New sphere-packing record stems from an unexpected source
quantamagazine.org
LookingGlass: Generative Anamorphoses via Laplacian Pyramid Warping
studios.disneyresearch.com
My first verified imperative program
markushimmel.de
Mercury: Ultra-fast language models based on diffusion
arxiv.org
The chemical secrets that help keep honey fresh for so long
bbc.com
Launch HN: Morph (YC S23) – Apply AI code edits at 4,500 tokens/sec
I used o3 to profile myself from my saved Pocket links
noperator.dev
The Miyawaki Method of micro-forestry
futureecologies.net
Adding a feature because ChatGPT incorrectly thinks it exists
holovaty.com
When Figma starts designing us
designsystems.international
François Chollet: The Arc Prize and How We Get to AGI [video]
youtube.com
Bitchat – A decentralized messaging app that works over Bluetooth mesh networks
github.com
You Should Run a Certificate Transparency Log
words.filippo.io
Show HN: NYC Subway Simulator and Route Designer
buildmytransit.nyc
Show HN: Ossia score – a sequencer for audio-visual artists
github.com
Lightfastness Testing of Colored Pencils
sarahrenaeclark.com
Solving Wordle with uv's dependency resolver
mildbyte.xyz
Analysing Roman itineraries using GIS tooling
link.springer.com
Hymn to Babylon, missing for a millennium, has been discovered
phys.org
SUS Lang: The SUS Hardware Description Language
sus-lang.org
Show HN: From Photos to Positions: Prototyping VLM-Based Indoor Maps
arjo129.github.io
A non-anthropomorphized view of LLMs
addxorrol.blogspot.com
Artist in Residence on a Satellite
global.cafa.edu.cn
I built Unlearning Comparator, a visual analytics toolkit to help researchers and developers compare how different machine unlearning methods work. It provides a unified workflow to test for accuracy, efficiency, and privacy. You can check out the live demo linked in the post, and the source code is on GitHub: https://github.com/gnueaj/Machine-Unlearning-Comparator Our accompanying paper is currently under review at IEEE TVCG. Happy to answer any questions and would love to hear your feedback!