ComputerWorld AI·
Over the years, enterprise IT execs have gotten frighteningly comfortable having little control or visibility over mission-critical apps, from SaaS to cloud and even cybersecurity. But generative AI (genAI) and agentic systems are taking that problem to a new extreme, with vendors able to dumb down a system IT is paying billions for without so much as a postcard. It’s not necessarily that AI changes are made to boost profits or revenue. Even if we accept the vendor argument that such changes are in the customer’s interest, companies still need for their systems to do on Thursday what they did on Tuesday, let alone what they did when the purchase order was signed. Alas, that is no longer the case. Consider a recent report from Anthropic that detailed a lengthy list of changes the company made to some of its AI offerings — including one that explicitly dumbed down answers — without asking or telling customers beforehand. The report describes various changes the Anthropic team made on t
Read full articleThe EU's plan highlights the need for digital sovereignty but lacks enforceable measures, risking increased reliance on US tech solutions. The post EU unveils AI cybersecurity action plan amid deepening US tech reliance appeared first on Crypto Briefing.
With the rapid progress of AI capabilities and the move to agentic systems, organizations are expanding their use cases as the technology continues to grow. That constant evolution also introduces risk, leaving IT leaders to wonder which investments will prove valuable even six months into the future. Returning to the foundational elements of AI architecture—the…
The ECB's cybersecurity mandate will likely drive increased investment in security technologies, influencing both traditional banks and crypto firms. The post European Central Bank demands cybersecurity action plans from banks by October 31 appeared first on Crypto Briefing.
Salesforce's European AI expansion could redefine enterprise tech, raising critical issues around data ownership and transparency in AI systems. The post Salesforce pours billions into European AI expansion as agentic systems reshape enterprise tech appeared first on Crypto Briefing.
LotL attacks represent a new frontier in cybersecurity, where adversaries use trusted system tools to carry out malicious activities.
CISA's use of Mythos AI highlights the growing reliance on advanced AI for cybersecurity, raising global collaboration and security risk concerns. The post CISA deploys Anthropic’s Mythos AI to hunt vulnerabilities in government code appeared first on Crypto Briefing.
South Korea’s largest telecommunications company KT has announced plans to invest 18 trillion won ($13.2 billion) over the next three years, including 6 trillion won for AI infrastructure and 12 trillion won for networks, IT, and cybersecurity, while expanding into…
Application programming interfaces have been successful because they define the limits of permissible exchange, including who may take what action, when, and under what circumstances. Those limitations create a framework for understanding the behavior of distributed systems. And they make it possible to enforce policy at the boundary between interacting systems. What constrains distributed systems isn’t access, but execution. With autonomous data movement and action occurring at machine speeds, where processes unfold sequentially over time rather than as a singular event, APIs no longer provide a sufficient means of enforcing boundaries. The problem is no longer whether a request is valid. It is whether a sequence of actions remains safe. For agentic systems, there needs to be runtime guardrails around what they can read, write, and execute. Microsegmentation, enforced through network and kernel-level policies, defines those guardrails. APIs made systems predictable APIs were successfu
