Architecture can no longer be conceived as an isolated object, detached from the technical networks that sustain contemporary life. This condition calls for new readings and approaches.
Smart TVs are capable of tracking user data, including viewing habits and app usage, which can lead to personalized advertising and content recommendations. Users may prefer to limit this tracking to protect their privacy.
"In agentic environments, agents mutate state across data, systems, and configurations in ways that compound fast and are hard to trace," says Pranay Ahlawat, Chief Technology and AI Officer at Commvault.
When civilian banks, logistics platforms, and payment processors share physical data center infrastructure with military AI systems, those facilities become legitimate military targets under international humanitarian law - and the civilian services housed inside lose their legal protection.
"World Cloud Security Day is a useful reminder to recognize how much cloud risk now comes down to everyday access decisions and overlooked misconfigurations," says James Maude, Field CTO at BeyondTrust.
A future-proof IT infrastructure is often positioned as a universal solution that can withstand any change. However, such a solution does not exist. Nevertheless, future-proofing is an important concept for IT leaders navigating continuous technological developments and security risks, all while ensuring that daily business operations continue. The challenge is finding a balance between reactive problem solving and proactive planning, because overlooking a change can cost your organization. So, how do you successfully prepare for the future without that one-size-fits-all solution?
Sovereignty, locality, and 'alternative cloud' strategies are often treated as simple settings in hyperscaler consoles. Pick a region, check a compliance box, and move on. IT consultancy Coinerella posted about replacing a typical US-centric startup baseline with a 'Made in the EU' stack. They treat sovereignty as an architectural posture and an operating model that can save money.
There is a growing emphasis on database compliance today due to the stricter enforcement of compliance rules and regulations to safeguard user privacy. For example, GDPR fines can reach £17.5 million or 4% of annual global turnover (the higher of the two applies). Besides the direct monetary implications, companies also need to prioritize compliance to protect their brand reputation and achieve growth.
Unverified and low quality data generated by artificial intelligence (AI) models - often known as AI slop - is forcing more security leaders to look to zero-trust models for data governance, with 50% of organisations likely to start adopting such policies by 2028, according to Gartner's seers. Currently, large language models (LLMs) are typically trained on data scraped - with or without permission - from the world wide web and other sources including books, research papers, and code repositories.
"If you look at the enterprise, there's just enormous enthusiasm to deploy AI, but the problem is that the infrastructure, the power, and the operational foundation that is required to run it just aren't there," Alex Bouzari, CEO of DDN, told The Register. "And so as a result, it pops up in the financial elements with IT projects getting delayed, the GPUs being underutilized, power costs going up. And so the economics, I think, for lots of organizations don't pencil out because of these challenges."