The Intersection of AI and Wi-Fi 7
Wi-Fi 7 is the newest standard in wireless networking. Though official ratification isn't expected until the end of 2024, Wi-Fi 7 client devices and wireless access points are already available. The top line speed of Wi-Fi 7 is often stated at 46 Gbps, but actual speeds will be lower. The higher speeds of Wi-Fi 7 are delivered by using a 320 MHz wide channel, increasing the transmission rate to 4K QAM and increasing the number of transmit and receive chains to 16. Another key advantage of Wi-Fi 7 is a significant reduction in packet latency, thanks to a feature called Multi-Link Operation (MLO). ... AI Autonomous Networks consolidate key performance indicators to aid decision-making. During the shift from 2.4 GHz and 5 GHz to 6 GHz networking, IT managers can use AI to expose timing and predict improvements, facilitating timely network upgrades. Another example is digital twin architecture, which simulates the network environment using real-world client analytics to model behavior, evaluate security changes, and assess configuration adjustments. The goal is to provide IT managers with tools for timely and accurate decisions.
Linux in your car: Red Hat’s milestone collaboration with exida
Red Hat’s collaboration with exida marks a significant milestone. While it may not be obvious to all of us, Linux is playing an increasingly important role in the automotive industry. In fact, even the car you’re driving today could be using Linux in some capacity. Linux is very well known and appreciated in the automotive industry with increasing attention being paid both to its reliability and its security. The phrase “open source for the open road” is now being used to describe the inevitable fit between the character of Linux and the need for highly customizable code in all sorts of automotive equipment. The safety of vehicles that get us from one place to another on a nearly daily basis has become a serious priority. ... Their focus on ensuring the safety of both individual components and the operating system as a whole is crucial. This latest achievement brings them even closer to realizing the first continuously-certified in-vehicle Linux Red Hat In-Vehicle Operating System. Their open source first approach to the organization, culture and thought process is an exemplary superset of what exida regards as a best practice for world-class safety culture.
How CIOs Can Integrate AI Among Employees Without Impacting DEI
As technology adoption accelerates, employees risk falling behind in adapting to
meet enterprise demands. This trend has been evident across computing eras, from
PCs to the current AI and Internet of Things era. Each phase widens the gap
between technology introduction and employees’ ability to use it effectively.
... To prioritize DEI in addressing employee upskilling to leverage AI, CIOs can
embrace a spectrum of initiatives, from establishing peer mentorship programs to
providing access to online courses, workshops, and conferences. The aim is to
promote educational opportunities for those most at risk of falling behind,
which will increase the cost risk in the future due to the extra cost of
retraining staff or seeking new talent. To successfully link digital dexterity
to DEI to prepare employees, CIOs should implement a training program that
equitably exposes all workforce segments to AI and the machine economy to
develop soft and technical skills. Shift the focus of AI adoption away from
solely business needs and focus on individual empowerment
What is a CAIO — and what should they know?
CAIOs and others tasked with overseeing AI deployments play an essential role in
“shaping an organization’s strategic, informed and responsible use of AI,” he
said. “There are many responsibilities baked into the role, but at its core,
it’s about steering the direction of AI initiatives and innovation to align with
company goals. AI leads must also create a culture of collaboration and
continuous learning.” ... While CAIOs might not always be seated at the C-suite
table, those who are there are keenly focused on genAI and its potential to
drive efficiencies and profits. Without an executive guiding those deployments,
achieving the performance and ROI organizations seek will be tough, she said.
“It’s hard to imagine how pieces come together and how you’d bring together so
many players,” Kosar said, noting that PwC has more than a dozen different LLMs
running internally to power AI tools and products in virtually every business
unit. “You have to have the ability to do short-term and long-term planning and
balance the two and stay focused on innovation,” she continued. “At the same
time, you need to recognize the pace of change while not getting distracted by
the latest shiny object.”
How AI is impacting data governance
Every organization needs to establish policies around the handling of its
data—informed by federal, state, industry, and international regulations as well
as internal business rules. In larger enterprises, a data governance committee
sets those policies and specifies how they should be followed in a living
document that evolves as regulations and procedures change. The natural language
capabilities of generative AI can pop out first drafts of that documentation and
make subsequent changes much less onerous. By analyzing data usage patterns,
regulatory requirements, and internal workflows, AI can help organizations
define and enforce data retention policies and automatically identify data that
has reached the end of its useful life. ... AI-powered disaster recovery systems
can help organizations develop sound recovery strategies by predicting potential
failure scenarios and establishing preventive measures to minimize downtime and
data loss. Backup systems infused with AI can ensure the integrity of backups
and, when disaster strikes, automatically initiate recovery procedures to
restore lost or corrupted data.
The impact of compliance technology on small FinTech firms
However, smaller firms often struggle to adapt quickly due to resource
constraints, leading to a more reactive compliance management approach. For
smaller firms, running on thin resources could mean higher risks. Many operate
with minimal compliance staff or assign compliance duties to employees who
juggle multiple roles. This can stretch employees too thin, making it tough to
keep up with regulatory changes or manage conflicts of interest that might
jeopardize the firm. The use of basic tools like spreadsheets and emails
increases the risk of missing important updates or failing to adequately address
identified risks due to the lack of clear ownership and effective action plans.
Furthermore, regulatory penalties can disproportionately impact smaller firms
that lack the financial buffer to absorb significant fines. The ever-evolving
regulatory landscape poses an ongoing risk to compliance. Smaller firms must
navigate a vast array of compliance policies and procedures. Even those with
dedicated compliance or legal experts face the challenge of sifting through
extensive documentation to identify relevant changes.
Revolutionising firms’ security with SASE
For Indian companies, today is an opportune time to have a well-thought
long-term SASE strategy and identify short-term consolidation tactics to achieve
your desired SASE model. There may be a change required in the firm’s IT culture
to adopt integrated networking and security teams, which involves a shift from
silo ways of working to shared control. Because no two SASE journeys are the
same, therefore, it is up to enterprises to prepare differently and plan for
different or customized outcomes. And the first step to doing so is selecting a
trusted partner to help in the assessment of your network and security roadmaps
against SASE as the reference architecture. Just as significant as the delivery
and operational components of SASE, is having a partner who understands
innovation and agility, with an eye towards the future. The partner should be
able to assist in technology evaluation, establish proof of value, and recommend
adaptations to integrate SASE components – all of which go toward laying the
foundation for the firm’s security and network roadmaps. Firms should know that
when it comes to executing SASE, it isn’t just done and dusted but a
multi-disciplinary project with moving parts.
The Next Phase of the Fintech Revolution: Inside the Disruption and the Challenges Facing Banking
The thing that’s causing the most waves right now, frankly, is the regulators.
We had evolved to this architecture where you had fintechs doing their thing.
You had sponsor banks of various types underneath who were actually bearing the
regulatory burden and holding the cash — things that only banks can really do.
And then you had these middleware companies that are generically kind of known
as banking as a service companies (BaaS). That architecture, which underpins
much of the payments, lending and banking innovation that we’ve seen, has now
been called into question by regulators and is being litigated ... The most
important theme right now is the implications of generative AI for financial
services and, not least of all, retail banking. What’s being funded right now
are basically vendors. So, this new crop of technology companies is springing up
to serve banks and financial institutions more generally and help them with
digital transformation as it relates to generative AI. So, you could think of
chatbot companies as being probably the most advanced wedge on this and customer
service generally as a way to introduce generative AI, lower OpEx and create
more customer delight.
Data Governance and AI Governance: Where Do They Intersect?
AI governance needs to cover the contents of the data fed to and retrieved
through AI, in addition to considering the level of AI intelligence. Doing so
addresses issues like biases, privacy, use of intellectual property, and misuse
of the technology. Consequently, AIG needs to guide what subject matter can be
processed through AI, when, and in what contexts. ... AIG and DG share common
responsibilities in guiding data as a product that AI systems create and
consume, despite their differences. Both governance programs evaluate data
integration, quality, security, privacy, and accessibility. ... The data
governance team audits the product data pipeline and finds inconsistent data
standards and missing attributes feeding into the AI model. However, the AI
governance team also identifies opportunities to enhance the recommendation
algorithm’s logic for weighting customer preferences. The retailer could resolve
the data quality issues through DG while AIG improved the AI model’s mechanics
by taking a collaborative approach with both data governance and AI governance
perspectives.
Enhancing security through collaboration with the open-source community
Without funding, it is difficult for open-source projects to get official
certifications. So, companies in regulated sectors that need those
certifications often can’t use open-source solutions. For the rest, open-source
really has “eaten the world.” Most modern tech companies wouldn’t exist without
open-source tools, or would have drastically different offerings. ... Too many
just download the open-source project and run away. One way for corporate
entities to get involved is by contributing bug fixes and small features. This
can be done through anonymous email accounts if it’s necessary to keep the
company’s involvement private. Companies should also use the results of their
security analysis to help improve the original project. There is some
self-interest involved here. Why should a company use its resources to maintain
proprietary patches for an open-source project when it can instead send those
patches back and have the community maintain them for free? Google has been
doing a good job of this with their OSS-FUZZ project. It has found many bugs and
helped a large number of the open-source projects using it.
Quote for the day:
"Develop success from failures.
Discouragement and failure are two of the surest stepping stones to success."
-- Dale Carnegie
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