Quote for the day:
“We are all failures - at least the best of us are.” -- J.M. Barrie
Extra Qubits Slash Measurement Time Without Losing Precision
Fast and accurate quantum measurements are essential for future quantum devices.
However, quantum systems are extremely fragile; even small disturbances during
measurement can cause significant errors. Until now, scientists faced a
fundamental trade-off: they could either improve the accuracy of quantum
measurements or make them faster, but not both at once. Now, a team of quantum
physicists, led by the University of Bristol and published in Physical Review
Letters, has found a way to break this trade-off. The team’s approach involves
using additional qubits, the fundamental units of information in quantum
computing, to “trade space for time.” Unlike the simple binary bits in classical
computers, qubits can exist in multiple states simultaneously, a phenomenon
known as superposition. In quantum computing, measuring a qubit typically
requires probing it for a relatively long time to achieve a high level of
certainty. ... Remarkably, the team’s process allows the quality of a
measurement to be maintained, or even enhanced, even as it is sped up. The
method could be applicable to a broad range of leading quantum hardware
platforms. As the global race to build the highest-performance quantum
technologies continues, the scheme has the potential to become a standard part
of the quantum read-out process.The leadership legacy: How family shapes the leaders we become
We’ve built leadership around performance metrics, dashboards and influence. Yet
the traits that truly sustain teams — empathy, accountability, consistency — are
often born not in corporate training but in the everyday rituals of family life.
On this International Day of Families, it’s time to reevaluate leadership models
that have long been defined by clarity, charisma and control and define it with
something deeper like care, connection and community. ... Here are five
principles drawn from healthy family systems that can reframe leadership models:
Consistency over chaos: Families thrive on routines and reliability. Leaders who
bring emotional consistency, set clear expectations and avoid reactionary
decisions foster psychological safety. Presence over performance: In families,
presence often matters more than fixing the problem. Leaders who truly listen,
offer time and engage with empathy build trust that performance alone cannot
buy. Accountability with care: Families call out mistakes, but with the intent
to support, not shame. Leaders who combine feedback with care build growth
mindsets without fear. Shared purpose over solo glory: Families move together.
In workplaces, this means shifting from individual heroism to collaborative
wins. Leaders must champion shared success. Adaptability with anchoring: Just
like families adjust to life stages, leaders need to flex without losing values.
Adapt strategy, but anchor culture.IPv4 was meant to be dead within a decade; what's happening with IPv6?
Globally, IPv6 is now approaching the halfway mark of Internet traffic.
Google, which tracks the percentage of its users that reach it via IPv6,
reports that around 46% of users worldwide access Google over IPv6 as of
mid-May 2025. In other words, given the ubiquity of Google's usage, nearly
half of Internet users have IPv6 capability today. While that’s a significant
milestone, IPv4 still carries about half of the traffic, even though it was
long expected to be retired by now. The growth has not been exponential, but
it is persistent. ... The first, and arguably largest hurdle is that IPv6 was
not designed to be backward-compatible with IPv4, a big criticism of IPv6 in
general and largely blamed for its slow adoption. An IPv6-only device cannot
directly communicate with an IPv4-only device without the help of a complex
translation gateway, such as NAT64. This means networks usually run dual-stack
support for both protocols, and IPv4 can't just be "switched off." This has
major downsides, though; dual-stack operation doubles certain aspects of
network management, requiring two address configurations, two sets of firewall
rules, and more, which increases operational complexity for businesses and
home users alike. This complexity causes a significant slowdown in deployment,
as network engineers and software developers must ensure everything works on
IPv6 in addition to IPv4. Any lack of feature parity or small
misconfigurations can cause major issues.Agentic mesh: The future of enterprise agent ecosystems
Many companies describe agents as “science experiments” that never leave the
lab. Others complain about suffering the pain of “a thousand proof-of-concepts”
with agents. The root cause of this pain? Most agents today aren’t designed to
meet enterprise-grade standards. ... As enterprises adopt more agents, a
familiar problem is emerging: silos. Different teams deploy agents in CRMs, data
warehouses, or knowledge systems, but these agents operate independently, with
no awareness of each other. ... An agentic mesh is a way to turn fragmented
agents into a connected, reliable ecosystem. But it does more: It lets
enterprise-grade agents operate in an enterprise-grade agent ecosystem. It
allows agents to find each other and to safely and securely collaborate,
interact, and even transact. The agentic mesh is a unified runtime, control
plane, and trust framework that makes enterprise-grade agent ecosystems
possible. ... Agentic mesh fulfills two major architectural goals: It lets you
build enterprise-grade agents and it gives you an enterprise-grade run-time
environment to support these agents. To support secure, scalable, and
collaborative agents, an agentic mesh needs a set of foundational components.
These capabilities ensure that agents don’t just run, but run in a way that
meets enterprise requirements for control, trust, and performance.
OpenAI launches research preview of Codex AI software engineering agent for developers
The new Codex goes far beyond its predecessor. Now built to act autonomously
over longer durations, Codex can write features, fix bugs, answer
codebase-specific questions, run tests, and propose pull requests—each task
running in a secure, isolated cloud sandbox. The design reflects OpenAI’s
broader ambition to move beyond quick answers and into collaborative work. Josh
Tobin, who leads the Agents Research Team at OpenAI, said during a recent
briefing: “We think of agents as AI systems that can operate on your behalf for
a longer period of time to accomplish big chunks of work by interacting with the
real world.” Codex fits squarely into this definition. ... Codex executes tasks
without internet access, drawing only on user-provided code and dependencies.
This design ensures secure operation and minimizes potential misuse. “This is
more than just a model API,” said Embiricos. “Because it runs in an air-gapped
environment with human review, we can give the model a lot more freedom safely.”
OpenAI also reports early external use cases. Cisco is evaluating Codex for
accelerating engineering work across its product lines. Temporal uses it to run
background tasks like debugging and test writing. Superhuman leverages Codex to
improve test coverage and enable non-engineers to suggest lightweight code
changes.
AI-Driven Software: Why a Strong CI/CD Foundation Is Essential
While AI can significantly boost speed, it also drives higher throughput,
increasing the demand for testing, QA monitoring, and infrastructure investment.
More code means development teams need to find ways to shorten feedback loops,
build times, and other key elements of the development process to keep pace.
Without a solid DevOps framework and CI/CD engine to manage this, AI can create
noise and distractions that drain engineers’ attention, slowing them down
instead of freeing them to focus on what truly matters: delivering quality
software at the right pace. ... By investing in a CI/CD platform with these
capabilities, you’re not just buying a tool — you’re establishing the foundation
that will determine whether AI becomes a force multiplier for your team or
simply creates more noise in an already complex system. The right platform turns
your CI/CD pipeline from a bottleneck into a strategic advantage, allowing your
team to harness AI’s potential while maintaining quality, security, and
reliability. To harness the speed and efficiency gains of AI-driven development,
you need a CI/CD platform capable of handling high throughput, rapid iteration,
and complex testing cycles while keeping infrastructure and cloud costs in
check. ... It is easy to get caught up in the excitement of powerful
technologies like AI and dive straight into experimentation without laying the
right groundwork for success.
Quantum Algorithm Outpaces Classical Solvers in Optimization Tasks, Study Indicates
The study focuses on a class of problems known as higher-order unconstrained
binary optimization (HUBO), which model real-world tasks like portfolio
selection, network routing, or molecule design. These problems are
computationally intensive because the number of possible solutions grows
exponentially with problem size. On paper, those are exactly the types of
problems that most quantum theorists believe quantum computers, once robust
enough, would excel at solving. The researchers evaluated how well different
solvers — both classical and quantum — could find approximate solutions to these
HUBO problems. The quantum system used a technique called bias-field digitized
counterdiabatic quantum optimization (BF-DCQO). The method builds on known
quantum strategies by evolving a quantum system under special guiding fields
that help it stay on track toward low-energy states. ... It is probably
important to note that the researchers didn’t just rely on the quantum component
and that the hybrid approach was essential in securing the quantum edge. Their
BF-DCQO pipeline includes classical preprocessing and postprocessing, such as
initializing the quantum system with good guesses from fast simulated annealing
runs and cleaning up final results with simple local searches.
How human connection drives innovation in the age of AI
When we are working toward a shared goal, there are core values and shared
aspirations that bind us. By actively seeking out this common ground and
fostering positive interactions, we can all bridge divides, both in our personal
lives and within our organizations. Feeling connection is not just good for our
own wellbeing, it is also crucial for business outcomes. According to research,
94% of employees say that feeling connected to their colleagues makes them more
productive at work, and over four times as likely to feel job satisfaction and
half as likely to leave their jobs within the next year. ... As we integrate AI
deeper into our workflows, we should be deliberate in cultivating environments
that prioritize genuine human connection and the development of these essential
human skills. This means creating intentional spaces—both physical and
virtual—that encourage open dialogue, active listening, and the respectful
exchange of diverse perspectives. Leaders should champion empathy and
relationship-building skill development within their teams, actively working to
promote thoughtful opportunities for human connection in our AI-driven
environment. Ultimately, the future of innovation and progress will be shaped by
our ability to harness the power of AI in a way that amplifies our uniquely
human capacities, especially our innate drive to connect with one another.
Enterprise Intelligence: Why AI Data Strategy Is A New Advantage
Forward-thinking enterprises are embracing cloud-native data platforms that
abstract infrastructure complexity and enable a new class of intelligent,
responsive applications. These platforms unify data access across object, file,
and block formats while enforcing enterprise-grade governance and policy. They
incorporate intelligent tiering and KV caching strategies that learn from access
patterns to prioritize hot data, accelerating inference and reducing overhead.
They support multimodal AI workloads by seamlessly managing petabyte-scale
datasets across edge, core, and cloud locations—without burdening teams with
manual tuning. And they scale elastically, adapting to growing demand without
disruptive re-architecture. ... AI-driven businesses are no longer defined by
how much compute power they can deploy but by how efficiently they can manage,
access, and utilize data. The enterprises that rethink their data
strategy—eliminating friction, reducing latency, and ensuring seamless
integration across AI pipelines—will gain a decisive competitive edge. For CIOs,
the message is clear: AI success isn’t just about faster algorithms or bigger
models; it’s about creating a smarter, more agile data architecture.
Organizations that embrace real-time, scalable data platforms will not only
unlock AI’s full potential but also future-proof their operations in an
increasingly data-driven world.
The future of the modern data stack: Trends and predictions
AI and ML are also key drivers of the modern data stack, because they are
creating new (or greatly amplifying existing) demands on data infrastructure.
Suddenly, the provenance and lineage of information is taking on new importance,
as enterprises fight against “hallucinations” and accidental exposure of PII or
PHI through AI mechanisms. Data sharing is also more important than ever,
because no single organization is likely to host all the information needed by
GenAI models itself, and will intrinsically rely on others to augment models,
RAG, prompt engineering, and other approaches when building AI-based solutions.
... The goal of simplifying data management and giving more users more access to
data has been around since long before computers were invented. But recent
improvements in GenAI and data sharing have vastly accelerated these trends —
suddenly, the idea that non-technical professionals can transform, combine,
analyze, and utilize complex datasets from inside and outside an organization
feels not just achievable, but probable. ... Advances in data sharing,
especially heterogeneous data sharing, through common formats like Iceberg,
governance approaches like Polaris, and safety and security mechanisms like
Vendia IceBlock are quickly removing the historical challenges to data product
distribution. 
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