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When Congress recessed in December, it left three crucial cyber priorities in the air, including the confirmation of Sean Plankey's nomination as CISA Director.
Although Plankey's renomination announcement is good news, experts say Congress's delay in acting on cyber priorities damages the nation's ability to counter rising threats.
Check out my latest CSO piece, which looks at the setbacks created by Plankey's confirmation delay and the other key priorities l…

US cybersecurity weakened by congressional delays despite Plankey renomination
Sean Plankey’s renomination as CISA director offers some relief, but stalled legislation on cyber threat information sharing and state and local grants continues to strain the nation’s ability to counter rising cyber threats.

Non-conformally Einstein instantons in Conformal Gravity with and without nonlinear matter fields
Crist\'obal Corral, Borja Diez, Eleftherios Papantonopoulos
https://arxiv.org/abs/2510.11854

Non-conformally Einstein instantons in Conformal Gravity with and without nonlinear matter fields
In this work, we study non-conformally Einstein gravitational instantons in four-dimensional Conformal Gravity, both in vacuum and in the presence of nonlinear conformal matter. First, the one-parameter extension of the Kerr-NUT-AdS metric is analyzed. We obtain their conserved charges by using the Noether-Wald formalism. It turns out that they receive corrections from the linear modes present in Conformal Gravity, which are properly identified. Then, we perform the analytic continuation into t…

I thought I’d seen this in some of the photos and videos, and @… via the Minnesota Reformer confirms it.
https://minnesotareformer.com/2026/01/14/we-found-more-than-40-cases-of-immigration-agents-using-banned-chokeholds/

Compressibility Measures Complexity: Minimum Description Length Meets Singular Learning Theory
Einar Urdshals, Edmund Lau, Jesse Hoogland, Stan van Wingerden, Daniel Murfet
https://arxiv.org/abs/2510.12077

Compressibility Measures Complexity: Minimum Description Length Meets Singular Learning Theory
We study neural network compressibility by using singular learning theory to extend the minimum description length (MDL) principle to singular models like neural networks. Through extensive experiments on the Pythia suite with quantization, factorization, and other compression techniques, we find that complexity estimates based on the local learning coefficient (LLC) are closely, and in some cases, linearly correlated with compressibility. Our results provide a path toward rigorously evaluating…

A look at WhatsApp's enormous global reach and influence, and how the messaging app became the dominant platform for everyday conversation worldwide (Sam Knight/New Yorker)
https://www.newyorker.com/magazine/2026/01/19/how-what…

How WhatsApp Took Over the Global Conversation
The platform has become a core technology around the world, relied on by governments and extended families alike, Sam Knight writes. What are we all doing there?

TerraCodec: Compressing Earth Observations
Julen Costa-Watanabe, Isabelle Wittmann, Benedikt Blumenstiel, Konrad Schindler
https://arxiv.org/abs/2510.12670 https://

TerraCodec: Compressing Earth Observations
Earth observation (EO) satellites produce massive streams of multispectral image time series, posing pressing challenges for storage and transmission. Yet, learned EO compression remains fragmented, lacking publicly available pretrained models and misaligned with advances in compression for natural imagery. Image codecs overlook temporal redundancy, while video codecs rely on motion priors that fail to capture the radiometric evolution of largely static scenes. We introduce TerraCodec (TEC), a …

Finally, comments on a recipe that are actually good advice.

Testing confirmed the patient has H5N5, a strain of bird flu that has previously been reported in animals but never before in humans
https://abcnews.go.com/Health/suspected-human-bird-flu-case-1st-us-9/story?id=127519769

1st US human bird flu case in 9 months confirmed with strain only seen in animals before
The patient is an older adult with underlying health conditions.

CuMPerLay: Learning Cubical Multiparameter Persistence Vectorizations
Caner Korkmaz, Brighton Nuwagira, Bar{\i}\c{s} Co\c{s}kunuzer, Tolga Birdal
https://arxiv.org/abs/2510.12795

CuMPerLay: Learning Cubical Multiparameter Persistence Vectorizations
We present CuMPerLay, a novel differentiable vectorization layer that enables the integration of Cubical Multiparameter Persistence (CMP) into deep learning pipelines. While CMP presents a natural and powerful way to topologically work with images, its use is hindered by the complexity of multifiltration structures as well as the vectorization of CMP. In face of these challenges, we introduce a new algorithm for vectorizing MP homologies of cubical complexes. Our CuMPerLay decomposes the CMP in…