Europe’s Digital Services Act applies in full from tomorrow - here’s what you need to know
In one early sign of potentially interesting times ahead, Ireland’s Coimisiún na Meán has recently been consulting on rules for video sharing platforms that could force them to switch off profiling-based content feeds by default in that local market. In that case the policy proposal was being made under EU audio visual rules, not the DSA, but given how many major platforms are located in Ireland the Coimisiún na Meán, as DSC, could spin up some interesting regulatory experiments if it take a similar approach when it comes to applying the DSA on the likes of Meta, TikTok, X and other tech giants. Another interesting question is how the DSA might be applied to fast-scaling generative AI tools. The viral rise of AI chatbots like OpenAI’s ChatGPT occurred after EU lawmakers had drafted and agreed the DSA. But the intent for the regulation was for it to be futureproofed and able to apply to new types of platforms and services as they arise. Asked about this, a Commission official said they have identified two different situations vis-à-vis generative AI tools: One where a VLOP is embedding this type of AI into an in-scope platform — where they said the DSA does already apply.
Composable Architectures vs. Microservices: Which Is Best?
Composable architecture is a modular approach to software design and development that builds flexible, reusable and adaptable software architecture. It entails breaking down extensive, monolithic platforms into small, specialized, reusable and independent components. This architectural pattern comprises a pluggable array of modular components, such as microservices, packaged business capability (PBC), headless architecture and API-first development that can be seamlessly replaced, assembled and configured to align with business requirements. In a composable application, each component is developed independently using the technologies best suited to the application’s functions and purpose. This enables businesses to build customized solutions that can swiftly adapt to business needs. ... The composable approach has gained significant popularity in e-commerce applications and web development for enhancing the digital experience for developers, customers and retailers, with industry leaders like Shopify and Amazon taking advantage of its benefits.
Nginx core developer quits project in security dispute, starts “freenginx” fork
Comments on Hacker News, including one by a purported employee of F5, suggest
Dounin opposed the assigning of published CVEs to bugs in aspects of QUIC.
While QUIC is not enabled in the most default Nginx setup, it is included in the
application's "mainline" version, which, according to the Nginx documentation,
contains "the latest features and bug fixes and is always up to date." ...
MZMegaZone confirmed the relationship between security disclosures and Dounin's
departure. "All I know is he objected to our decision to assign CVEs, was not
happy that we did, and the timing does not appear coincidental," MZMegaZone
wrote on Hacker News. He later added, "I don't think having the CVEs should
reflect poorly on NGINX or Maxim. I'm sorry he feels the way he does, but I hold
no ill will toward him and wish him success, seriously." Dounin, reached by
email, pointed to his mailing list responses for clarification. He added,
"Essentially, F5 ignored both the project policy and joint developers' position,
without any discussion." MegaZone wrote to Ars (noting that he only spoke for
himself and not F5), stating, "It's an unfortunate situation, but I think we did
the right thing for the users in assigning CVEs and following public disclosure
practices.
Bridging Silos and Overcoming Collaboration Antipatterns in Multidisciplinary Organizations
Some problems with these anti-patterns. I'm going to talk again in threes,
I've talked about three anti-patterns, one role across many teams, product
versus engineering wars, and X-led. I'm going to talk about some of the
problems with these. The first one is one group holds the power. One group
holds all the decision-making power, and others can't properly contribute.
They aren't given the opportunity to contribute. In our first example, Anita
the designer doesn't hold any power because all she's doing is playing
catch-up. She's got no time to really contribute to decisions. In the second
anti-pattern in the product versus engineering, there's always a battle
between who holds the power. It's not collaborative, there's silos between the
two. ... Professional protectionism is about people protecting their
professional boundaries and not letting other people step into them. It's
like, "No, this is my area, you stay over there and you do your thing and I'll
do my thing over here." Maybe some people have experienced this. For example,
I was working with an organization recently and they said the user research
team didn't want to publish how they did user research, because other people
might do it.
Scalability Challenges in Microservices Architecture: A DevOps Perspective
Although microservices architectures naturally lend themselves to scalability,
challenges remain as systems grow in size and complexity. Efficiently managing
how services discover each other and distribute loads becomes complex as the
number of microservices increases. Communication across complex systems also
introduces a degree of latency, especially with increased traffic, and leads
to an increased attack surface, raising security concerns. Microservices
architectures also tend to be more expensive to implement than monolithic
architectures. Creating secure, robust, and well-performing microservices
architectures begins with design. Domain-driven design plays a vital role in
developing services that are cohesive, loosely coupled, and aligned with
business capabilities. Within a genuinely scalable architecture, every service
can be deployed, scaled, and updated autonomously without affecting the
others. One essential aspect of effectively managing microservices
architecture involves adopting a decentralized governance model, in which each
microservice has a dedicated team in charge of making decisions related to the
service
CQRS Pattern in C# and Clean Architecture – A Simplified Beginner’s Guide
When implementing Clean Architecture in C#, it’s important to recognize the
role each of the four components plays. Entities and Use Cases represent the
application’s core business logic, Interface Adapters manage the communication
between the Use Cases and Infrastructure components, and Infrastructure
represents the outermost layer of the architecture. To implement Clean
Architecture successfully, we have some best practices to keep in mind. For
instance, Entities and Use Cases should be agnostic to the infrastructure and
use plain C# classes, providing a decoupled architecture that avoids excess
maintenance. Additionally, applying the SOLID principles ensures that the code
is flexible and easily extensible. Lastly, implementing use cases
asynchronously can help guarantee better scalability. Each component of Clean
Architecture has a specific role to play in the implementation of the overall
architecture. Entities represent the business objects, Use Cases implement the
business logic, Interface Adapters handle interface translations, and
Infrastructure manages the communication to the outside world.
AI in practice - Celonis’ VP shares how AI can support system & process change
Brown said that, at the moment, Celonis is seeing AI being used to expedite
often tedious work, or work that often is prone to human error. Looking back
at the adoption of previous general purpose technologies, this makes sense.
More often than not the tools that are adopted early on are applied to use
cases that take time, don’t add a significant amount of value, and where
mistakes are easily made by people. ... Brown also had some thoughts
regarding how enterprises should consider their approach to AI adoption,
with a focus on not isolating people away from the technology - keeping them
close to the change and bringing them along on the journey. Firstly, Brown
acknowledged that this is going to be challenging, given the tendency for
employees to ‘build empires’ within enterprises and protect them at all
costs. She said: I'll go back to a phrase I used for a long, long time and I
still use: people don't hurt what they own. So if I'm invested in it, and
it's part of what I care about, I'm going to protect it and grow it. If I
boil down change management into one sentence, it’s about expectations and
accountability. So, what can I expect to be different and what do I need to
do differently?
Open Agile Architecture: A Comprehensive Guide for Enterprise Architecture Professionals
Open Agile Architecture equips you with a methodology that seamlessly
integrates Agile principles into the realm of enterprise architecture. In
today's business environment, change is constant. Open Agile Architecture
allows you to respond swiftly and effectively to evolving business needs,
technological advancements, and market dynamics. ... Collaboration is at the
heart of Agile methodologies, and Open Agile Architecture extends this
principle to enterprise architecture. By promoting cross-functional
collaboration and open communication, the methodology breaks down silos
within the organization. As a practitioner, you'll experience improved
collaboration between business and IT teams, fostering a shared
understanding of goals and priorities. ... Open Agile Architecture
emphasizes an iterative and incremental approach to development. This means
that instead of long, rigid planning cycles, you work on delivering
incremental value in shorter iterations. This not only ensures continuous
progress but also allows you to demonstrate tangible outcomes to
stakeholders regularly.
Microsoft Copilot is preparing advances in data protection
As the company has revealed through the Bing blog, Copilot is being prepared
to maximize the protection of user and company data that use this system.
With this, Microsoft wants to make it clear that the company’s priority is
to show that it has no interest in user data while using Copilot services in
its 365 versions. It is evident that Copilot is becoming a fundamental piece
of Microsoft’s brand strategy, and precisely for that reason they want to
distance it from some of the main stigmas that AI currently has. For its
part, Copilot is already deeply integrated into various Microsoft services,
such as Bing or Teams, where it offers considerable support to the user. One
of the concerns that many users have when using Artificial Intelligence is
the mere fact of being part of the learning and training process by the AI.
As these tools are constantly evolving, many of these systems used the
users’ own usage to create variations and advancements in various subjects.
However, over time, it has been shown that, in many cases, this has ended up
“dumbing down” the AI. However, many users find it quite ironic that an AI,
which is trained precisely by collecting data massively illicitly through
the Internet, has to actively demonstrate a system that ensures that Copilot
will not use user data to continue improving.
Artificial intelligence needs to be trained on culturally diverse datasets to avoid bias
Culture plays a significant role in shaping our communication styles and
worldviews. Just like cross-cultural human interactions can lead to
miscommunications, users from diverse cultures that are interacting with
conversational AI tools may feel misunderstood and experience them as less
useful. To be better understood by AI tools, users may adapt their
communication styles in a manner similar to how people learned to
“Americanize” their foreign accents in order to operate personal assistants
like Siri and Alexa. ... AI is already in use as the backbone of
various applications that make decisions affecting people’s lives, such as
resume filtering, rental applications and social benefits applications. For
years, AI researchers have been warning that these models learn not only
“good” statistical associations — such as considering experience as a
desired property for a job candidate — but also “bad” statistical
associations, such as considering women as less qualified for tech
positions. As LLMs are increasingly used for automating such processes, one
can imagine that the North American bias learned by these models can result
in discrimination against people from diverse cultures.
Quote for the day:
''Failure will never overtake me if
my de determination to succeed is strong enough.'' --
Og Mandino
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