Tootfinder

Always appreciate #Python package developers being responsible about API stability, and… [checks notes]… raising the major version number over a "minor API tweak", then delaying the release until a security fix demanded one.
#packaging

Mandating “Evidence-Based” Suicide Detection in Chatbots
https://fpf.org/blog/mandating-evidence-based-suicide-detection-in-chatbots/
@…

Back when I was diagnosed with #diabetes, I've found two apps to help me. Both were proprietary.
The first one came from the glucometer's manufacturer, and it featured the ability to copy its readings over Bluetooth. It also had a pretty useful bolus calculator. However, it was also annoying in a number of ways: it required an account with all the implied data sharing, was premiumware (though using their glucometer implied a free "pro" version), was quite childish in design, didn't respect disabled animations or dark theme.
The second one was an independent Polish app to compute carbs from meals. It wasn't perfect, but it had a rich database of products and quite a few convenient features (like copying meals or calculating carbs based on recipes). Unfortunately, the authors went full way into AI hype, and while I didn't use any of the "AI" features (they were premiumware anyway), the app itself was becoming increasingly crappy.
Eventually, this motivated me to look for a new app. I've settled for #Diaguard. It's just got the basics: meal composition and computing carbs, plus letting me log blood sugar and insulin doses manually. It used to have a bolus calculator before I used it, but it was removed over legal concerns. Still, it's open source, it's nice, it's got no crap and it respects the dark theme. And honestly, given that I've already reached the point of overriding bolus calculator, I've figured out it's enough for me.
In fact, it's so "enough" that I'm not even using it regularly. I mean, if my blood sugar is predictable and my meals are predictable, there's no reason to waste time logging them. The app is there to assist me when I need it, not force me to use it.
I still keep the two other apps installed. The first one in case I had doubts over insulin doses and wanted to use the bolus calculator. The second one over my database of meals; though I had already exported it, so I just need to figure out if the export is complete enough.
#Android

Space may feel separate from the environmental systems that sustain life on Earth.
But increasingly, the way we build, launch and dispose of satellites is starting to change that.
Over the past few years, the number of satellite launches has skyrocketed.
There are now nearly 15,000 active satellites in orbit around the Earth,
most of them part of “mega-constellations” in which each satellite has a service life of only a few years.
New satellites must be quickly la…

A new space race could turn our atmosphere into a ‘crematorium for satellites’
Planned ‘megaconstellations’ of satellites could cause unforeseen harm to the ozone layer and climate systems. Global regulation is needed before it’s too late.

Dependency cooldowns are a nice idea, but I dare say they're a short-term solution.
They resemble the idea of avoiding poison by waiting for someone else to start eating first. That works, provided that someone actually eats first, and that the poison works fast. But eventually it leads to that awkward silence at the table when nobody wants to risk the first bite.
Adapting dependency cooldowns means basically waiting for "someone else" to notice the problem. At some point when large enough number of projects adapts them, we're going back to square one — except with an artificial few-day delay.
#security #FreeSoftware

Swiss Federal Military supplier Ruag paid ransom to Akira to get of their US subsidiary Ruag LLC (formerly Mecanex) data back and prevent leaking of information
https://www.srf.ch/news/schweiz/nach-erpressung-in-den-usa-bundeskonz…

Rezension zu "Platform Power and Libraries" (Christine F. Smith 2025, https://litwinbooks.com/books/platform-power-and-libraries/ &

Sometimes it makes sense to act smart rather than brute-force.
For example, when Intel makes another #MKL release and you get version like "2026.0.0", and you need to figure out the remaining "-n" suffix for the .deb packages. And you really don't want to start a Debian container to figure that out.
Well, you could just keep brute-forcing until you find the right number. Or you can figure out that the index URL is #Gentoo

Replaced article(s) found for cs.IT. https://arxiv.org/list/cs.IT/new
[1/1]:
- Optimal Proximity Gap for Folded Reed--Solomon Codes via Subspace Designs
Fernando Granha Jeronimo, Lenny Liu, Pranav Rajpal
https://arxiv.org/abs/2601.10047 https://mastoxiv.page/@arXiv_csIT_bot/115903956641689136
- Breaking Symmetry in D2D Coded Caching: Optimal Communication with Low Subpacketization
Xiang Zhang, Giuseppe Caire, Mingyue Ji
https://arxiv.org/abs/2602.12220 https://mastoxiv.page/@arXiv_csIT_bot/116062725600909840
- A New Approach to Code Smoothing Bounds
Tsuyoshi Miezaki, Yusaku Nishimura, Katsuyuki Takashima
https://arxiv.org/abs/2603.18077 https://mastoxiv.page/@arXiv_csIT_bot/116260380391748925
- Fluid Antenna Systems Enabling 6G HRLLC With Port Switching Delay
Xusheng Zhu, Kai-Kit Wong, Hao Xu, Chenguang Rao, Hyundong Shin
https://arxiv.org/abs/2605.06275 https://mastoxiv.page/@arXiv_csIT_bot/116537839161835575
- Accurate Estimation of Mutual Information in High Dimensional Data
Eslam Abdelaleem, K. Michael Martini, Ilya Nemenman
https://arxiv.org/abs/2506.00330 https://mastoxiv.page/@arXiv_physicsdataan_bot/114618315134354611
- SDQM: Synthetic Data Quality Metric for Object Detection Dataset Evaluation
Ayush Zenith, Arnold Zumbrun, Neel Raut, Jing Lin
https://arxiv.org/abs/2510.06596 https://mastoxiv.page/@arXiv_csCV_bot/115343628773188610
- SEDULity: A Proof-of-Learning Framework for Distributed and Secure Blockchains with Efficient Use...
Weihang Cao, Mustafa Doger, Sennur Ulukus
https://arxiv.org/abs/2512.13666 https://mastoxiv.page/@arXiv_csCR_bot/115729118798706696
- A theory of learning data statistics in diffusion models, from easy to hard
Lorenzo Bardone, Claudia Merger, Sebastian Goldt
https://arxiv.org/abs/2603.12901 https://mastoxiv.page/@arXiv_statML_bot/116237842977106276
- On the independence number of de Bruijn graphs
Pietro Majer, Matteo Novaga
https://arxiv.org/abs/2604.14671 https://mastoxiv.page/@arXiv_mathCO_bot/116419097221023806
- Information bottleneck for learning the phase space of dynamics from high-dimensional experimenta...
K. Michael Martini, Eslam Abdelaleem, Paarth Gulati, Ilya Nemenman
https://arxiv.org/abs/2604.24662 https://mastoxiv.page/@arXiv_physicsdataan_bot/116481236697063671
- Improved Amenability Bounds for Local Coordination Games
Ron Peretz, Dean Kraizberg
https://arxiv.org/abs/2606.01963 https://mastoxiv.page/@arXiv_csGT_bot/116679490095124433
toXiv_bot_toot

ANNS-AMP: Accelerating Approximate Nearest Neighbor Search via Adaptive Mixed-Precision Computing
Mingkai Chen, Cheng Liu, Shengwen Liang, Lei Zhang, Xiaowei Li, Huawei Li
https://arxiv.org/abs/2606.07156 https://arxiv.org/pdf/2606.07156 https://arxiv.org/html/2606.07156
arXiv:2606.07156v1 Announce Type: new
Abstract: Approximate nearest neighbor search(ANNS) is a critical kernel in modern applications such as LLM and recommendation systems.However,its efficiency is fundamentally limited by the need to compute distances between a query and a massive number of high-dimensional vectors,most of which are non-neighbors.Existing approaches reduce redundancy via index optimization or early termination,but remain constrained by fixed-precision computation,leading to unnecessary arithmetic and memory bandwidth overhead.This paper presents ANNS-AMP,an adaptive mixed-precision framework and accelerator that adapts the precision of distance computation to the characteristics of queries and data distribution.The key insight is that different regions of the vector space require different levels of precision to preserve top-k accuracy.ANNS-AMP leverages the clustered structure of PQ-based indices and introduces a lightweight predictor to determine cluster-level precision at runtime based on features such as scale,radius,and query distance.To efficiently realize variable-precision execution,we design a bit-serial accelerator with a bit-interleaved data layout,enabling throughput to scale with reduced precision while mitigating memory bandwidth bottlenecks and load imbalance through a greedy scheduling strategy.Moreover,the runtime predictor can also reuse the bit-serial computing array for efficient runtime prediction and can be fitted to the ANNS pipeline without performance penalty.According to our experiments on representative datasets,ANNS-AMP achieves 163.76x,10.57x,and 2.06x performance speedups on average,and reduces average energy consumption by 1100.00x,39.41x,and 6.66x compared to CPU,GPU,and customized ANNS accelerator baselines,respectively,while maintaining accuracy loss below 2.7%.These results demonstrate that adaptive mixed-precision computing is a promising direction for efficient large-scale ANNS.
toXiv_bot_toot

So one of the authors is Nicholas Carlini, who works for Anthropic. This is basically an ad for the three letter agencies to use Claude. It massively over-promises compared to what the actual paper says.
But, it is important. First, this is really about silencing people. The threat of identification is designed to make people afraid to talk online. There's a massive asymmetry between the fascists and the people. The fascists are weird racists and pedophiles who are obsessed with control. No one likes them. No one likes their ideas, because their ideas are creepy and bad.
When they talk about their ideas, that people should be murdered or kidnaped based on their skin color, that there should be a national dress code, that people's sex lives should be monitored, that children should be treated like objects that are owned by the parent (specifically, one parent), that people with different skin color or uteri should be considered as livestock, people fucking hate it because it's awful. When we talk about our ideas, that everyone should be able to eat and take care of themselves, that people who can't take care of themselves should be taken care of, that we should live in a society that values life, that we should live in harmony with nature, people like those ideas. When fascists out us for talking about those ideas, people support us. When we out people who are working as fascist goons those people have to face social consequences.
Everyone hates these people. The US government is currently less popular than it has ever been. The only way they can keep power is by making everyone think that they aren't extraordinarily unpopular. The only way to do that, the way authoritarian have always done it, is to make everyone afraid to talk.
But, yes, what this paper is saying is actually kind of bad. It looks like people who don't take any precautions at all in separating identities can be identified about 30% of the time (based on the results). It's unclear how this will actually work in the real world. Larger corpses will probably have more data, making connecting things easier.
This isn't as good as a human trying to dox someone. It's not going to work as well. It may only work in a small number of cases. There will be false positives (just like there are with people doing the work). It's probably not cheaper than hiring people. But it does mean that you can just dump money into a machine that has no ethical framework and get data out. That's the point. It's hard to find humans who will do evil shit like help dictatorships target human rights activists, but if a machine can do it for twice the price then it's a better deal for the dictatorship.
For most people, you just shouldn't care. This isn't for you. As long as you keep doing what you're doing, and you can keep everyone else doing what they're doing, then there aren't enough resources to actually target you. Even if they know who you are, there are just too many people who hate them and too few goons.
For people who might actually be targeted, there are a lot of things. First, keep in mind what you're putting into anonymous accounts. Any feature that's connected to your real life is a feature that can be extracted to identify you. This has always been true, it just may be easier to find now. Your identities should be totally siloed. It's also harder to identify you if you're writing anonymously as a collective. Collectives are better anyway because they can help check your thinking. When you write as a collective, you can help clean up each other's personal details and language. A collective develops its own voice, which is distinct from individual contributors. If you do this, and you also present your work as being from one "person," then it becomes even harder for anyone (systems or individuals) to really figure it out.
I'm not going to do a full deep dive on this because I just don't have time, but your existing threat model should *already cover these threats* if you need to make sure your writing remains anonymous.
This paper doesn't present any novel methodologies. It just extracts a bunch of features, which a human would extract as notes, and tries to correlate those between identities, which is how human researchers work. Linguistic forensics were mentioned (not by name) in the paper, but the actual methodology doesn't actually seem to use them.
So a thing with less ethics can do a worse job for more money (when adjusted for the real, not investor deflated, price of tokens). It's worth knowing. It's not the end of the world, but it is a good reminder to check your threat model and make sure it's up to date.

If international viewers are wondering why Keir Starmer's resignation speech is accompanied by Beethoven's Ninth Symphony - people troll Prime Ministers by setting up sound systems within earshot of Number 10.
https://en.wikipedia.org/wiki/Steve_Bray

Steve Bray - Wikipedia