Tootfinder

Did an "AI" (LLM) write that report? @… https://flipboard.com/@npr/science-uk3a4d92z/-/a-2dzVqOFxTxGIIGWtXjFa7Q:a:319544…

The risks of AI in schools outweigh the benefits, report says
The risks of using generative artificial intelligence to educate children and teens currently overshadow the benefits, according to a new study by the Brookings Institution's Center for Universal Education. The sweeping study includes focus groups and interviews with K-12 students, parents, …

Under Donald Trump, the E.P.A.
plans to stop tallying gains from the health benefits caused by curbing two of the most widespread deadly air pollutants,
fine particulate matter and ozone,
when regulating industry, according to internal agency emails and documents reviewed by The New York Times.
It’s a seismic shift that runs counter to the E.P.A.’s mission statement,
which says the agency’s core responsibility is to protect human health and the environment, env…

E.P.A. to Stop Considering Lives Saved by Limiting Air Pollution
In a reversal, the agency plans to calculate only the cost to industry when setting pollution limits, and not the monetary value of saving human lives, documents show.

I just spoke to WGME CBS/Fox last night about a data center proposed for an old Maine mill. Lewiston's climate and water resources are a better fit than in the southern US, but city managers still overestimate the benefits to local economies—about 20 jobs post-construction, many remote.

Diffusion-Link: Diffusion Probabilistic Model for Bridging the Audio-Text Modality Gap
KiHyun Nam, Jongmin Choi, Hyeongkeun Lee, Jungwoo Heo, Joon Son Chung
https://arxiv.org/abs/2510.11330

Diffusion-Link: Diffusion Probabilistic Model for Bridging the Audio-Text Modality Gap
Contrastive audio-language pretraining yields powerful joint representations, yet a persistent audio-text modality gap limits the benefits of coupling multimodal encoders with large language models (LLMs). We present Diffusion-Link, a diffusion-based modality-bridging module that generatively maps audio embeddings into the text-embedding distribution. The module is trained at the output embedding from the frozen multimodal encoder and implemented as a lightweight network with three residual MLP…

Celebrate a quarter century of #NorthBeach Citizens non profit org with upcoming big bash at Bimbo's 365 Club 0n Columbus
https://northbeachcitizens.org
Better yet, join the event as a sponsor and help thi…

I’m somewhat annoyed by big parts of the “AI” discourse (“it’s useless” is patently wrong/wishful thinking and “it’s morally wrong” won’t convince anyone) so this banger by Cory Doctorow was godsend:
> [S]ome people will be on the workers' side because of politics or aesthetics. […] But if you want to win over all the people who benefit from your labor, you need to understand and stress how the products of the AI will be substandard.

Locally Linear Convergence for Nonsmooth Convex Optimization via Coupled Smoothing and Momentum
Reza Rahimi Baghbadorani, Sergio Grammatico, Peyman Mohajerin Esfahani
https://arxiv.org/abs/2511.10239 https://arxiv.org/pdf/2511.10239 https://arxiv.org/html/2511.10239
arXiv:2511.10239v1 Announce Type: new
Abstract: We propose an adaptive accelerated smoothing technique for a nonsmooth convex optimization problem where the smoothing update rule is coupled with the momentum parameter. We also extend the setting to the case where the objective function is the sum of two nonsmooth functions. With regard to convergence rate, we provide the global (optimal) sublinear convergence guarantees of O(1/k), which is known to be provably optimal for the studied class of functions, along with a local linear rate if the nonsmooth term fulfills a so-call locally strong convexity condition. We validate the performance of our algorithm on several problem classes, including regression with the l1-norm (the Lasso problem), sparse semidefinite programming (the MaxCut problem), Nuclear norm minimization with application in model free fault diagnosis, and l_1-regularized model predictive control to showcase the benefits of the coupling. An interesting observation is that although our global convergence result guarantees O(1/k) convergence, we consistently observe a practical transient convergence rate of O(1/k^2), followed by asymptotic linear convergence as anticipated by the theoretical result. This two-phase behavior can also be explained in view of the proposed smoothing rule.
toXiv_bot_toot

Unlocking New Frontiers: The Versatile Potential of the Brazilian Multipurpose Reactor
Luiz P. de Oliveira, Alexandre P. S. Souza, Carlos G. S. Santos, Iber\^e R. S. J\'unior, Barbara P. G. Silva, Marco A. S. Pereira, Frederico A. Genezini, Jos\'e A. Perrotta
https://arxiv.org/abs/2510.10657

Unlocking New Frontiers: The Versatile Potential of the Brazilian Multipurpose Reactor
The multipurpose nature of nuclear research reactors has been investigated. This class of reactors has gained momentum within the international community, given the multiple benefits of nuclear technology in medicine, agriculture, industry, and the development of new materials, being characterized by the simultaneous use of several applications. In this context, Brazil has recently joined the group of countries with multipurpose reactor projects. The Brazilian Multipurpose Reactor (RMB) will be…

Chancellor Thomas Gibson is offering a challenge to #UWM faculty and staff: Raise a total of $1,000 by the end of this week, and he will match with a $1,000 gift. Visits to the UWM food pantry rose more than 41% from September to October, as the federal government shutdown cut paychecks and certain government benefits and demand is expected to spike in the coming days as Supplemental Nutrition Assistance Program benefits are interrupted.
It's a good cause.
#Milwaukee

In her keynote at #ISWC2025, Yuko Harayama, Secretary General of Global Partnership on AI Tokyo Expert Support Center, is discussing the challenges of #AI on Human Society, suggesting a shift from originally tech-driven to human-centered paradigm, addressing key questions related to