Why Are User Acceptance Tests Such a Hassle?
In the reality of many projects, UAT often becomes irreplaceable and needs to
be extensive, covering a larger part of the testing pyramid than recommended
... Automated end-to-end tests often fail to cover third-party integrations
due to limited access and support, requiring UAT. For instance, if a system
integrates with an analytics tool, any changes to the system may require
stakeholders to verify the results on the tool as well. ... In industries such
as finance, healthcare, or aviation, where regulatory compliance is critical,
UATs must ensure that the software meets all legal and regulatory
requirements. ... In projects involving intricate business workflows, many
UATs may be necessary to cover all possible scenarios and edge cases. ... This
process can quickly become complex when dealing with numerous test cases,
engineering teams, and stakeholder groups. This complexity often results in
significant manual effort in both testing and collaboration. Even though UATs
are cumbersome, most companies do not automate them because they focus on
validating business requirements and user experiences, which require
subjective assessment. However, automating UAT can save testing hours and the
effort to coordinate testing sessions.
The full-stack architect: A new lead role for crystalizing EA value
First, the full-stack architect could ensure the function’s other architects
are indeed aligned, not only among themselves, but with stakeholders from both
the business and engineering. That last bit shouldn’t be overlooked, Ma says.
While much attention gets paid to the notion that architects should be able to
work fluently with the business, they should, in fact, work just as fluently
with Engineering, meaning that whoever steps into the role should wield deep
technical expertise, an attribute vital to earning the respect of engineers,
and one that more traditional enterprise architects lack. For both types of
stakeholders, then, the full-stack architect could serve as a single point of
contact. Less “telephone,” as it were. And it could clarify the value
proposition of EA as a singular function — and with respect to the business it
serves. Finally, the role would probably make a few other architects
unnecessary, or at least allow them to concentrate more fully on their
respective principal responsibilities. No longer would they have to coordinate
their peers. Ma’s inspiration for the role finds its origin in the full-stack
engineer, as Ma sees EA today evolving similarly to how software engineering
evolved about 15 years ago.
Groundbreaking 8-Photon Qubit Chip Accelerates Quantum Computing
Quantum circuits based on photonic qubits are among the most promising
technologies currently under active research for building a universal quantum
computer. Several photonic qubits can be integrated into a tiny silicon chip
as small as a fingernail, and a large number of these tiny chips can be
connected via optical fibers to form a vast network of qubits, enabling the
realization of a universal quantum computer. Photonic quantum computers offer
advantages in terms of scalability through optical networking,
room-temperature operation, and the low energy consumption. ... The research
team measured the Hong-Ou-Mandel effect, a fascinating quantum phenomenon in
which two different photons entering from different directions can interfere
and travel together along the same path. In another notable quantum
experiment, they demonstrated a 4-qubit entangled state on a 4-qubit
integrated circuit (5mm x 5mm). Recently, they have expanded their research to
8 photon experiments using an 8-qubit integrated circuit (10mm x 5mm). The
researchers plan to fabricate 16-qubit chips within this year, followed by
scaling up to 32-qubits as part of their ongoing research toward quantum
computation.
Mastering The Role Of CISO: What The Job Really Entails
A big part of a CISO’s job is working effectively with other senior
executives. Success isn’t just about technical prowess; it’s about building
relationships and navigating the politics of the C-suite. Whether you’re
collaborating with the CEO, CFO, CIO, or CLO, you must be able to work within
a broader leadership context to align security goals with business objectives.
One of the most important lessons I’ve learned is to involve key stakeholders
early and often. Don’t wait until you have a finalized proposal to present;
get input and feedback from the relevant parties—especially the CTO, CIO, CLO,
and CFO—at every stage. This collaborative approach helps you refine your
security plans, ensures they are aligned with the company’s broader strategy,
and reduces the likelihood of pushback when it’s time to present your final
recommendations. ... While technical expertise forms the foundation of the
CISO role, much of the work comes down to creative problem-solving. Being a
CISO is like being a puzzle solver—you need to look at your organization’s
specific challenges, risks, and goals, and figure out how to put the pieces
together in a way that addresses both current and future needs.
Why Future-proofing Cybersecurity Regulatory Frameworks Is Essential
As regulations evolve, ensuring the security and privacy of the personal
information used in AI training looks set to become increasingly difficult,
which could lead to severe consequences for both individuals and
organizations. The same survey went on to reveal that 30% of developers
believe that there is a general lack of understanding among regulators who are
not equipped with the right set of skills to comprehend the technology they're
tasked with regulating. With skills and knowledge in question, alongside
rapidly advancing AI and cybersecurity threats, what exactly should regulators
keep in mind when creating regulatory frameworks that are both adaptable and
effective? It's my view that, firstly, regulators should know all the options
on the table when it comes to possible privacy-enhancing technologies (PETs).
... Incorporating continuous learning within the organization is also crucial,
as well as allowing employees to participate in industry events and
conferences to stay up to speed on the latest developments and to meet with
experts. Where possible, we should be creating collaborations with the
industry — for example, inviting representatives of tech companies to give
internal seminars or demonstrations.
AI could alter data science as we know it - here's why
Davenport and Barkin note that generative AI will take citizen development to
a whole new level. "First is through conversational user interfaces," they
write. "Virtually every vendor of software today has announced or is soon to
introduce a generative AI interface." "Now or in the very near future, someone
interested in programming or accessing/analyzing data need only make a request
to an AI system in regular language for a program containing a set of
particular functions, an automation workflow with key steps and decisions, or
a machine-learning analysis involving particular variables or features." ...
Looking beyond these early starts, with the growth of AI, RPA, and other
tools, "some citizen developers are likely to no longer be necessary, and
every citizen will need to change how they do their work," Davenport and
Barkin speculate. ... "The rise of AI-driven tools capable of handling data
analysis, modeling, and insight generation could force a shift in how we view
the role and future of data science itself," said Ligot. "Tasks like data
preparation, cleansing, and even basic qualitative analysis -- activities that
consume much of a data scientist's time -- are now easily automated by AI
systems."
Scaling Small Language Models (SLMs) For Edge Devices: A New Frontier In AI
Small language models (SLMs) are lightweight neural network models designed to
perform specialized natural language processing tasks with fewer computational
resources and parameters, typically ranging from a few million to several
billion parameters. Unlike large language models (LLMs), which aim for
general-purpose capabilities across a wide range of applications, SLMs are
optimized for efficiency, making them ideal for deployment in
resource-constrained environments such as mobile devices, wearables and edge
computing systems. ... One way to make SLMs work on edge devices is through
model compression. This reduces the model’s size without losing much
performance. Quantization is a key technique that simplifies the model’s data,
like turning 32-bit numbers into 8-bit, making the model faster and lighter
while maintaining accuracy. Think of a smart speaker—quantization helps it
respond quickly to voice commands without needing cloud processing. ... The
growing prominence of SLMs is reshaping the AI world, placing a greater
emphasis on efficiency, privacy and real-time functionality. For everyone from
AI experts to product developers and everyday users, this shift opens up
exciting possibilities where powerful AI can operate directly on the devices
we use daily—no cloud required.
How To Ensure Your Cloud Project Doesn’t Fail
To get the best out of your team requires striking a delicate balance between
discipline and freedom. A bunch of “computer nerds” might not produce much
value if left completely to their own devices. But they also won’t be
innovative if not given freedom to explore and mess around with ideas. When
building your Cloud team, look beyond technical skills. Seek individuals who
are curious, adaptable, and collaborative. These traits are crucial for
navigating the ever-changing landscape of Cloud technology and fostering an
environment of continuous innovation. ... Culture plays a pivotal role in
successful Cloud adoption. To develop the right culture for Cloud innovation,
start by clearly defining and communicating your company's values and goals.
You should also work to foster an environment that encourages calculated
risk-taking and learning from failures as well as promotes collaboration and
knowledge sharing across teams. Finally, make sure to incentivise your culture
by recognising and rewarding innovation, not just successful outcomes. ...
Having a well-defined culture is just the first step. To truly harness the
power of your talent, you need to embed your definition of talent into every
aspect of your company's processes.
2025 Tech Predictions – A Year of Realisation, Regulations and Resilience
A number of businesses are expected to move workloads from the public cloud
back to on-premises data centres to manage costs and improve efficiencies.
This is the essence of data freedom – the ability to move and store data
wherever you need it, with no vendor lock-in. Organisations that previously
shifted to the public cloud now realise that a hybrid approach is more
advantageous for achieving cloud economics. While the public cloud has its
benefits, local infrastructure can offer superior control and performance in
certain instances, such as for resource-intensive applications that need to
remain closer to the edge. ... As these threats become more commonplace,
businesses are expected to adopt more proactive cybersecurity strategies and
advanced identity validation methods, such as voice authentication. The uptake
of AI-powered solutions to prevent and prepare for cyberattacks is also
expected to increase. ... Unsurprisingly, the continuous profileration of data
into 2025 will see the introduction of new AI-focused roles. Chief AI Officers
(CAIOs) are responsible for overseeing the ethical, responsible and effective
use of AI across organisations and bridging the gap between technical teams
and key stakeholders.
In an Age of AI, Cloud Security Skills Remain in Demand
While identifying and recruiting the right tech and security talent is
crucial, cybersecurity experts note that organizations must make a
conscientious choice to invest in cloud security, especially as more data is
uploaded and stored within SaaS apps and third-party,
infrastructure-as-a-service (IaaS) providers such as Amazon Web Services and
Microsoft Azure. “To close the cloud security skills gap, organizations should
prioritize cloud-specific security training and certifications for their IT
staff,” Stephen Kowski, field CTO at security firm SlashNext, told Dice.
“Implementing cloud-native security tools that provide comprehensive
visibility and protection across multi-cloud environments can help mitigate
risks. Engaging managed security service providers with cloud expertise can
also supplement in-house capabilities and provide valuable guidance.” Jason
Soroko, a senior Fellow at Sectigo, expressed similar sentiments when it comes
to organizations assisting in building out their cloud security capabilities
and developing the talent needed to fulfill this mission. “To close the cloud
security skills gap, organizations should offer targeted training programs,
support certification efforts and consider hiring experts to mentor existing
teams,” Soroko told Dice.
Quote for the day:
"If you want to achieve excellence,
you can get there today. As of this second, quit doing less-than-excellent
work." -- Thomas J. Watson
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