Tootfinder

FEMA Employees Reassigned to ICE
Probationary employees who had been on paid leave were told to report to ICE within seven days or lose their jobs.
It could signal problems with ICE recruitment
https://prospect.org/labor/2025-08-06-fema-employees-reassigned…

FEMA Employees Reassigned to ICE
Probationary employees who had been on paid leave were told to report to ICE within seven days or lose their jobs. It could signal problems with ICE recruitment.

@… Boy-oh-boy. What DIY is like for the disabled. Humbling.
https://oldfriends.live/@paul/114805197623754036

Paul Chambers🚧 (@paul@oldfriends.live)
Attached: 1 image Today, I got put down on the floor with my Hoyer lift, took apart the back of a through the wall hotel like HVAC unit and changed the broken fan blade. What should have taken 30 minutes took me around 4 hours with my Parkinson's but I was not going to pay someone $250 for a service call to change a $57 fan blade. Parts was still under warranty but labor was not. It cost me $25 to have the guy that mows my grass pull it out for me and then slide it back in on his way home…

Ich habe das #planted #Steak heute ergebnisoffen verkostet. Ich muss das nicht mehr haben. Weder schmeckt das nach Fleisch, noch wäre der Geschmack für sich geeignet, es noch einmal zuzubereiten. Dann lieber gewürzte Zucchinistreifen oder eine feine Grillpaprika.

LobRA: Multi-tenant Fine-tuning over Heterogeneous Data
Sheng Lin, Fangcheng Fu, Haoyang Li, Hao Ge, Xuanyu Wang, Jiawen Niu, Yaofeng Tu, Bin Cui
https://arxiv.org/abs/2509.01193

LobRA: Multi-tenant Fine-tuning over Heterogeneous Data
With the breakthrough of Transformer-based pre-trained models, the demand for fine-tuning (FT) to adapt the base pre-trained models to downstream applications continues to grow, so it is essential for service providers to reduce the cost of processing FT requests. Low-rank adaption (LoRA) is a widely used FT technique that only trains small-scale adapters and keeps the base model unaltered, conveying the possibility of processing multiple FT tasks by jointly training different LoRA adapters wit…

Multimodal, Multi-Disease Medical Imaging Foundation Model (MerMED-FM)
Yang Zhou, Chrystie Wan Ning Quek, Jun Zhou, Yan Wang, Yang Bai, Yuhe Ke, Jie Yao, Laura Gutierrez, Zhen Ling Teo, Darren Shu Jeng Ting, Brian T. Soetikno, Christopher S. Nielsen, Tobias Elze, Zengxiang Li, Linh Le Dinh, Lionel Tim-Ee Cheng, Tran Nguyen Tuan Anh, Chee Leong Cheng, Tien Yin Wong, Nan Liu, Iain Beehuat Tan, Tony Kiat Hon Lim, Rick Siow Mong Goh, Yong Liu, Daniel Shu Wei Ting

Multimodal, Multi-Disease Medical Imaging Foundation Model (MerMED-FM)
Current artificial intelligence models for medical imaging are predominantly single modality and single disease. Attempts to create multimodal and multi-disease models have resulted in inconsistent clinical accuracy. Furthermore, training these models typically requires large, labour-intensive, well-labelled datasets. We developed MerMED-FM, a state-of-the-art multimodal, multi-specialty foundation model trained using self-supervised learning and a memory module. MerMED-FM was trained on 3.3 mi…

Jack Johnson opened a multi-racial restaurant and nightclub, Club Deluxe, which he ran with his white wife.
Because of this, the authorities arrested him for violating the Mann act (transporting women across state lines for immoral purposes).
Johnson fled the country to avoid arrest, but continued boxing abroad.
Eventually he turned himself in and served time at Leavenworth Prison.
Fight- fan Donald Trump pardoned him in 2018, something Reagan, both Bushes and even…

MikeDunnAuthor (@MikeDunnAuthor@kolektiva.social)
Attached: 1 image Today in Labor History July 4, 1910: African-American boxer Jack Johnson knocked out white boxer Jim Jeffries in the 15th round, leading to race riots throughout the U.S. 11 separate riots occurred in NYC, alone. There were riots in 50 cities, including New York, Baltimore, Pittsburgh, Philadelphia, Houston, New Orleans, Atlanta, and St. Louis. At least 20 people died in these riots. Johnson, who was also known as the Galveston Giant, became the first black World Heavyweight …

How to tell a vibe coder of lying when they say they check their code.
People who will admit to using LLMs to write code will usually claim that they "carefully check" the output since we all know that LLM code has a lot of errors in it. This is insufficient to address several problems that LLMs cause, including labor issues, digital commons stress/pollution, license violation, and environmental issues, but at least it's they are checking their code carefully we shouldn't assume that it's any worse quality-wise than human-authored code, right?
Well, from principles alone we can expect it to be worse, since checking code the AI wrote is a much more boring task than writing code yourself, so anyone who has ever studied human-computer interaction even a little bit can predict people will quickly slack off, stating to trust the AI way too much, because it's less work. I'm a different domain, the journalist who published an entire "summer reading list" full of nonexistent titles is a great example of this. I'm sure he also intended to carefully check the AI output, but then got lazy. Clearly he did not have a good grasp of the likely failure modes of the tool he was using.
But for vibe coders, there's one easy tell we can look for, at least in some cases: coding in Python without type hints. To be clear, this doesn't apply to novice coders, who might not be aware that type hints are an option. But any serious Python software engineer, whether they used type hints before or not, would know that they're an option. And if you know they're an option, you also know they're an excellent tool for catching code defects, with a very low effort:reward ratio, especially if we assume an LLM generates them. Of the cases where adding types requires any thought at all, 95% of them offer chances to improve your code design and make it more robust. Knowing about but not using type hints in Python is a great sign that you don't care very much about code quality. That's totally fine in many cases: I've got a few demos or jam games in Python with no type hints, and it's okay that they're buggy. I was never going to debug them to a polished level anyways. But if we're talking about a vibe coder who claims that they're taking extra care to check for the (frequent) LLM-induced errors, that's not the situation.
Note that this shouldn't be read as an endorsement of vibe coding for demos or other rough-is-acceptable code: the other ethical issues I skipped past at the start still make it unethical to use in all but a few cases (for example, I have my students use it for a single assignment so they can see for themselves how it's not all it's cracked up to be, and even then they have an option to observe a pre-recorded prompt session instead).

On est dimanche soir, je peux Š peine lever et tendre le bras droit sans presque hurler de douleur, ma sciatique s'est réveillée jusqu'au bout des orteils, quant Š mes cervicales... no coment, cette fois c'est sûr, c'est la fin des vacances et la reprise du boulot demain matin Š 5h. Niveau psychosomatisme, vous en êtes-où, vous, de votre #rentree ?

Time is running out.
#LibreFM #Music

The fast X-ray detector system of the FAMU experiment at RAL
M. Bonesini
https://arxiv.org/abs/2507.01819 https://arxiv.org/pdf/2507.…

The fast X-ray detector system of the FAMU experiment at RAL
The FAMU experiment at RAL has been designed to study the hyperfine splitting (HFS) of muonic hydrogen and thus measure the Zemach radius of the proton, with a precision better than 1 %. The HFS transition is excited by a tunable MIR laser at ~ 6790 nm and is recognized by delayed ($μ$O) X-ray emission around 130-170 keV. The fast X-ray detection system is based on 34 scintillating LaBr3:Ce crystals and one HPGe detector for inter-calibration.