Reproducibility is a cornerstone of scientific research, enabling validation, extension, and progress. However, the rapidly evolving nature of software and dependencies poses significant challenges to reproducing research results, particularly in fields like adversarial robustness for deep neural networks, where complex codebases and specialized toolkits are utilized. This paper presents a case study of attempting to validate the results on certified adversarial robustness in "SoK: Certified Robustness for Deep Neural Networks" using the VeriGauge toolkit. Despite following the documented methodology, numerous software and hardware compatibility issues were encountered, including outdated or unavailable dependencies, version conflicts, and driver incompatibilities. While a subset of the original results could be run, key findings related to the empirical robust accuracy of various verification methods proved elusive due to these technical obstacles, as well as slight discrepancies in the test results. This practical experience sheds light on the reproducibility crisis afflicting adversarial robustness research, where a lack of reproducibility threatens scientific integrity and hinders progress. The paper discusses the broader implications of this crisis, proposing potential solutions such as containerization, software preservation, and comprehensive documentation practices. Furthermore, it highlights the need for collaboration and standardization efforts within the research community to develop robust frameworks for reproducible research. By addressing the reproducibility crisis head-on, this work aims to contribute to the ongoing discourse on scientific reproducibility and advocate for best practices that ensure the reliability and validity of research findings within not only adversarial robustness, but security and technology research as a whole.

While technology is critical and necessary for businesses, it often is challenging to effectively ... [ ] implement and apply. Innovation and technology are at the top of nearly every business agenda. Technology is critical to innovation, and it also serves as the accelerator for many parts of businesses' growth plans, from manufacturing to distribution to marketing to finance. As the last decade has increasingly shown, companies that are unable to adopt new technologies quickly and effectively or don't have the right mix of talent run the risk of being outpaced, outsmarted, and otherwise disrupted. In many cases, the willingness and ability to adopt technology determines a company's very survival.

This article was co-written by John Latsis, chairman of the Independent Social Research Foundation. The classic 1995 crime film The Usual Suspects revolves around the police interrogation of Roger "Verbal" Kint, played by Kevin Spacey. Kint paraphrases Charles Baudelaire, stating that "the greatest trick the Devil ever pulled was convincing the world he didn't exist". The implication is that the Devil is more effective when operating unseen, manipulating and conditioning behavior rather than telling people what to do. In the film's narrative, his role is to cloud judgment and tempt us to abandon our sense of moral responsibility.

Artificial intelligence (AI) is proving to be a double-edged sword. While this can be said of most new technologies, both sides of the AI blade are far sharper, and neither is well understood. These technologies are starting to improve our lives in myriad ways, from simplifying our shopping to enhancing our healthcare experiences. Their value to businesses also has become undeniable: nearly 80 percent of executives at companies that are deploying AI recently told us that they're already seeing moderate value from it. Although the widespread use of AI in business is still in its infancy and questions remain open about the pace of progress, as well as the possibility of achieving the holy grail of "general intelligence," the potential is enormous.

Digital disruption, fintech infiltration, big tech competition, or even new technologies such as artificial intelligence seem daunting. Yet the most serious threat to banks and credit unions lies closer to home but remains more difficult to address -- because it is ingrained in almost every traditional financial institution. Subscribe to The Financial Brand via email for FREE!Financial institutions are being disrupted on almost every front due to digital technologies, new competition, redefined business models and increasing consumer expectations. Increasingly they need to innovate, become more agile, utilize data and advanced analytics to support cost reduction and revenue improvement, and build partnerships with organizations who may also be competitors. So, which of these massive changes pose the greatest risk to the future of banking?

Writing about negative events and past failings is one of the most effective ways to reduce stress and give you a new lease of life, new research claims. Acknowledging and analyzing what went wrong during prior setbacks gives people insight which helps them cope better in future stressful situations, researchers found. People are often advised to ''look on the bright side' when they fail and move on, but the new study suggests thinking critically about these negative events can actually lead to better outcomes in the future. Instead, researchers at Rutgers University-Newark found that simply thinking about negative events could be used to help people manage stress better, and improve performance in many areas, including therapeutic settings, education and sports. Previous studies have shown that paying close attention to negative events or feelings -- by either meditating or writing about them -- can actually lead to positive outcomes.

Kathryn Hume and Carole Piovesan are powerful forces in the Toronto artificial intelligence community. Kathryn Hume is Vice President of product and strategy for Integrate.ai Carole Piovesan is a lawyer at McCarthy Tétrault LLP and the firm's lead in the area of artificial intelligence. Piovesan has appeared before various administrative tribunals, at all levels of court in Ontario, as well as at the Supreme Court of Canada. Hume and Piovesan are widely respected speakers and writers on AI and excel at communicating how AI and machine learning technologies work in everyday language.