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@Techmeme@techhub.social
2026-02-17 20:12:50

Google schedules I/O 2026 for May 19 to 20 in Mountain View, teasing the "latest AI breakthroughs and updates" in Gemini, Android, and more (Abner Li/9to5Google)
9to5google.com/2026/02/17/goog

Google I/O 2026 set for May 19-20
Following the interactive puzzle this morning, Google has announced that I/O 2026 is taking place May 19-20...

@toxi@mastodon.thi.ng
2025-11-19 15:05:19

#ReleaseWednesday — Thanks to a user suggestion, I've added support for declarative canvas pixel density adjustments in the following packages:
- thi.ng/hiccup-canvas
-

Hiccup shape tree renderer for vanilla Canvas 2D contexts

@relcfp@mastodon.social
2026-01-17 06:10:24

H-Net Job Guide Weekly Report for H-HOAC: 4 January - 11 January
ift.tt/pSsL9Io
CFP: [FRISTVERLÄNGERUNG] Variations 28/2021: Gender through technology (25.09.2021) Call…
via Input 4 RELCFP

H-Net Job Guide Weekly Report for H-HOAC: 4 January - 11 January | H-Net
The following jobs were posted to the H-Net Job Guide from 4 January to 11 January. These job postings are included here based on the categories selected by the network editors for H-Announce. See the H-Net job guide web site at https://www.h-net.org/jobs/ for more information. To contact the Job Guide, write to jobguide@mail.h-net.org or call +1-517-432-5134 between 9 AM and 5 PM US Eastern time.

@aardrian@toot.cafe
2025-12-04 16:00:57

My work days feel more and more like people outwardly employing Pascal’s Wager when talking about genAI, LLMs, agentic whatever fake-AI silliness. Saying the words for their bosses but not feeling it otherwise.
PAIscal’s Wager? Pascal’s wAIger? PascaLLM’s wager?

@Erikmitk@mastodon.gamedev.place
2026-01-19 21:48:20

„It’s a path puzzle. You draw a path that enters the grid at the top and exits at the bottom. Along the way, there are 50 sections, each following a different ruleset. Consecutive sections overlap by a few rows, creating short hybrid sections in between.”
This is amazing! The printable PDF-version is 17 pages! 🤯

Rorschach’s River: a Collaborative Conundrum
In July 2022, I asked Puzzlers Club whether there would be any interest in writing a big mashup puzzle in an exquisite corpse style. There was. This is that puzzle. Wait, why is it December 2025?

@nohillside@smnn.ch
2026-02-03 19:51:05

Let me translate that: Musks boosts the value of xAI by integrating it into SpaceX and claiming that the future of AI is in space, in two years. That’s the same Musk who is flying to Mars „real soon now“.
pxlnv.com/linklog/musk-spacex-

Elon Musk Gives Himself the Biggest Handshake – Pixel Envy
You may remember how, a little under a year ago, Elon Musk’s company xAI bought Elon Musk’s other company X, “valuing” it at $44 billion, exactly the same as the amount he paid for it despite Fidelity valuing it at more like $9 billion. Then, just a few months later, Elon Musk’s company SpaceX gave […]

@kexpmusicbot@mastodonapp.uk
2025-12-30 11:43:14

🇺🇦 #NowPlaying on KEXP's #VarietyMix
Jaybee & Pixel:
🎵 It's Me
#Jaybee #Pixel
flightpattern.bandcamp.com/alb
open.spotify.com/track/02Ku5Wm

@arXiv_csLG_bot@mastoxiv.page
2025-12-22 10:31:40

Estimating Spatially Resolved Radiation Fields Using Neural Networks
Felix Lehner, Pasquale Lombardo, Susana Castillo, Oliver Hupe, Marcus Magnor
arxiv.org/abs/2512.17654 arxiv.org/pdf/2512.17654 arxiv.org/html/2512.17654
arXiv:2512.17654v1 Announce Type: new
Abstract: We present an in-depth analysis on how to build and train neural networks to estimate the spatial distribution of scattered radiation fields for radiation protection dosimetry in medical radiation fields, such as those found in Interventional Radiology and Cardiology. Therefore, we present three different synthetically generated datasets with increasing complexity for training, using a Monte-Carlo Simulation application based on Geant4. On those datasets, we evaluate convolutional and fully connected architectures of neural networks to demonstrate which design decisions work well for reconstructing the fluence and spectra distributions over the spatial domain of such radiation fields. All used datasets as well as our training pipeline are published as open source in separate repositories.
toXiv_bot_toot