How generative AI will benefit physical industries
To make generative AI’s potential a reality for a physical business, two crucial elements come into play: people and data. Investing in a highly skilled team is a given precondition for success with any business. Also critical is having a diversity of expertise, as well as a diversity of experiences, cultural touch points, and background. Drawing on this expertise and experience to inform how generative AI is developed allows more context to be built-in, and the models can be expanded to serve a global audience versus a regional or national one. Data quality in both edge computing and generative AI models is crucial. This is what has driven Motive to invest in a truly world-class annotations team. Because accuracy is so critical for the safety and optimization of our customers, this team ensures that the processes behind our use of generative AI are strong and consistent. These processes include ensuring the highest quality data and labels to train our models, and thus our products and services. At the same time, generative AI in the physical economy will only be as useful as the insights and capabilities it creates.
Do you need a larger project team?
There is plenty of anecdotal evidence in the industry where GCs have taken on data center projects in EU regions and have not fully understood the local resourcing requirements and supply chain logistics. In addition, they have incorrectly assumed that a UK labor force will be as effective as normal, when they are on rotational-based attendance in a regional project office. Instead, the solution may lie in developing smaller, fully supported, highly competent, highly motivated, and well-compensated teams capable of delivering increased outputs to realize your competitive potential – a theme also adopted by the World Quality Week in 2023. To meet the strong imperative for quick time-to-market in the industry within the context of an acute skills shortage, we argue that the solution lies in focusing on training people and empowering them with the capabilities of AI. Streamlined, lean teams with mature AI tools have a better chance of efficiently delivering on larger projects. Investment in training is crucial across the industry, particularly innovative approaches that enable smaller teams to achieve more thanks to AI assistance and other technological advancements.
Data Observability in the Cloud: Three Things to Look for in Holistic Data Platform Governance
To be truly meaningful in addressing the pain associated with data and AI
pipelines, data observability tools must expand into FinOps. It’s no longer
enough to know where a pipeline stalls or breaks -- data teams need to know how
much the pipelines cost. In the cloud, inefficient performance drives up
computing costs, which in turn drives up total costs. Tools must encompass
FinOps to provide observability into costs pertaining to both infrastructure and
computing resources, broken down by job, user, and project. They must also
include advanced analytics to provide guidance on how to make individual
pipelines cost-efficient. This will free up data teams to focus on strategic
decision-making rather than spending their time reconfiguring pipelines for
cost. ... To meet these demands, data observability solution vendors must offer
custom products that allow customers to see on a platform-specific level such
things as detailed cost visibility, efficient management of storage costs,
chargeback/showback, and where the expensive projects, queries, and users lie.
Fundamentals of Functions and Relations for Software Quality Engineering
Effective testing is not just about covering every line of code. It's about
understanding the underlying relationships. How do we effectively test the
complex relationships in our software code? Understanding functions and
relations proves an invaluable asset in this endeavor. ... It's worth noting
that while all programs can be viewed as functions in a broad sense, not all
are "pure" functions. Pure functions have no side effects, meaning they solely
rely on their inputs to produce outputs without altering any external state.
In contrast, many practical programs involve side effects, complicating their
pure function interpretation. ... While functions provide clear input-output
connections, not all relationships in software are so straightforward. Imagine
tracking dependencies between tasks in a project management tool. Here,
multiple tasks might relate to each other, forming a more complex network. ...
Relations can sometimes group elements into equivalence classes, where
elements within a class behave similarly. Testers can leverage this by testing
one element in each class, assuming similar behavior for others, saving time
and resources.
Your AI Girlfriend Is Cheating On You, Warns Mozilla
Mozilla said it could find only one chatbot that met its minimum security
standards, with a worrying lack of transparency over how the intensely
personal information that might be shared in such apps is protected. Almost
two thirds of the apps didn’t reveal whether the data they collect is
encrypted. Just under half of them permitted the use of weak passwords, with
some even accepting a password as flimsy as “1”. More than half of the apps
tested also failed to let users delete their personal data. One even claimed
that “communication via the chatbot belongs to the software.” Mozilla also
found the use of trackers—tiny pieces of code that gather information about
your device and what you do on it— was widespread among the romantic chatbots.
... The main tip is not to say anything to the chatbot that you wouldn’t want
friends or colleagues to discover, as the privacy of these services cannot be
guaranteed. Also use a strong password, request that personal data is deleted
once you’ve finished using the chatbot, opt out of having your data used to
train AI models and don’t accept phone permissions that give the chatbot
access to your location, camera, microphone or files on your device.
A Balanced Look at the Potential and Challenges of Popular LLMs
A beautiful symphony requires more than just individual talent. Ethical
considerations like potential biases and misinformation risks demand
attention. We must ensure responsible development, ensuring these LLMs don’t
become instruments of discord but rather powerful tools for good. The
potential for collaboration is even more exciting. Imagine Bard fact-checking
Claude’s poems, or Qwen providing real-time data for GPT-3.5-Turbo-0613’s code
generation. Such collaborations could lead to groundbreaking innovations, a
true ensemble performance exceeding the capabilities of any single LLM. This
is just the opening act of a much grander performance. As the music evolves,
LLMs hold immense potential. Advancements in natural language understanding
could enable nuanced conversations, personalized education could become a
reality, and creative collaboration could reach unprecedented heights. This
orchestra is just beginning its performance, and the future holds a symphony
of possibilities waiting to be composed. In short, The key lies in
understanding their technical nuances, recognizing their individual strengths,
and fostering responsible development.
Without contact prints or finger detail photos, how can an attacker hope to
get any fingerprint data to enhance MasterPrint and DeepMasterPrint dictionary
attack results on user fingerprints? One answer is as follows: the
PrintListener paper says that “finger-swiping friction sounds can be captured
by attackers online with a high possibility.” The source of the finger-swiping
sounds can be popular apps like Discord, Skype, WeChat, FaceTime, etc. Any
chatty app where users carelessly perform swiping actions on the screen while
the device mic is live. Hence the side-channel attack name – PrintListener.
... To prove the theory, the scientists practically developed their attack
research as PrintListener. In brief, PrintListener uses a series of algorithms
for pre-processing the raw audio signals which are then used to generate
targeted synthetics for PatternMasterPrint. Importantly, PrintListener went
through extensive experiments “in real-world scenarios,” and, as mentioned in
the intro, can facilitate successful partial fingerprint attacks in better
than one in four cases, and complete fingerprint attacks in nearly one in ten
cases.
ClickHouse: Scaling Log Management with Managed Services
A viable solution emerges in the merging of the advantages of open-source
tools with the efficiency of managed services. This combination effectively
addresses scalability and cost concerns, while upholding the operational
efficiency required. Striking this balance between functionality, cost, and
effort is particularly critical for teams constrained by budget and limited
engineering resources. To illustrate this approach, consider specific log
management strategies, such as the one implemented by DoubleCloud, which
embody these principles. DoubleCloud, for instance, employs services like
ClickHouse for data transfer and visualization, effectively managing
substantial log volumes within a modest budget. ClickHouse is renowned for its
efficient data compression techniques, serving as a prime example of how open
source tools, when properly managed, can significantly enhance log management
processes. This scenario provides a practical demonstration of how the
integration of open source benefits with managed services can offer optimal
solutions to the challenges previously discussed.
4 hidden risks of your enterprise cloud strategy
Cloud vendors themselves can encounter any number of business-related issues
that can challenge their ability to provide service to the standard enterprise
CIOs committed to when the contract was signed, including the introduction of
new risks. ... Many enterprise IT executives see the cloud as delivering
near-infinite scalability — something that is not mathematically true. This is
not helped by cloud marketing, which strongly implies — if not outright
promises — unlimited scalability. Most of the time, the cloud’s elasticity
affords great levels of scalability for its tenets. When emergency strikes,
however, all bets are off, says Charles Blauner, operating partner and CISO in
residence at cybersecurity investment firm Team8, and former CISO for
Citigroup, Deutsche Bank, and JP Morgan Chase. ... “CIOs believe that by using
multiple cloud providers, they think that it is improving availability, but
it’s not. All it’s doing is increasing complexity, and complexity has always
been the enemy of security,” Winckless says. “It is far more cost-effective to
use the cloud provider’s zones.” Enterprises also often fall short on the
financial and efficiency benefits promised by the cloud because they are
unwilling to trust the cloud environment’s mechanisms sufficiently — or so
argues Rich Isenberg, a partner at consulting firm McKinsey who oversees their
cybersecurity strategy practice.
Data Governance in the Era of Generative AI
GenAI accelerates trends already evident with traditional AI: the importance
of data quality and privacy, growing focus on responsible and ethical AI, and
the emergence of AI regulations. This will create both new challenges and
opportunities for DG. ... Traditional DG processes provide a well-trodden path
for proper management and usage of data across organizations: discover and
classify data to identify critical/sensitive data; map the data to policies
and other business context; manage data access and security; manage privacy
and compliance; and monitor and report on effectiveness. Similarly, as DG
frameworks expand to support AI governance, they have an important role to
play across the GenAI/LLM value chain. ... Traditional AI/ML will continue to
be critical for automating and scaling various DG processes. These include
data classification; associating policy and business context with data; and
detecting anomalies/issues and creating and applying data quality rules to fix
them. Building on these capabilities, GenAI has the potential to turbocharge
data democratization and drive dramatic gains in productivity for data teams.
Quote for the day:
"You may be good. You may even be
better than everyone esle. But without a coach you will never be as good as
you could be." -- Andy Stanley
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