How AI Is Driving Data Center Transformation - Part 3
According to AFCOM's 2024 State of Data Center Report, AI is already having a
major influence on data center design and infrastructure. Global hyperscalers
and data center service providers are increasing their capacity to support AI
workloads. This has a direct impact on power and cooling requirements. In terms
of power, the average rack density is expected to rise from 8.5 kW per rack in
2023 to 12 kW per rack by the end of 2024, with 55% of respondents expecting
higher rack density in the next 12 to 36 months. As GPUs are fitted into these
racks, servers will generate more heat, increasing both power and cooling
requirements. The optimal temperature for operating a data center hall is
between 21 and 24°C (69.8 - 75.2°F), which means that any increase in rack
density must be accompanied by improvements in cooling capabilities. ... The
efficiency of a data center is measured by a metric called power usage
efficiency, PUE, which is the ratio of the total amount of power used by a data
center to the power used by its computing equipment. To be more efficient, data
center providers aim to reduce their PUE rating and bring it closer to 1. A way
to achieve that is to reduce the power consumed by the cooling units through
advanced cooling technologies.
The Intellectual Property Risks of GenAI
Boards and C-suites that have not yet had discussions about the potential risks
of GenAI need to start now. “Employees can use and abuse generative AI even when
it is not available to them as an official company tool. It can be really
tempting for a junior employee to rely on ChatGPT to help them draft
formal-sounding emails, generate creative art for a PowerPoint presentation and
the like. Similarly, some employees might find it too tempting to use their
phone to query a chatbot regarding questions that would otherwise require
intense research,” says Banner Witcoff’s Sigmon. “Since such uses don’t
necessarily make themselves obvious, you can’t really figure out if, for
example, an employee used generative AI to write an email, much less if they
provided confidential information when doing so. This means that companies can
be exposed to AI-related risk even when, on an official level, they may not have
adopted any AI.” ... “As is the case with the use of technology within any large
organization, successful implementation involves a careful and specific
evaluation of the tech, the context of use, and its wider implications including
intellectual property frameworks, regulatory frameworks, trust, ethics and
compliance,” says Raeburn in an email interview.
The 10x Developer vs. AI: Will Tech’s Elite Coder Be Replaced?
We’re seeing AI tools that can smash out complex coding tasks in minutes and
take even your best senior devs’ hours. At Cosine, we’ve seen this firsthand
with our AI, Genie. Many of the tasks we tested were in the four to six-hour
range, and Genie could complete them in four to six minutes. It’s a genuine
superhuman thing to be able to solve problems that quickly. But here’s where it
gets interesting. This isn’t just about raw output. The real mind-bender is that
AI is starting to think like an engineer. It’s not just spitting out code — it’s
solving problems. ... Suppose we’re looking slightly more pragmatically at what
AI could signal for career progression. In that case, there is a counterargument
that junior developers won’t be exposed to the same level of problem-solving or
acquire the same skill sets, given the availability of AI. This creates a
complete headache for HR. How do you structure career progression when the
traditional markers of seniority — years of experience, deep technical knowledge
— might not mean as much? I think we’ll see a shift in focus. Companies will
probably lean more on whether you fulfilled your sprint objectives and shipped
what you wanted on time instead of going deeper. As for the companies
themselves? Those who don’t get on board with AI coding tools will get left in
the dust.
The 5 gears of employee well-being
Ritika is of view that managing employees’ and organisational expectations
requires clear communication from the leadership. “It offers employees a
transparent view of the organisation's direction and highlights how their
contributions drive Amway's success and growth. Our leadership prioritises
transparency, ensuring that employees have a clear understanding of the
organisation’s direction and how their individual and collaborative efforts
contribute to collective goals. This approach fosters a strong sense of purpose
and engagement while aligning with the vision and desired culture of the
company.” She further calls for having a robust feedback mechanism that allows
employees an opportunity to share their honest feedback on areas that matter the
most and the ones that impact them. “We believe in the feedback flywheel, our
bi-annual culture and employee engagement survey allow employees an opportunity
to share feedback. Each feedback is followed by a cycle of sharing results and
action planning.” She further adds that frequent check-in conversations between
the upline and team members ensure there is clarity of expectations, our
performance management system ensures there are 3 formal check-in conversations
that are focused on coaching and development and not ‘judgement’.
Agentic AI swarms are headed your way
OpenAI launched an experimental framework last month called Swarm. It’s a
“lightweight” system for the development of agentic AI swarms, which are
networks of autonomous AI agents able to work together to handle complex tasks
without human intervention, according to OpenAI. Swarm is not a product. It’s an
experimental tool for coordinating or orchestrating networks of AI agents. The
framework is open-source under the MIT license, and available on GitHub. ... One
way to look at agentic AI swarming technology is that it’s the next powerful
phase in the evolution of generative AI (genAI). In fact, Swarm is built on
OpenAI’s Chat Completions API, which uses LLMs like GPT-4. The API is designed
to facilitate interactive “conversations” with AI models. It allows developers
to create chatbots, interactive agents, and other applications that can engage
in natural language conversations. Today, developers are creating what you might
call one-off AI tools that do one specific task. Agentic AI would enable
developers to create a large number of such tools that specialize in different
specific tasks, and then enable each tool to dragoon any others into service if
the agent decides the task would be better handled by the other kind of tool.
How To Develop Emerging Leaders In Your Organization
Mentorship and coaching are critical for unlocking the leadership potential of
emerging talent. By pairing less experienced employees with seasoned leaders,
companies provide invaluable hands-on learning experiences beyond formal
training programs. These relationships allow future leaders to observe
high-level decision-making in action, receive personalized feedback, and
cultivate their leadership instincts in real-world scenarios. ... While
technical skills are essential, leadership success depends heavily on soft
skills like emotional intelligence, communication, and adaptability. These
skills help leaders navigate team dynamics, inspire trust, and handle
organizational challenges with confidence. Workshops, problem-solving
exercises, and leadership programs are effective for developing these
abilities. ... Leadership development can’t happen in a vacuum. One of the
most effective ways to accelerate growth is through “stretch assignments,”
opportunities that push employees beyond their comfort zones by challenging
them with responsibilities that test their leadership abilities. These
assignments expose future leaders to high-stakes decision-making,
cross-functional collaboration, and strategic thinking, all of which prepare
them for the demands of more senior roles.
CIOs look to sharpen AI governance despite uncertainties
There is no dearth of AI governance frameworks available from the US
government and European Union, as well as top market researchers, but no
doubt, as gen AI innovation outpaces formal standards, CIOs will need to enact
and hone internal AI governance policies in 2025 — and enlist the entire
C-suite in the process to ensure they are not on the hook alone, observers
say. ... “Governance is really about listening and learning from each other as
we all care about the outcome, but equally as important, howwe get to the
outcome itself,” Williams says. “Once you cross that bridge, you can quickly
pivot into AI tools and the actual projects themselves, which is much easier
to maneuver.” TruStone Financial Credit Union is also grappling with
establishing a comprehensive AI governance program as AI innovation booms.
“New generative AI platforms and capabilities are emerging every week. When we
discover them, we block access until we can thoroughly evaluate the
effectiveness of our controls,” says Gary Jeter, EVP and CTO at TruStone,
noting, as an example, that he decided to block access to Google’s NotebookLM
initially to assess its safety. Like many enterprises, TruStone has deployed a
companywide generative AI platform for policies and procedures branded as
TruAssist.
Design strategies in the white space ecosystem
AI compute cabinets can weigh up to 4,800 pounds, raising concerns about floor
load capacity. Raised floors offer flexibility for cabling, cooling, and power
management but may struggle with the weight demands of high-density setups.
Slab floors are sturdier but come with their own design and cost challenges,
particularly for liquid cooling, which can pose risks if leaks occur. This
isn’t just a financial concern – it’s also about safety. “As we integrate
various trades and systems into the same space with multiple teams working
alongside each other, safety becomes paramount. Proper structural load
assessments and seismic bracing, especially in earthquake-prone areas, are
essential to ensure the raised floor can handle the weight,” Willis
emphasizes. ... As the landscape of high-performance computing continues to
grow and evolve, so too do the designs of data center cabinets. These changes
are driven by the need for deeper and wider cabinets that can support a
greater number of power distribution units (PDUs) and cabling. The emphasis is
not just on accommodating equipment, but also on optimizing space and power
capacity to avoid the network distance limitations that can arise when
cabinets become too wide.
Costly and struggling: the challenges of legacy SIEM solutions
The main problem organizations face with legacy SIEM systems is the massive
amount of unstructured data they produce, making it hard to spot signs of
advanced threats such as ransomware and advanced persistent threat groups.
“These systems were built primarily to detect known threats using
signature-based approaches, which are insufficient against today’s
sophisticated, constantly evolving attack techniques,” Young says. “Modern
threats often employ subtle tactics that require advanced analytics,
behavior-based detection, and proactive correlation across multiple data
sources — capabilities that many legacy SIEMs lack. In addition, legacy SIEM
systems typically don’t support automated threat intelligence feeds, which are
crucial for staying ahead of emerging threats, according to Young. “They also
lack the ability to integrate with security orchestration, automation, and
response tools, which help automate responses and streamline incident
management.” Without these modern features, legacy SIEMs often miss important
warning signs of attacks and have trouble connecting different threat signals,
making organizations more exposed to complex, multi-stage attacks. Mellen says
SIEMS are only as good as the work that companies put into them, which is the
predominant feedback she’s received over the years from many practitioners.
Why Effective Fraud Prevention Requires Contact Data Quality Technology
From our experience the quality of contact data is essential to the
effectiveness of ID processes, influencing everything from end-to-end fraud
prevention to delivering simple ID checks; meaning more advanced and costly
techniques, like biometrics and liveness authentication, may not be necessary.
The verification process becomes more reliable when a customer’s contact
information, such as name, address, email and phone number, are accurate. With
this data ID verification technology can then confidently cross-reference the
provided information against official databases or other authoritative
sources, without discrepancies that could lead to false positives or
negatives. A growing issue is fraudsters exploiting inaccuracies in contact
data to create false identities and manipulate existing ones. By maintaining
clean and accurate contact data ID verification systems can more effectively
detect suspicious activity and prevent fraud. For example, inconsistencies in
a user’s phone or email, or an address linked to multiple identities, could
serve as a red flag for additional scrutiny.
Quote for the day:
“Disagree and commit is a really
important principle that saves a lot of arguing.” -- Jeff Bezos
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