G Norr

An anonymous reader shares a report: The Food and Drug Administration has refused to start a review of Moderna's application for its experimental flu shot, the company announced Tuesday, in another sign of the Trump administration's influence on tightening vaccine regulations in the U.S. Moderna said the move is inconsistent with previous feedback from the agency from before it submitted the application and started phase three trials on the shot, called mRNA-1010. The drugmaker said it has requested a meeting with the FDA to "understand the path forward." Moderna noted that the agency did not identify any specific safety or efficacy issues with the vaccine, but instead objected to the study design, despite previously approving it. The company added that the move won't impact its 2026 financial guidance. Moderna's jab showed positive phase three data last year, meeting all of the trial goals. At the time, Moderna said the stand-alone flu shot was key to its efforts to advance a combination vaccine targeting both influenza and Covid-19.

Read more of this story at Slashdot.

This is a current list of where and when I am scheduled to speak:

• Nathan E. Sanders and I will be giving a book talk on Rewiring Democracy at the Harvard Kennedy School’s Ash Center in Cambridge, Massachusetts, USA, on October 22, 2025, at noon ET.
• Nathan E. Sanders and I will be speaking and signing books at the Cambridge Public Library in Cambridge, Massachusetts, USA, on October 22, 2025, at 6:00 PM ET. The event is sponsored by Harvard Bookstore.
• Nathan E. Sanders and I will give a virtual talk about our book Rewiring Democracy on October 23, 2025, at 1:00 PM ET. The event is hosted by Data & Society.
• I’m speaking at the Ted Rogers School of Management in Toronto, Ontario, Canada, on Thursday, October 29, 2025, at 1:00 PM ET.
• Nathan E. Sanders and I will give a virtual talk about our book Rewiring Democracy on November 3, 2025, at 2:00 PM ET. The event is hosted by the Boston Public Library.
• I’m speaking at the World Forum for Democracy in Strasbourg, France, November 5-7, 2025.
• I’m speaking and signing books at the University of Toronto Bookstore in Toronto, Ontario, Canada, on November 14, 2025. Details to come.
• Nathan E. Sanders and I will be speaking at the MIT Museum in Cambridge, Massachusetts, USA, on December 1, 2025, at 6:00 pm ET.
• Nathan E. Sanders and I will be speaking at a virtual event hosted by City Lights on the Zoom platform, on December 3, 2025, at 6:00 PM PT.
• I’m speaking and signing books at the Chicago Public Library in Chicago, Illinois, USA, on February 5, 2026. Details to come.

The list is maintained on this page.

Intel Linux engineers have begun posting patches for enabling the Xe3P architecture. While Xe3P is also expected to be found with next-generation Intel discrete GPUs, the initial focus is on enabling support for Nova Lake...

A new paper, “Polynomial Time Cryptanalytic Extraction of Neural Network Models,” by Adi Shamir and others, uses ideas from differential cryptanalysis to extract the weights inside a neural network using specific queries and their results. This is much more theoretical than practical, but it’s a really interesting result.

Abstract:

Billions of dollars and countless GPU hours are currently spent on training Deep Neural Networks (DNNs) for a variety of tasks. Thus, it is essential to determine the difficulty of extracting all the parameters of such neural networks when given access to their black-box implementations. Many versions of this problem have been studied over the last 30 years, and the best current attack on ReLU-based deep neural networks was presented at Crypto’20 by Carlini, Jagielski, and Mironov. It resembles a differential chosen plaintext attack on a cryptosystem, which has a secret key embedded in its black-box implementation and requires a polynomial number of queries but an exponential amount of time (as a function of the number of neurons). In this paper, we improve this attack by developing several new techniques that enable us to extract with arbitrarily high precision all the real-valued parameters of a ReLU-based DNN using a polynomial number of queries and a polynomial amount of time. We demonstrate its practical efficiency by applying it to a full-sized neural network for classifying the CIFAR10 dataset, which has 3072 inputs, 8 hidden layers with 256 neurons each, and about 1.2 million neuronal parameters. An attack following the approach by Carlini et al. requires an exhaustive search over 2^256 possibilities. Our attack replaces this with our new techniques, which require only 30 minutes on a 256-core computer.

One of the most common test automation challenges is how do we modify the request headers in Selenium WebDriver. As an automation tester, you would come across this challenge for any programming language, including Java. Before coming to a solution, we need to understand the problem statement better and arrive at different possibilities to modify the header request in Java while working with Selenium WebDriver Tutorial.

In this Selenium Java tutorial, we will learn how to modify HTTP request headers in Java using Selenium WebDriver with different available options.