'Move Fast And Break Things' Doesn’t Apply To AI
Given the urgency around generative AI, those looking for a first-mover
advantage or those fearing being left behind may be tempted to adopt the "move
fast and break things" mantra. After all, it has long been a staple of Silicon
Valley culture. But following it would be a mistake in this instance. ...
Consider the analogy of building a house—you wouldn’t just start digging
immediately. You need to lay the groundwork first. You need to be planning,
consulting structural engineers, involving site visitors, commissioning
architectural drawings and building control. It is all essential work that
needs to be completed before a brick is laid. But once it has been, confidence
in the build skyrockets because there is a clear procedure to follow. Going
slower to go faster also applies to AI. Developing a strategy for AI requires
deep expertise and a first-class analysis of organizational data. This
involves getting a holistic view of the data within an organization,
understanding which elements could have inherent bias and lead to the wrong
insights and building a picture of the level of automation that could improve
operational efficiency.
Generative AI as a copilot for finance and other sectors
While advanced AI technologies such as quantum computing and blockchain have
long been a part of Moody's Analytics' IT arsenal, generative AI has spun off
many complex models. That can be challenging for a company with large data
sets that is concerned about data privacy and security, said Caroline Casey,
general manager for customer experience and innovation at the company, in an
interview. Before releasing its Research Assistant product on Dec. 4, Moody's
created an internal copilot product -- not to be confused with Microsoft
Copilot. Research Assistant is a search and analytical tool built on Azure
OpenAI and uses OpenAI's GPT-4. "We know that the purpose of this is not to
replace a human," Casey said. "It's to take out the kind of mundane work --
the trying to find information, the retrieval, the searching -- and actually
help them to focus on where they've got the best expertise." Moody's began its
journey in the summer after the CEO encouraged all employees of Moody's Corp.
to be innovators.
World’s First Cybersecurity & AI Guidelines: Experts Weigh in
Speaking to Techopedia, Nic Chavez, Field Chief Information Officer at
DataStax, noted that one of the important takeaways is the cautious and
collaborative approach employed by the UK to develop the guideline. “I think
it’s important to recognize the caution and collaboration with which NCSC
approached this endeavor. By seeking feedback from the international
community, including other NATO nations, NCSC was able to triangulate
recommendations that were reasonable, swiftly actionable and strong.” In his
reaction, Jeff Schwartzentruber, Senior Machine Learning Scientist at eSentire
and Industry Research Fellow at Toronto Metropolitan University, told
Techopedia that releasing these AI guidelines is a step in the right direction
as it will help to expand international cooperation and accelerate commitments
on the regulation and appropriate use of AI technologies. “I see this as a
positive step forward in terms of expanding the international cooperation and
discourse on the regulation and appropriate use of AI technologies. ...”
How the blockchain industry can adopt cybersecurity
While the theoretical underpinnings of blockchain offer unparalleled security
benefits, the practical implementation introduces potential vulnerabilities.
One such vulnerability lies in the exchange of data between blocks, where
cybercriminals can intercept and manipulate information. To fortify blockchain
systems against such attacks, the adoption of advanced encryption measures
becomes paramount. Just as Distributed Denial of Service (DDoS) attacks are
thwarted in traditional systems, blockchain must implement robust encryption
to safeguard data exchange between blocks. Another challenge in blockchain
security arises from censorship attacks, where malicious validators
intentionally disrupt or halt the blockchain protocol. Additionally, attackers
may masquerade as validators, gaining trust within the system and executing
Trojan attacks. To address these threats, it is essential to employ
traditional cybersecurity strategies, including encryption, key management,
and DNS hygiene. By integrating artificial intelligence (AI) into the system,
organizations can enhance their ability to detect consensus attacks,
particularly in Proof of Stake (PoS) validation methods.
SLAM Attack: New Spectre-based Vulnerability Impacts Intel, AMD, and Arm CPUs
The attack is an end-to-end exploit for Spectre based on a new feature in
Intel CPUs called Linear Address Masking (LAM) as well as its analogous
counterparts from AMD (called Upper Address Ignore or UAI) and Arm (called Top
Byte Ignore or TBI). "SLAM exploits unmasked gadgets to let a userland process
leak arbitrary ASCII kernel data," VUSec researchers said, adding it could be
leveraged to leak the root password hash within minutes from kernel memory.
While LAM is presented as a security feature, the study found that it
ironically degrades security and "dramatically" increases the Spectre attack
surface, resulting in a transient execution attack, which exploits speculative
execution to extract sensitive data via a cache covert channel. ... AMD has
also pointed to current Spectre v2 mitigations to address the SLAM exploit.
Intel, on the other hand, intends to provide software guidance prior to the
future release of Intel processors that support LAM. In the interim, Linux
maintainers have developed patches to disable LAM by default.
Taking a strategic view of telecom networks in Indo-Pacific
The Indo-Pacific is home to some of the world’s fastest-growing digital
economies harnessing technology for national governance and economic
development. Telecommunications connectivity – the internet and mobile
penetration base – forms the backbone for these economies. Unsurprisingly, the
telecom market in the region is witnessing an upgrade. By 2030, telecom
companies are expected to invest US$259 billion in the development of networks
in the region. These investments will foster the expansion of the digital economy and act as
catalysts for innovation, growth and prosperity, with 5G playing an
indispensable role in this. 5G represents a generational shift in wireless
telecommunications – anchored on higher data transfer speed and ultra-low
latency. It holds the promise of revolutionising how people communicate and
consume content on the internet and transforming edtech, telemedicine,
precision agriculture, and the Internet of Things. However, 5G technology is
not cheap, and developing economies have faced budgetary constraints in
deploying it.
How to stop digital twins from being used against you
y
Beyond device optimization and prolonged lifecycles, however, there’s a dark
side of digital twins that warrants careful consideration and mitigation
strategies. First and foremost, digital twins offer hackers another chance at
sensitive company information, particularly when the device data is stored in
plain text in the cloud. Providing these models with up-to-date data means
providing sensitive information. This goes beyond mere device information, it
can sometimes include the personally identifiable data of employees and
customers. Meanwhile, the use of international servers to run digital twin
operations further complicates things. Different jurisdictions count different
privacy requirements, meaning that cross-border data exchanges to run these
simulations can bring regulatory and compliance headaches. Additionally, the
connected devices themselves can cause security issues. For example, IoT sensors
sometimes operate on outdated and vulnerable operating systems. Additionally,
cheap devices are well-known for default credentials and unencrypted
communications, an important concern as more than two billion devices come
online next year.
The Role of Non-Executive Directors in Driving Innovation
The agile nature of startups grants them an advantage in driving disruptive
innovation. They have a greater appetite for risk and tend to be nimbler than
their established counterparts. Free from the shackles of middle management’s
confining layers and quarterly reporting pressures, these small entities are
often seen as the leaders of innovation. On the other side of the spectrum,
large companies, despite having the funds to finance innovation, tend to
exhibit risk avoidance to protect individual reputations and the status quo.
But the acquisition of innovative companies can be a strategic move for larger
corporations, provided the innovative culture of the smaller entity is
preserved in the process. ... NEDs play an important role in balancing the
need for funding innovation against potential impacts on existing business
practices. But conflict often emerges between securing immediate profits for
shareholders and investing in long-term growth fueled by innovation. However,
there is evidence that companies built for the future—those that prioritize
innovation—can generate shareholder returns almost three times greater than
those of the broader market reflected in the S&P 1200.
Surviving The Polycrisis Of Technological Singularity
First, let us agree on what a technological singularity would look like. It
is an idea that puts us in an era where predictability ceases to exist and
the conventional understanding of technological evolution is of little use.
Historically, we as a society have failed to predict the effects of
technological evolutions. Humans have usually underestimated the effects of
technological disruptions in the long term. The fusion of various
revolutionary technologies in this era, such as quantum computing,
nanotechnology, superconductivity and AI, will surely propel us into a zone
of immense possibilities and daunting uncertainties that are hard to grasp,
let alone predict. One could argue that, if we have this stage today, then
we are in the nascent stages of technological singularity. The open letter
that was written by leaders from various areas of society calling for a
pause in AI development for six months is, to me, one clear signal of the
beginning of technological singularity. We can slow down its pace, but we
may not be able to stop it. At the core of this discussion lies these
profound questions: Can humanity harness the potential of these technologies
and mitigate the corresponding risks simultaneously?
DevOps Strategies for Connected Car Development
The connected car is a complex ecosystem of software systems. These vehicles
have numerous systems that communicate with each other, the driver and the
outside world. Managing the development of these systems can be a daunting
task, and this is where DevOps strategies come in. DevOps aims to shorten
the system development life cycle and provide continuous delivery with high
software quality. This methodology is particularly suited to the complex
software systems of connected cars, as it encourages a holistic view of the
development process, ensuring that all components work together seamlessly.
Moreover, DevOps helps to manage the complexity of car software systems by
automating tasks, reducing errors and improving efficiency. The use of
automated tools for configuration management, deployment and monitoring
means less manual work, fewer mistakes, and quicker problem resolution. One
of the greatest challenges in connected car development is the need for
speed. In this fast-paced industry, companies are under pressure to develop
and deploy new features quickly to stay competitive.
Quote for the day:
"If you genuinely want something,
don't wait for it--teach yourself to be impatient." --
Gurbaksh Chahal
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