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Alibaba open-sources its chip software, following similar plays from Huawei and Moore Threads, as Chinese GPU makers try to break the dominance of Nvidia's CUDA (Ann Cao/South China Morning Post)
https://www.scmp.com/tech/tech-war/article

Alibaba targets Nvidia’s dominant software ecosystem with open-source AI stack
The firm’s chip unit T-Head aims to lower migration barriers to Zhenwu AI computing architectures, following similar initiatives by Huawei and Moore Threads.

I am really liking the new #Drupal homepage. The last one was awful and I don't seem to remember feeling too positive about any of the ones before that one either.
The last one just screamed "WTF is this? NOBODY KNOWS."
The current one answers the question, "Why would you want to give Drupal a try?"
Drupal is amazing software with a great ecosystem for people…

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Drupal is an open source platform for building amazing digital experiences. It's made by a dedicated community. Anyone can use it, and it will always be free.

NIST is looking for a National Vulnerability Database Program Manager
https://www.usajobs.gov/job/876565100

National Vulnerability Database Program Manager
Join NIST as the National Vulnerability Database (NVD) Program Manager! You'll lead teams and software infrastructure while collaborating with global stakeholders to evolve vulnerability management standards. Identify ecosystem gaps and develop new technical guidelines and capabilities to strengthen our national cybersecurity posture. This notice is issued under direct-hire authority to recruit new talent to occupations for which NIST has a severe shortage of candidates.

svMultiPhysics: a finite element-based solver for cardiovascular simulations
David Codoni, Sujal Dave, David W. Parker, Aaron L. Brown, Javiera Jilberto, Han Zhao, Divya Adil, Zachary A. Sexton, Martin R. Pfaller, Michele Bucelli, Shawn C. Shadden, Charles A. Taylor, Alison L. Marsden
https://arxiv.org/abs/2607.19631 https://arxiv.org/pdf/2607.19631 https://arxiv.org/html/2607.19631
arXiv:2607.19631v1 Announce Type: new
Abstract: Heart disease remains the leading cause of death in the United States, motivating extensive efforts to improve its diagnosis, treatment, and prevention. Over the past decade, computational modeling has emerged as a powerful tool to advance cardiovascular research by enabling detailed, patient-specific studies of cardiac physiology and pathology. svMultiPhysics is an open-source, parallel finite element solver written in C specifically designed for multiphysics cardiovascular problems. It provides a unified framework for simulating the partial differential equations that govern solid mechanics, fluid dynamics, diffusion, and cardiac electrophysiology. These equations can be solved independently or in a coupled fashion, allowing researchers to investigate interactions between physical processes in a modular yet integrated way. The solver's main strength lies in its ability to seamlessly couple multiple physics modules, enabling the study of complex, highly nonlinear systems. For example, svMultiPhysics can capture the interplay between cardiac electrophysiology, myocardial tissue mechanics, and blood flow dynamics, processes that are essential to understanding vascular and cardiac physiology and function in health and disease. Preliminary GPU-enabled simulations show up to approximately $30\times$ wall-clock speedup for selected linear solver configurations over CPU-based simulations. By offering a robust, extensible, and freely available platform, svMultiPhysics empowers researchers to explore multiphysics problems in cardiovascular science. As the primary 3D solver in the SimVascular open source project, it forms a key component of an end-to-end open source software ecosystem for image based patient specific modeling in the cardiovascular system. It is maintained and openly developed on GitHub, fostering transparency, reproducibility, and collaboration.
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Despite the extortionate pricing: the #calendar application #Fantastical is quite simply the finest software product I've utilised over the past decade. It features continuous, purposeful iterations, robust stability, and flawless integration across Apple ecosystem. It…

Hola 👋 ¿sabían que hay ciberataques dirigidos que aprovechan vulnerabilidades de software llamadas "ejecución de código remoto, cero click"?
En algunas aplicaciones como WhatsApp existe una configuración para protegerse de ciberataques avanzados, especialmente importante para personas de alto riesgo como activistas, periodistas, empresarias , políticas o cualquiera que cuenten con acceso a sistemas de empresas u organizaciones, también personas cercanas a otras de alto riesgo…

Fisher Forecasting for the DESC with $\texttt{Augur}$
Paul Rogozenski, Sankarshana Srinivasan, Javier S\'anchez, Nora Elisa Chisari, Arthur Loureiro, Marc Paterno, Rebekah Polen, Heather Prince, Biancamaria Sersante, An\v{z}e Slosar, Sandro Vitenti, Carlos Garc\'ia-Garc\'ia, Eric Gawiser, Christos Georgiou, C. Danielle Leonard, Ayan Mitra, Jeremy Neveu, The LSST Dark Energy Science Collaboration
https://arxiv.org/abs/2608.03876 https://arxiv.org/pdf/2608.03876 https://arxiv.org/html/2608.03876
arXiv:2608.03876v1 Announce Type: new
Abstract: The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) has begun its ten-year survey of the entire visible southern hemisphere. To ensure robust cosmological measurements, computationally inexpensive investigations of modeling choices must be made to gauge the performance of proposed cosmological analyses. In this paper, we introduce the $\texttt{Augur}$ tool of the Dark Energy Science Collaboration (DESC), which provides Fisher forecasts for cosmological inference for the LSST using software frameworks designed for DESC science. We test the pipeline by comparing it to forecasts produced by external code and direct sampling of the posterior via nested sampling methods, finding good agreement between all methods. We additionally investigate a range of modeling and hyperparameter choices for a 3$\times$2pt investigation in harmonic space, providing users with diagnostics to obtain reliable forecasts. $\texttt{Augur}$ will be continually updated to be compatible with the other tools in the DESC software ecosystem as additional probes and functionality become available.
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Digs, which is building AI software for residential construction, raised a $25.3M Series A led by building materials giant Builders FirstSource (Kurt Schlosser/GeekWire)
https://www.geekwire.com/2026/homebuilding-ai-startup-d…

Homebuilding AI startup Digs raises $25.3M and partners with building products giant
Under the five-year agreement, Builders FirstSource will integrate Digs’ AI platform into its digital ecosystem, expanding tools for its 140,000 builder clients.