The ‘Great Retraining’: IT upskills for the future
As the technology ecosystem expands, Servier Pharmaceuticals’ Yunger believes
cultivating hard-to-find skill sets from within is instrumental to
future-proofing the IT organization. The company, a Google Cloud Platform
shop, came face-to-face with that reality when it became difficult to find
specialists, shifting its emphasis to growing its own talent. Yunger takes a
talent lifecycle management approach that considers the firm’s three- to
five-year strategy, aligns it to the requisite IT skills, and then matches the
plan to individualized development and training programs. “We provide our
vision of the future to our existing team and give them an opportunity to
self-select into those paths to meet our future needs,” he explains. “The
better our long-term vision, the more time we have to give our team the chance
to learn and grow.” The University of California, Riverside, which is
undertaking a similar practice to nurture IT talent from within, makes a
concerted effort to start any large-scale reskilling initiative with those
most willing to embrace change.
The double-edged sword of AI in financial regulatory compliance
As fraudsters obtain more personal data and create more believable fake IDs,
the accuracy of AI models improves, leading to more successful scams. The ease
of creating believable identities enables fraudsters to scale identity-related
scams with high success rates. Another key area where generative AI models can
be employed by criminals is during various stages of the money laundering
process, making detection and prevention more challenging. For instance, fake
companies can be created to facilitate fund blending, while AI can simplify
the generation of fake invoices and transaction records, making them more
convincing. Furthermore, by bypassing KYC/CDD checks, it’s possible to create
offshore accounts that hide the beneficial owners behind money laundering
schemes. Generating false financial statements becomes effortless and AI can
identify loopholes in legislation to facilitate cross-jurisdictional money
movements.
Growing With AI Not Against It: How To Stay One Step Ahead
The key to effectively integrating AI into your business lies in proactive
engagement. Rather than being passive recipients of technological changes,
businesses should take an active role in understanding AI's potential
applications. Reflecting on prominent companies such as Kodak and Nokia, which
once dominated their respective industries, but ultimately faltered due to
their reluctance to adopt technological advancements, underscores the
importance of embracing AI as a transformative force. Consider Netflix's
evolution from mailing in DVDs to streaming and their use of AI algorithms to
recommend personalized content to users. ... In the face of advancing AI
technology, the role of leaders is not merely to keep up but to set the pace.
By actively engaging with AI, embracing it as a partner, learning from
mistakes, and strategically adapting our approach, we position ourselves to
harness its potential to foster innovation and enable us to navigate the
future with confidence.
Metaverse and Telemedicine: Creating a Seamless Virtual Healthcare Experience
Firstly, the convergence of new core technologies like blockchain, digital
twins, convergence, and virtual hospitals into the Metaverse will empower
clinicians to offer more integrated treatment packages and programs. Secondly,
using AR and VR technologies will enhance patient experiences and outcomes.
Another benefit of the Metaverse for telemedicine is that it will facilitate
collaboration among healthcare professionals. The ability to share information
between healthcare professionals immediately will enable quicker pinpointing
of the causes of illnesses. Moreover, the Metaverse will offer new
opportunities to students and trainees to examine the human body in a safe,
virtual reality educational environment. Surgeons are already using VR, AR,
and AI technology to perform minimally-invasive surgeries, and the Metaverse
opens up new frontiers in this area. Surgeons will be able to get a complete
360-degree view of a patient’s body, allowing them to better perform complex
procedures using these immersive technologies.
Adaptive Security: A Dynamic Defense for a Digital World
Adaptive security systems employ continuous monitoring to gain real-time
insights into an organization's network, applications, and endpoints. This
continuous data collection allows for the rapid detection of abnormal behavior
and potential threats. ... Understanding the context of an activity is crucial
in adaptive security. Systems analyze not only the behavior of individual
elements but also the relationships between them. This context-awareness helps
in distinguishing between normal and malicious activities, reducing false
positives. ... Adaptive security leverages machine learning and artificial
intelligence (AI) algorithms to process vast amounts of data and identify
patterns indicative of threats. These algorithms can adapt and evolve their
detection capabilities based on new information and emerging attack vectors.
... Automation is a core element of adaptive security. When a potential threat
is detected, adaptive security systems can automatically respond by isolating
affected systems, blocking suspicious traffic, or alerting security teams for
further investigation.
The Power Duo: How Platforms and Governance Can Shape Generative AI
As you catalog the tools in your organization, consider where most of your
development takes place. Is it happening solely in notebooks requiring code
knowledge? Are you versioning your work through a tool like Github, which is
often confusing to a non-coding audience? How is documentation handled and
maintained over time? Oftentimes, business stakeholders and consumers of the
model are locked out of the development process because there is a lack of
technical understanding and documentation. When work happens in a silo,
hand-offs between teams can be inefficient and result in knowledge loss or
even operational roadblocks. This leads to results that are not trusted,
oreven worse, adoption of the outputs. Many organizations wait too long before
leveraging business experts during the preparation and build stages of the AI
lifecycle. ... This might be because only some of the glued together
infrastructure is understood by the business unit, the hand off between teams
is clunky and poorly documented, or the steps aren’t clearly laid out in an
understandable manner.
How India is driving tech developments at G20
While there were no major technology-related announcements, a lot of indirect
spillovers can be found in discussions on artificial intelligence (AI) and
crypto regulations, taking a human-centric approach to technology,
digitisation of trade documents and tech-enabled development of agriculture
and education. As a run-up, there were recommendations and policy actions for
the business sector, including the Startup20 initiative to support startup
companies and the focus on digital public infrastructure (DPI). The summit had
also cast the spotlight on climate change commitments, clean energy, and
sustainability development goals. Pradeep Gupta, founder of think tank
Security and Policy Initiatives, noted that the emphasis on climate change
initiatives at G20 would require IT to play a role in areas like equipment,
data management and analytics. “Carbon credits cannot function without good AI
and data technology in place,” he said. “DPI will also be a big lever for the
industry.” V K Sridhar ... agreed that IT will be instrumental in driving all
the climate change agreements that emerged at this G20 – both from a
technology and administrative point of view.
Executive Q&A: Developing Data-Focused Professionals
Many universities have been caught unprepared for the exploding demands in AI
skills. Most educational programs are traditional (four years) and do not
necessarily give students the specialized in-time skills they need for these
jobs. Deloitte had an interesting article about “AI whisperers” as the job of
the future, referring to enterprises’ need for employees who deeply understand
machine learning algorithms, data structures, and programming languages. Such
jobs are already being advertised. An institute of higher education needs to
be agile enough to create concentrations and certificates that quickly provide
students and existing employees with just-in-time skills. ... There is
inertia, and you can argue it is by design: universities are most comfortable
with a traditional four-year education. They know how to do that, and
education boards that approve these programs are also comfortable with that
format. However, a four-year education does not speak to all students or speak
to their needs and where they are in life.
How to Become a Database Administrator
Capacity planning is a core responsibility of database administrators.
Capacity planning is about estimating what resources will be needed – and
available – in the future. These resources include computer hardware,
software, storage, and connection infrastructure. Fortunately, planning for
infrastructure-as-a-service (IaaS) is quite similar to planning for
on-premise. The basic difference in planning is the additional flexibility
offered by the cloud. This flexibility allows DBAs to plan for the business’s
immediate needs instead of planning for needs three to four years in advance.
DBAs can also make use of the cloud’s ability to quickly scale up or down to
meet the client’s demands. ... The DBA must be consciously aware of the
business’s changing demands and the tools offered in the various clouds.
Organizing the business in preparation for surge events – such as Black Friday
or the start of school in September – and using the on-demand scalability
available in cloud platforms is a primary responsibility of the modern DBA.
Anticipating and responding to cyclical demands or major events makes the
organization much more efficient.
SSE vs SASE: What You Need to Know
The Security Service Edge (SSE) framework was also coined by Gartner, but
several years later in 2021. The SSE framework retains most of the core
elements of SASE. The key difference is that SSE is designed for IT
environments where SD-WAN is not required. SSE fits well for networks that do
not have multiple paths to reach destinations without a need for
application-based routing decisions. SSE is responsible for secure web, cloud
services, and application access. Some of the top business case scenarios in
which SSE works best is VPN replacement for remote employees. ... Typically,
those considering SSE want a purely cloud-based security platform that
provides a range of security functions at the edge of the network. As with
SASE, leading networking and security vendors also have SSE options. However,
the cloud-native nature of SSE means it is often marketed as a single platform
that can be easily deployed, managed, and scaled. For this reason, SSE will
likely gain traction at organizations looking to simplify and scale security
for remote workers and transition to cloud-native environments.
Quote for the day:
"Everything you want is on the other
side of fear." -- Jack Canfield
