Quote for the day:
"When I dare to be powerful - to use my strength in the service of my vision, then it becomes less and less important whether I am afraid." -- Audre Lorde
Declaring Quantum Christmas Advantage: How Quantum Computing Could Optimize The Holidays
If logistics is about moving stuff, gaming is about moving minds. And quantum
computing’s influence here is more playful, at least for now. At the
intersection of quantum and gaming, researchers are experimenting with
quantum-inspired procedural content generation. Essentially, this is using
hybrid quantum-classical approaches to generate game worlds, rules and
narratives that are bigger and more complex than traditional methods allow. ...
The holiday shopping season — part retail frenzy, part seasonal ritual and part
absolute bottom-line need for business survival — is another area where quantum
computing’s optimization chops could shine in a future-looking Christmas
playbook. Retailers are beginning to explore how quantum optimization could help
with workforce scheduling, inventory planning, dynamic pricing, and promotion
planning, all classic holiday headaches for brick-and-mortar and online
merchants alike, according to a D-Wave report. ... Finally, an esoteric — but
perhaps way more festive — application of quantum tech would be using it for
holiday analytics and personalization. Imagine real-time gift-recommendation
engines that use quantum-accelerated models to process massive datasets
instantly, teasing out patterns and preferences that help retailers suggest the
perfect present for even the hardest-to-buy-for relative. How Today’s Attackers Exploit the Growing Application Security Gap
Zero-day vulnerabilities in applications are quite common these days, even in
well-supported and mature technologies. But most zero-days aren’t that fancy.
Attackers regularly exploit some common errors developers make. A good resource
to learn from about this is the OWASP Top 10, which was recently updated to
cover the latest application security gaps. The main issue on the list is broken
access controls, which happens when the application doesn’t properly enforce who
can access what. In reality, this translates into bad actors being able to view
or manipulate data and functionality they shouldn’t have access to. Next on the
list are security misconfigurations. These are simple to tune, but given the
vast number of environments, services, and cloud platforms most applications
span, they are difficult to maintain at scale. A common example are exposed
admin interfaces, which opens the door to credential-related attacks,
particularly brute-forcing. Software supply chain failures add another layer of
risk. Modern applications rely heavily on open-source libraries, APIs, packages,
container images, and CI/CD components. Any of these can introduce
vulnerabilities or malicious code into production. A single compromised
dependency can impact thousands of downstream applications. For application
developers and enthusiasts, it is highly recommended to study the entries in the
OWASP Top 10, along with related OWASP lists such as the API Security Top 10 and
emerging AI security guidance.Data governance key to AI security
Cybersecurity was once built to respond. Today, the response alone is no longer
enough. We believe security must be predictive, adaptive, and intelligent. This
belief led to the creation of the Digital Vaccine, an evolution of Managed
Security Services (MSSP) designed for an AI-first, quantum-ready world. "Much
like a biological vaccine, Digital Vaccine continuously identifies new and
unknown attack patterns, learns from every attempted breach, and builds defence
mechanisms before damage occurs," he explained. The urgency is real, according
to the experts, because post-quantum risks will soon render many of today's
encryption methods ineffective, exposing sensitive data that was once considered
secure. At the same time, AI-powered cyber threats are becoming autonomous,
faster, and more targeted-operating at machine speed and scale. ... Almost every
AI is built on data. "It is transforming data into knowledge. Once it is
learned, we cannot remove it. So what is being fed into the data and LLModels?
No governance policies exist as of today," pointed out Krishnadas. Cybersecurity
was once built to respond. Today, the response alone is no longer enough. We
believe security must be predictive, adaptive, and intelligent. This belief led
to the creation of the Digital Vaccine, an evolution of Managed Security
Services (MSSP) designed for an AI-first, quantum-ready world.How the AI era is driving the resurgence in disaggregated storage
As AI workloads surge and accelerated computing takes the center stage, data
center architectures and storage systems must keep pace with the increasing
demand for memory and compute. Yet, the fast and ever-evolving
high-performance computing (HPC) and AI systems have different requirements
for the various IT infrastructure hardware components. While they require
Central Processing Unit (CPU) and Graphic Processing Unit (GPU) nodes to be
refreshed every couple of years to keep up with the AI workload demands,
storage solutions like high-capacity HDDs come with longer warranties (up to
five years), are therefore built to last several years longer, and don’t need
to be refreshed as often. Based on this, more and more organizations are
moving storage out of the server and embracing disaggregated infrastructures
to avoid wasting resources. ... In the AI era and ZB age, IT leaders need more
from their storage systems. They are looking for scalable, low-risk solutions
that can evolve with them, delivering an optimized cost per Terabyte ($/TB),
better energy-efficiency per TB (kW/TB), improved storage density,
high-quality, and trust to perform at scale. Disaggregated storage can be a
solution that offers precisely this flexibility of demand-driven scaling to
meet the individual requirements of data center workloads and business needs.
... With disaggregated storage, enterprises can embrace AI and HPC while no
longer being tethered to HCI architectures.
OpenAI admits prompt injection is here to stay as enterprises lag on defenses
OpenAI, the company deploying one of the most widely used AI agents, confirmed
publicly that agent mode “expands the security threat surface” and that even
sophisticated defenses can’t offer deterministic guarantees. For enterprises
already running AI in production, this isn’t a revelation. It’s validation —
and a signal that the gap between how AI is deployed and how it’s defended is
no longer theoretical. None of this surprises anyone running AI in production.
What concerns security leaders is the gap between this reality and enterprise
readiness. ... OpenAI pushed significant responsibility back to enterprises
and the users they support. It’s a long-standing pattern that security teams
should recognize from cloud shared responsibility models. The company
recommends explicitly using logged-out mode when the agent doesn't need access
to authenticated sites. It advises carefully reviewing confirmation requests
before the agent takes consequential actions like sending emails or completing
purchases. And it warns against broad instructions. "Avoid overly broad
prompts like 'review my emails and take whatever action is needed,'" OpenAI
wrote. "Wide latitude makes it easier for hidden or malicious content to
influence the agent, even when safeguards are in place." The implications are
clear regarding agentic autonomy and its potential threats. The more
independence you give an AI agent, the more attack surface you create.
The 3-Phase Framework for Turning a Cyberattack Into a Strategic Advantage
Typically, a lot of companies will panic and then look for a scapegoat when faced with a crisis. Maersk opted to realize that the root cause of the problem was not just a virus. Leaders accepted that they were bang average in terms of how they handled cybersecurity. The company also accepted that what happened may have been due to a cultural problem internally that needed to be fixed. While malware was a cause of issues, they also understood that their culture played a part, as security was seen as something that IT dealt with and not a core business thing. ... Maersk succeeded in strengthening customer trust and communication as it turned what could have been a defeat into a competitive advantage. Rather than trying to sugarcoat, they were very transparent and quickly informed customers of what was happening in the journey to recovery. Instead of telling customers, “we failed you,” they opted for a stance of “we are being tested, and we are in this together.” ... After a data disaster, your aim should not just be to recover, but you must also aim to build an “antifragile” organization that can come out stronger after a major challenge. An important step is to ensure that you fully internalize the lessons. When Maersk had to act, it did not just fix the problem. Instead, it embedded a new security system into its future planning. Accountability was added to all teams. Resilience should not just be something you aim for or use in a one-time project.Leadership And The Simple Magic Of Getting Lost
There’s a part of the brain called the hippocampus that’s deeply tied to memory
and spatial reasoning. It’s what helps us build internal maps of the world. It
helps us recognize patterns, landmarks, distance and direction. It lights up
when we have to figure things out for ourselves. When we follow turn-by-turn
directions all the time, something subtle shifts. We’re not really navigating
anymore. We’re just ... complying. It's efficient, yes. But also quieter,
mentally. There’s growing concern among neuroscientists that when we outsource
too much of this kind of thinking, we may be weakening one of the core systems
tied to memory and long-term brain health. The research is still unfolding.
Nothing is fully settled. But there’s enough there that it’s worth paying
attention. Because the brain, like the body, works on a simple principle: Use it
or lose it. ... This is why, every once in a while, I’ll let myself get a little
lost on purpose. Not dangerously. Not recklessly. Just less optimized. I’ll take
a different road. Walk through a neighborhood I don’t know. Let the uncertainty
stretch a little. Let my brain build the map instead of borrowing one. This is
the same skill we build in children when we’re teaching them how to find their
way, but inside companies, it shows up as orientation. When you’re facing
something unfamiliar—a new market, a hard strategic turn, a problem no one has
quite named yet—your job isn’t to hand your team a route. It’s to give them
landmarks: Here’s what we know. Here’s what can’t change.
Gen AI Paradox: Turning Legacy Code Into an Asset
Legacy modernization for decades was unglamorous and often postponed until the pain of technical debt surpassed the risks of migration. There is $2.41 trillion in technical debt in the United States alone. Seventy percent of workloads still run on-premises, and 70% of legacy IT software for Fortune 500 companies was developed over 20 years ago. ... It's not just about wishful thinking but is also driven by internal organizational dynamics. When we launched AWS Transform, after processing over a billion lines of code, we estimated it saved customers about 800,000 hours of manual work. But for a CIO, the true measure often relates to capacity. We observe organizations saving up to 80% in manual effort. This doesn't only mean cost reductions, but also avoiding the need to increase headcount for maintenance. For instance, I spoke with a technology leader managing a smaller team of about 200 people. His dilemma was: "Do I invest in building new functions, or do I maintain and modernize?" He told his team he wouldn't add a single person for modernization. They have to use tools to accomplish it. Using these tools, he completed a .NET transformation of 800,000 lines of code in two weeks, a project he estimated would typically take six months. The justification for the CIO is simple: save time and redirect 20% to 30% of the budget previously spent on tech debt toward innovation.5 stages to observability maturity
The first requirement is coherence. Companies must move away from fragmented
tooling and build unified telemetry pipelines capable of capturing logs,
metrics, traces, and model signals in a consistent way. For many, this means
embracing open standards such as OpenTelemetry and consolidating data sources so
AI systems have a complete picture of the environment. ... The second
requirement is business alignment. Enterprises that successfully evolve from
monitoring to observability, and from observability to autonomous operations, do
so because they learn to articulate the relationship between technical signals
and business outcomes. Leaders want to understand not just the number of errors
thrown by a microservice, but customers affected, the revenue at stake, or the
SLA exposure if the issue persists. ... A third element is AI governance. As
Nigam says, AI models change character over time, so observability must extend
into the AI layer, providing real-time visibility into model behavior and early
signs of instability. Companies that rely more heavily on AI must also accept a
new operational responsibility to ensure the AI itself remains reliable,
auditable, and secure. Finally, organizations must learn to construct guardrails
for automation. Casanova and Woodside both say the shift to autonomous
operations isn’t an overnight leap but a progressive widening of the boundary
between what humans review and what machines handle automatically.
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