Quote for the day:
"Success seems to be connected with action. Successful people keep moving. They make mistakes but they don’t quit." -- Conrad Hilton
Beyond Von Neumann: Toward a unified deterministic architecture
In large AI workloads, datasets often cannot fit into caches, and the
processor must pull them directly from DRAM or HBM. Accesses can take hundreds
of cycles, leaving functional units idle and burning energy. Traditional
pipelines stall on every dependency, magnifying the performance gap between
theoretical and delivered throughput. Deterministic Execution addresses these
challenges in three important ways. First, it provides a unified architecture
in which general-purpose processing and AI acceleration coexist on a single
chip, eliminating the overhead of switching between units. Second, it delivers
predictable performance through cycle-accurate execution, making it ideal for
latency-sensitive applications such as large langauge model (LLM) inference,
fraud detection and industrial automation. Finally, it reduces power
consumption and physical footprint by simplifying control logic, which in turn
translates to a smaller die area and lower energy use. ... For enterprises
deploying AI at scale, architectural efficiency translates directly into
competitive advantage. Predictable, latency-free execution simplifies capacity
planning for LLM inference clusters, ensuring consistent response times even
under peak loads. Lower power consumption and reduced silicon footprint cut
operational expenses, especially in large data centers where cooling and
energy costs dominate budgets. Invest in quantum adoption now to be a winner in the quantum revolution
History shows that transformative compute paradigms require years of preparation
before delivering real returns. Graphics processing units (GPUs), for example,
took more than a decade of groundwork before fueling the AI revolution that now
powers almost every sector of the economy. Organizations that invested early
positioned themselves to capture this growth, while those who waited paid more,
were caught flat-footed, and lost ground to competitors. Quantum will follow the
same trajectory. ... Investing in readiness today reduces both risk and cost. By
spreading integration work over time, organizations avoid the disruption and
price premium of a sudden adoption push once the full enterprise value of
quantum computing is achieved. Budget holders know that rushed, unplanned
programs often exceed forecasts and erode margins. Smaller projects with clear
deliverables can be managed within existing budgets and allow lessons to be
learned incrementally, lowering both financial exposure and operational risk.
For decision-makers, this creates a predictable investment profile rather than a
costly “big bang” rollout. Early engagement also builds skills at a fraction of
the future cost. Recruiting or retraining talent under pressure once the market
overheats will be significantly more expensive.
What an IT career will look like in 5 years — and how to thrive through the changes
Success in the near future will depend less on narrow expertise — mastering a
specific technology stack for example — and more on evaluating, adapting, and
applying the right tools to solve organizational problems. “People shift into
cloud, security, data, or AI work depending on business need,” says Chris
Camacho, COO and co-founder at Abstract Security. “Titles matter less than
visible proof-of-work — small wins shared internally or publicly. Pick a lane
and go deep, then layer AI expertise on top. And show your work — on GitHub,
LinkedIn, wherever recruiters can see results.” Justina Nixon-Saintil, global
chief impact officer at IBM, says success in the future will favor those who are
adaptable and use AI to amplify creativity rather than replace it. “Technology
roles are evolving from traditional tasks into more dynamic, interdisciplinary
pathways that blend technical expertise with strategic thinking,” Nixon-Saintil
says. “Those who can navigate the ethical challenges of AI and technology will
succeed, leveraging innovation responsibly to solve complex problems and
anticipate evolving business needs. You’ll not only future-proof your career but
also unlock new opportunities for growth and innovation.” Beth Scagnoli, vice
president of product management of Redpoint Global, agrees the successful pro of
the near future will easily move between related but traditionally separate IT
domains, such as system architecture and development.
Using AI as a Therapist? Why Professionals Say You Should Think Again
It can be incredibly tempting to keep talking to a chatbot. When I conversed
with the "therapist" bot on Instagram, I eventually wound up in a circular
conversation about the nature of what is "wisdom" and "judgment," because I was
asking the bot questions about how it could make decisions. This isn't really
what talking to a therapist should be like. Chatbots are tools designed to keep
you chatting, not to work toward a common goal. One advantage of AI chatbots in
providing support and connection is that they're always ready to engage with
you. That can be a downside in some cases, where you might need to sit with your
thoughts, Nick Jacobson, an associate professor of biomedical data science and
psychiatry at Dartmouth, told me recently. ... While chatbots are great at
holding a conversation -- they almost never get tired of talking to you --
that's not what makes a therapist a therapist. They lack important context or
specific protocols around different therapeutic approaches, said William Agnew,
a researcher at Carnegie Mellon University and one of the authors of the recent
study alongside experts from Minnesota, Stanford and Texas. "To a large extent
it seems like we are trying to solve the many problems that therapy has with the
wrong tool," Agnew told me. "At the end of the day, AI in the foreseeable future
just isn't going to be able to be embodied, be within the community, do the many
tasks that comprise therapy that aren't texting or speaking."
CISOs rethink the security organization for the AI era
“Organizations that have invested in security over time are seeing efficiencies
by layering AI-driven tools into their workflows,” Oleksak says. “But those who
haven’t taken security seriously are still stuck with the same exposures they’ve
always had. AI doesn’t magically catch them up.’” In fact, because attackers are
using AI to make phishing, scanning, and deepfakes cheaper and faster, Oleksak
adds, the gap between mature and unprepared organizations is widening. ...
“We’re now embedding cybersecurity into AI initiatives from the start, working
closely across teams to ensure innovation is both safe and ethical,” she
stresses. “Our commitment to responsible AI means every solution is designed
with transparency, fairness, and accountability in mind.” Jason Lander,
senior vice president of product management at Aya Healthcare, who manages
security for the organization, is also seeing a change in the dynamics between
cybersecurity and IT. “AI is noticeably reshaping how security and IT
departments collaborate, streamline workflows, blend responsibilities, make
decisions and redefine trust dynamics,” he says. ... “IT’s focus is on
speed, efficiency, and enabling the business, while the CISO’s focus is on
protecting the business. That distinction is often misunderstood,” he maintains.
“As AI introduces powerful new risks, from deepfakes and AI-driven phishing to
employees unintentionally exposing sensitive IP through AI queries, only the
CISO is positioned to anticipate and mitigate these threats.”Why Secure Data Migration is the Next Big Boardroom Priority
Industries with the highest dependency on sensitive data are leading the way in
secure migration. Financial services, with their heavy regulatory
responsibilities and high stakes for customer trust, are among the most
proactive industries when it comes to secure data migration. Banks moving from
legacy mainframes to cloud-native platforms know that a single misstep could
cascade into systemic risk. Healthcare, another high-stakes sector, faces
similar urgency. ... Technology hyperscalers such as Microsoft, Google, and
Amazon Web Services (AWS) play a dual role: enablers of secure migration and,
simultaneously, critical dependencies for enterprises. This reliance brings
resilience but also concentration risk. Many CIOs remain concerned about vendor
lock-in, even as few alternatives exist at a comparable scale. Enterprises must
therefore ensure secure migration while also diversifying their strategy to
avoid overreliance on a single ecosystem. ... The shift is clear: secure data
migration is no longer an IT department problem. It is a board-level agenda
item, shaping strategy and shareholder value. As per the latest findings, 82% of
CISOs now directly report to the CEO’s, underscoring their elevated importance.
The World Economic Forum has gone further, warning in its 2025 Global Risks
Report that data migration failures represent an underappreciated threat to
global business resilienceHow self-learning AI agents will reshape operational workflows
Experience-based training for AI agents offers strong potential because it
allows agents to act autonomously in real-world situations, guided by rewards
that emerge from the environment. In the context of operations management, this
means agents can learn from past incidents, events, customer tickets,
application and infrastructure metrics and logs, as well as any other metrics
made available to them. While modern-day hype cycles demand rapid results, much
of the promise of AI agents lies in how they will improve operations management
over time. Given enough time and training data, the AI agent will be able to
plan actions and predict their consequences in the environment—i.e., predict the
reward—much better than a human. ... Experience-based learning in this context
requires human engineers to conduct post-incident reviews to understand an
incident and establish actions to prevent that incident from recurring. However,
in many cases, the learnings from a post-incident review are siloed to
individual teams and not shared with the wider organization. ... Given that
organizations do not consistently conduct post-incident learning reviews or
share their findings across the wider organization, operations management is
ripe for “agentification” powered by self-learning agents. Instead of burdening
busy human engineers with post-incident reviews, AI agents can conduct these
reviews and then apply this valuable experience-based training data.
The DPDPA’s impact on law firms
Most of the personal data processing in HR departments is for purposes related to employment. The DPDPA does provide exemption from obtaining consent from employment purposes under Sec. 7(i) ... However, a reading of this Section would indicate that this exemption is applicable only to current employees and it excludes all processing which happens post-employment or pre-employment. In some instances, where an employee or intern voluntarily emails their resumes to HR departments and the HR departments do not consider the application or take any action on the resume received through email, the DPDPA compliances will not kick in as DPDPA does not apply to personal data which is provided voluntarily by a data principal. But HR departments will need to be vigilant about data collected through designated online portals available on their websites, as in such a case, they can be said to be actively inviting applications unlike the former scenario wherein a candidate is voluntarily sharing their data. ... Under Section 3 of the DPDPA, any foreign entity offering services to individuals in India falls within the law’s extra-territorial scope. ... Several law firms in India have shown significant efforts in enhancing operational standards to ensure that client and partner data is handled safely. Several law firms have implemented standards like ISO 27001, which improves information security, risk management and compliance with regulations.Is quantum computing poised for another breakthrough?
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“Almost all of us in the quantum computing field are absolutely convinced,”
Kulkarni said. “But even the skeptics who always thought this was something of
the future and never really going to materialize, I think, can concur with us
that this is going to happen.” ... Quantum processors currently provide
physicists and other scientists with the tools to do big research projects that
simply aren’t realistic with other computers. That’s the main use of the
technology for now, Boixo said, but as things continue to move forward, the pool
of who will use quantum computers will grow. Of course, it’s not just scientists
trying to uncover the limits of quantum technology who are using the computers.
Marc Lijour, a researcher with the Institute of Electrical and Electronics
Engineers, told IT Brew that attackers are interested in how quantum computers
can potentially crack encryption much faster than traditional computers. They’re
probably already playing with the technology, and waiting until the computers
are widely available. “Attackers…are downloading everything they can at the
moment and storing it, basically copying the internet and anything they can so
they can open it later [using quantum technology],” Lijour said. That’s still a
ways in the future. Boixo estimated chaining together 50–100 logical qubits is
about five or so years away. With a number of firms looking at developing the
next level of quantum computing, it’s a race.
CISO Spotlights Cybersecurity Challenges in Education Following Kido Breach
Budget is certainly going to be a challenge for all, but more so for
state-funded schools and organizations. We do see that as being a challenge
everywhere, they have limited resources. The overwhelming feedback is that they
just don't have any money to spend, and it's perceived that, therefore, that
they can't deploy the security controls that they need. That's a big thing, but
I think an even bigger issue is the lack of expertise and time. On lots of
occasions you’ll discover institutions where there just aren’t experts on the
ground that can manage these cybersecurity risks. They often lean on IT service
providers and assume that they’re doing something about cybersecurity, whereas
that is not necessarily the case. Budget, expertise and time are big
constraints, and I think those issues are causing so many schools to be
vulnerable. ... There are plenty of things that can be done with little or no
cost. Reviewing all the users, identifying who’s got access and making sure MFA
is turned on doesn't carry a significant cost beyond somebody taking the time to
do it. That’s going to have a material impact on their posture. Most schools
will have an awareness training program, but it's probably a tick box exercise
where somebody has to do the course when they join and that’s it. Assigning one
person to really own and champion that program could make a material difference
to peoples’ awareness.
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