We will be as unknowledgeable about what machines know about us as they are about what we know about them.
Emerging projects suggest technologies that could supply the grid, datacenters, and other energy-hungry facilities with electricity from space could be here within five years.
Assessing whether an AI system can independently “rediscover” known scientific breakthroughs.
Seeking a transformative memory scheme that grows in performance and capacity as the infrastructure expands.
The Resource Public Key Infrastructure (RPKI) was standardized to add cryptographic security to Internet routing. With over 50% of announced BGP prefixes protected with RPKI today, the protocol already impacts significant parts of Internet traffic. In addition to its growing adoption, there is also increasing political interest in RPKI. The White House indicated in its Roadmap to Enhance Internet Routing Security , on September 4, 2024, that RPKI is a mature and readily available technology for securing inter-domain routing. The Roadmap attributes the main obstacles toward wide adoption of RPKI to a lack of understanding, lack of prioritization, and administrative barriers. This article presents the first comprehensive study of the maturity of RPKI as a viable, production-grade technology. We find that current RPKI implementations still lack production-grade resilience and are plagued by software vulnerabilities, inconsistent specifications, and operational challenges, raising significant security concerns. The deployments lack experience with full-fledged, strict RPKI validation in production environments and operate in fail-open mode. We provide recommendations to improve RPKI resilience and guide stakeholders in securing their deployments against current and emerging threats. The numerous issues we have discovered with the current RPKI specifications and implementations inevitably lead to the question: Is RPKI sufficiently stable to align with the expectations outlined in the White House roadmap? Certainly, it is not perfect, but is it good enough? The answer, as we will explore, varies depending on one’s viewpoint.
Highlighting the need for controlled AI integration in peer review and harmonized policies governing AI use in academic evaluation.
Carlos Baquero looks at the potential impact of agentic AI on scientific research and peer review.
Efforts to improve gender diversity in the computing industry have traditionally centered on the educational pipeline and early career entry. However, less attention has been paid to a critical part of the picture: employee retention within the high-tech workforce. Among those already established in professional roles, some choose to leave or shift careers later on. What can lead to these decisions—particularly among women? This study addresses that question through a gender-informed analysis of the perceptions among early and mid-career computing professionals. We examine three focal areas: intentions to leave the high-tech industry, perceived triggers for exit, and workplace priorities. Using a sequential mixed-methods approach—focus groups followed by a large-scale survey—we analyze responses from 352 computer science alumni who graduated over the past 12 years from an academic college with a high industry-placement rate. Our findings reveal both shared priorities and distinct gender-based patterns. Men are significantly more likely to report no intention to leave and express more positive attitudes toward their workplaces than women. Women identify work-life balance, workplace environment, and working hours as key exit triggers, whereas men identify compensation most often. While compensation ranks as the top workplace priority for both groups, secondary preferences differ. A very interesting insight is that workplace priorities and exit triggers do not always align—some highly valued factors appear necessary but not sufficient to drive exit decisions, and what people state as “important” and “trigger to leave” do not always match. We also bring an interesting view on organizational values. By highlighting the nuanced experiences of those already embedded in the high-tech sector, this study offers insights on the gendered dynamics of retention in the computing profession. These insights are particularly timely, as emerging AI technologies are expected to reshape roles, skill requirements, and potentially retention, including gender, with mid-career professionals likely to be among the most affected.
Bertrand Meyer considers how disputes over intelligence may boil down to definitions.
As concerns grow over the role AI plays in delusions and psychosis, researchers look for answers .
From bionic eyes restoring sight to AI-powered haptics creating novel senses, researchers are blurring the line between restoration and enhancement.
