Quote for the day:
“The only true wisdom is knowing that you know nothing.” -- Socrates
How AI is Becoming More Human-Like With Emotional Intelligence
The concept of humanizing AI is designing systems that can understand,
interpret, and respond to human emotions in a way that feels more natural. It
is making the AI efficient enough to pick up cues to read the room and react
as a human would but in a polished way. ... It is only natural that a
potential user will prefer to interact with someone who acknowledges the
queries and engages with them like a human. AI that sounds and responds like a
human helps build trust and rapport with users. ... AI that adapts based on
mood and tone. You cannot keep sending automated messages to your users,
especially to the ones who are irate. AI that sounds and responds like a human
helps build trust and rapport with users ... The humanization of AI makes AI
accessible and inclusive to all. Voice assistants and screen readers,
AI-powered speech-to-text, and text-to-speech tools are some great examples of
these fleets. ... As AI becomes more aware and powerful there are rising
concerns about its ethical usage. There have to be checks in place that ensure
AI doesn’t blatantly mimic human emotions to exploit users’ feelings. There
should be a trigger warning for the users to know that they are dealing with
machine-generated content. Businesses must ensure ethical AI development,
prioritizing user trust and transparency systems should be programmed to
respect user privacy and not manipulate users into making purchases or
conversions.
Beyond Trends: A Practical Guide to Choosing the Right Message Broker
In distributed systems, messaging patterns define how services communicate and
process information. Each pattern comes with unique requirements, such as
ordering, scalability, error handling, or parallelism, which guide the
selection of an appropriate message broker. ... The Event-Carried State
Transfer (ECST) pattern is a design approach used in distributed systems to
enable data replication and decentralized processing. In this pattern, events
act as the primary mechanism for transferring state changes between services
or systems. Each event includes all the necessary information (state) required
for other components to update their local state without relying on
synchronous calls to the originating service. By decoupling services and
reducing the need for real-time communication, ECST enhances system
resilience, allowing components to operate independently even when parts of
the system are temporarily unavailable. ... The Event Notification Pattern
enables services to notify other services of significant events occurring
within a system. Notifications are lightweight and typically include just
enough information (e.g., an identifier) to describe the event. To process a
notification, consumers often need to fetch additional details from the source
(and/or other services) by making API calls.
Successful AI adoption comes down to one thing: Smarter, right-size compute
A common perception in the enterprise is that AI solutions require a massive
investment right out of the gate, across the board, on hardware, software and
services. That has proven to be one of the most common barriers to adoption —
and an easy one to overcome, Balasubramanian says. The AI journey kicks off
with a look at existing tech and upgrades to the data center; from there, an
organization can start scaling for the future by choosing technology that can
be right-sized for today’s problems and tomorrow’s goals. “Rather than
spending everything on one specific type of product or solution, you can
now right-size the fit and solution for the organizations you have,”
Balasubramanian says. “AMD is unique in that we have a broad set of solutions
to meet bespoke requirements. We have solutions from cloud to data center,
edge solutions, client and network solutions and more. ... While both hardware
and software are crucial for tackling today’s AI challenges, open-source
software will drive true innovation. “We believe there’s no one company in
this world that has the answers for every problem,” Balasubramanian says. “The
best way to solve the world’s problems with AI is to have a united front, and
to have a united front means having an open software stack that everyone can
collaborate on. ...”
CDOs: Your AI is smart, but your ESG is dumb. Here’s how to fix it
Embedding sustainability into a data strategy requires a deliberate shift in
how organizations manage, govern and leverage their data assets. CDOs must
ensure that sustainability considerations are integrated into every phase of
data decision-making rather than treating ESG as an afterthought or compliance
requirement. A well-designed strategy can help organizations balance business
growth with environmental, social and governance (ESG) responsibility while
improving operational efficiency. ... Advanced analytics and AI can unlock new
opportunities for sustainability. Predictive modeling can help companies
optimize energy consumption, while AI-driven insights can identify supply
chain inefficiencies that lead to excessive waste. For example, retailers are
leveraging AI-powered demand forecasting to reduce overproduction and excess
inventory, significantly cutting down carbon emissions and waste. ...
Creating a sustainability-focused data culture requires education and
engagement across all levels of the organization. CDOs can implement
ESG-focused data literacy programs to ensure that business leaders, data
scientists and engineers understand the impact of their work on
sustainability. Encouraging collaboration between data teams and
sustainability departments ensures ESG considerations remain a priority
throughout the data lifecycle.
Five Critical Shifts for Cloud Native at a Crossroads
General-purpose operating systems can become a Kubernetes bottleneck at scale.
Traditional OS environments are designed for a wide range of use cases, carry
unnecessary overhead and bring security risks when running cloud native
workloads. Enterprises are increasingly instead turning to specialized
operating systems that are purpose-built for Kubernetes environments, finding
that this shift has advantages across security, reliability and operational
efficiency. The security implications are particularly compelling. While
traditional operating systems leave many potential entry points exposed,
specialized cloud native operating systems take a radically different
approach. ... Cost-conscious organizations (Is there another kind?) are
discovering that running Kubernetes workloads solely in public clouds isn’t
always the best approach. Momentum has continued to grow toward pursuing
hybrid and on-premises strategies for greater control over both costs and
capabilities. This shift isn’t just about cost savings, it’s about building
infrastructure precisely tailored to specific workload requirements, whether
that’s ultra-low latency for real-time applications or specialized
configurations for AI/machine learning workloads.
Moving beyond checkbox security for true resilience
A threat-informed and risk-based approach is paramount in an era of
perpetually constrained cybersecurity budgets. Begin by assessing the
organization’s crown jewels – sensitive customer data, intellectual property,
financial records, or essential infrastructure. These assets represent the
core of the organization’s value and should demand the highest priority in
protection.... Organizations frequently underestimate the risks from unmanaged
devices, also called shadow IT, and within their software supply chain. As
reliance on third-party software and libraries embedded within the
organization and in-house apps deepens, the attack surface becomes a
constantly shifting landscape with hidden vulnerabilities. Unmanaged devices
and unauthorized applications are equally problematic and can introduce
unexpected and substantial risks. To address these blind spots, organizations
must implement rigorous vendor risk management programs, track IT assets, and
enforce application control policies. These often-overlooked elements create
critical blind spots, allowing attackers to exploit vulnerabilities that
existing security measures might miss. ... Regardless of the trends, CISOs
should assess the specific threats relative to their organization and ensure
that foundational security measures are in place.
How to simplify app migration with generative AI tools
Reviewing existing documentation and interviewing subject matter experts is
often the best starting point to prepare for an application migration.
Understanding the existing system’s business purposes, workflows, and data
requirements is essential when seeking opportunities for improvement. This
outside-in review helps teams develop a checklist of which requirements are
essential to the migration, where changes are needed, and where unknowns
require further discovery. Furthermore, development teams should expect and
plan a change management program to support end users during the
migration. ... Technologists will also want to do an inside-out analysis,
including performing a code review, diagraming the runtime infrastructure,
conducting a data discovery, and analyzing log files or other observability
artifacts. Even more important may be capturing the dependencies, including
dependent APIs, third-party data sources, and data pipelines. This
architectural review can be time-consuming and often requires significant
technical expertise. Using genAI can simplify and accelerate the process.
“GenAI is impacting app migrations in several ways, including helping
developers and architects answer questions quickly regarding architectural and
deployment options for apps targeted for migration,” says Rob Skillington, CTO
& co-founder of Chronosphere.
How to Stop Expired Secrets from Disrupting Your Operations
Unlike human users, the credentials used by NHIs often don’t receive expiration
reminders or password reset prompts. When a credential quietly reaches the end
of its validity period, the impact can be immediate and severe: application
failures, broken automation workflows, service downtime, and urgent security
escalations. And unlike the food in your fridge, there’s no nosy relative to
point out that your secrets have gone bad. ... While TLS/SSL certificate
expiration often gets the most attention due to its visible impact on websites,
many types of machine credentials have built-in expiration. API keys silently
time out in backend services, OAuth tokens reach their limits, IAM role sessions
terminate, Kubernetes service account tokens expire, and database connection
credentials become invalid. ... The primary consequence of an expired credential
is a failed authentication attempt. At first glance, this might seem like a
simple fix – just replace the credential and restart the service. But in
reality, identifying and resolving an expired credential issue is rarely
straightforward. Consider a cloud-native application that relies on multiple
APIs, internal microservices, and external integrations. If an API key or OAuth
token used by a backend service expires, the application might return unexpected
errors, time out, or degrade in ways that aren’t immediately obvious.
Role of Interconnects in GenAI
The emergence of High-Performance Computing (HPC) demanded a leap in
interconnect capabilities. InfiniBand entered the scene, offering significantly
higher throughput and lower latency compared to existing technologies. It became
the cornerstone of data centers and large-scale computing environments, enabling
the rapid exchange of massive datasets required for complex simulations and
scientific computations. Simultaneously, the introduction of Peripheral
Component Interconnect Express (PCIe) revolutionized off-chip communication. ...
the scalability of GenAI models, particularly large language models, relies
heavily on robust interconnects. These systems facilitate the distribution of
computational load across multiple processors and machines, enabling the
training and deployment of increasingly complex models. This scalability is
achieved through efficient network topologies that minimize communication
bottlenecks, allowing for both vertical and horizontal scaling. Parallel
processing, a cornerstone of GenAI training, is also dependent on effective
interconnects. Model and data parallelism require seamless communication and
synchronization between processors working on different segments of data or
model components. Interconnects ensure that these processors can exchange
information efficiently, maintaining consistency and accuracy throughout the
training process.
That breach cost HOW MUCH? How CISOs can talk effectively about a cyber incident’s toll
Many CISOs struggle to articulate the financial impact of cyber incidents. “The
role of a CISO is really interesting and uniquely challenging because they have
to have one foot in the technical world and one foot in the executive world,”
Amanda Draeger, principal cybersecurity consultant at Liberty Mutual Insurance,
tells CSO. “And that is a difficult challenge. Finding people who can balance
that is like finding a unicorn.” ... Quantifying the costs of an incident in
advance is an inexact art greatly aided by tabletop exercises. “The best way in
my mind to flush all of this out is by going through a regular incident response
tabletop exercise,” Gary Brickhouse, CISO at GuidePoint Security, tells CSO.
“People know their roles so that when it does happen, you’re prepared.” It also
helps to develop an incident response (IR) plan and practice it frequently. “I
highly recommend having an incident response plan that exists on paper,” Draeger
says. “I mean literal paper so that when your entire network explodes, you still
have a list of phone numbers and contacts and something to get you started.” Not
only does the incident response plan lead to better cost estimates, but it will
also lead to a quicker return of network functions. “Practice, practice,
practice,” Draeger says.
