-best NL-to-logic translation methods, the proposed approach is designed to preserve attachment and scope ambiguity. Case studies on representative task descriptions demonstrate that the method generates multiple STL candidates for genuinely ambiguous inputs while collapsing unambiguous or canonically equivalent derivations to a single STL formula.
toXiv_bot_toot

@kexpmusicbot@mastodonapp.uk
2026-02-11 00:27:20

πŸ‡ΊπŸ‡¦ #NowPlaying on KEXP's #DriveTime
Death Valley Girls:
🎡 Magic Powers
#DeathValleyGirls
deathvalleygirls.bandcamp.com/
open.spotify.com/track/4wpXRM0

@Techmeme@techhub.social
2026-02-18 19:31:01

Efficient Computer, which is developing AI chips with a "spatial dataflow" architecture to minimize energy consumption, raised a $60M Series A (Mike Wheatley/SiliconANGLE)
siliconangle.com/2026/02/18/ef

@migueldeicaza@mastodon.social
2026-01-15 03:15:07

In this world nothing can be said to be certain except death, taxes and LLM will dutifuly exfiltrate your data via a hidden prompt:
promptarmor.com/resources/clau