#network interface

[techdirectarchive]

How to Configure Multiple IP Addresses on a Single or Multiple Network Cards

Configure Multiple IP Addresses on a Single or Multiple Network Cards In certain scenarios, assigning multiple IP addresses to a single Network Interface Card (NIC) can be incredibly useful. Whether you’re managing multiple applications that need to listen on the same port, or connecting to different network segments with one interface, understanding how to configure multiple IPs on a single NIC…

[mostlysignssomeportents]

But HP is still in business. Apple is still in business. Google is still in business. Microsoft is still in business. IBM is still in business. Facebook is still in business.

We don’t have those controlled burns anymore. Yesterday’s giants tower over all, forming a thick canopy. The internet is “five giant websites, each filled with screenshots of the other four.”

These tech companies have produced a lot of fire-debt. Over and over, they erupt in flames—in this short decade alone, every one of our tech giants has experienced a privacy scandal that should have permanently disqualified it from continuing to enjoy our patronage (and I do mean every one of them, including the one that spends millions telling you that it’s the pro-privacy alternative to the others).

Privacy is just one way that these firms are enshittifying themselves. There are the ghastly moderation failures, the community betrayals, the frauds and the billions squandered on follies.

We hate these companies. We hate their products. They are always on fire. They can’t help it. It’s the curse of bigness.

Companies cannot unilaterally mediate the lives of hundreds of millions — or even billions — of people, speaking thousands of languages, living in hundreds of countries.

- Let the Platforms Burn: The Opposite of Good Fires is Wildfires

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The Way the Brain Learns is Different from the Way that Artificial Intelligence Systems Learn - Technology Org

New Post has been published on https://thedigitalinsider.com/the-way-the-brain-learns-is-different-from-the-way-that-artificial-intelligence-systems-learn-technology-org/

The Way the Brain Learns is Different from the Way that Artificial Intelligence Systems Learn - Technology Org

Researchers from the MRC Brain Network Dynamics Unit and Oxford University’s Department of Computer Science have set out a new principle to explain how the brain adjusts connections between neurons during learning.

This new insight may guide further research on learning in brain networks and may inspire faster and more robust learning algorithms in artificial intelligence.

Study shows that the way the brain learns is different from the way that artificial intelligence systems learn. Image credit: Pixabay

The essence of learning is to pinpoint which components in the information-processing pipeline are responsible for an error in output. In artificial intelligence, this is achieved by backpropagation: adjusting a model’s parameters to reduce the error in the output. Many researchers believe that the brain employs a similar learning principle.

However, the biological brain is superior to current machine learning systems. For example, we can learn new information by just seeing it once, while artificial systems need to be trained hundreds of times with the same pieces of information to learn them.

Furthermore, we can learn new information while maintaining the knowledge we already have, while learning new information in artificial neural networks often interferes with existing knowledge and degrades it rapidly.

These observations motivated the researchers to identify the fundamental principle employed by the brain during learning. They looked at some existing sets of mathematical equations describing changes in the behaviour of neurons and in the synaptic connections between them.

They analysed and simulated these information-processing models and found that they employ a fundamentally different learning principle from that used by artificial neural networks.

In artificial neural networks, an external algorithm tries to modify synaptic connections in order to reduce error, whereas the researchers propose that the human brain first settles the activity of neurons into an optimal balanced configuration before adjusting synaptic connections.

The researchers posit that this is in fact an efficient feature of the way that human brains learn. This is because it reduces interference by preserving existing knowledge, which in turn speeds up learning.

Writing in Nature Neuroscience, the researchers describe this new learning principle, which they have termed ‘prospective configuration’. They demonstrated in computer simulations that models employing this prospective configuration can learn faster and more effectively than artificial neural networks in tasks that are typically faced by animals and humans in nature.

The authors use the real-life example of a bear fishing for salmon. The bear can see the river and it has learnt that if it can also hear the river and smell the salmon it is likely to catch one. But one day, the bear arrives at the river with a damaged ear, so it can’t hear it.

In an artificial neural network information processing model, this lack of hearing would also result in a lack of smell (because while learning there is no sound, backpropagation would change multiple connections including those between neurons encoding the river and the salmon) and the bear would conclude that there is no salmon, and go hungry.

But in the animal brain, the lack of sound does not interfere with the knowledge that there is still the smell of the salmon, therefore the salmon is still likely to be there for catching.

The researchers developed a mathematical theory showing that letting neurons settle into a prospective configuration reduces interference between information during learning. They demonstrated that prospective configuration explains neural activity and behaviour in multiple learning experiments better than artificial neural networks.

Lead researcher Professor Rafal Bogacz of MRC Brain Network Dynamics Unit and Oxford’s Nuffield Department of Clinical Neurosciences says: ‘There is currently a big gap between abstract models performing prospective configuration, and our detailed knowledge of anatomy of brain networks. Future research by our group aims to bridge the gap between abstract models and real brains, and understand how the algorithm of prospective configuration is implemented in anatomically identified cortical networks.’

The first author of the study Dr Yuhang Song adds: ‘In the case of machine learning, the simulation of prospective configuration on existing computers is slow, because they operate in fundamentally different ways from the biological brain. A new type of computer or dedicated brain-inspired hardware needs to be developed, that will be able to implement prospective configuration rapidly and with little energy use.’

Source: University of Oxford

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[electrivahical]

AIMA Big Sur Sport Ebike – High-Performance Fat Tire E-Bike 26

Have you experience the AIMA Big Sur Sport Ebike, a high-performance fat tire e-bike boasting 26″ wheels, 203mm brake rotors, and full UL2849 certification for safety and reliability. At Aimatech, we’re excited to unveil Big Sur, a name that represents innovation, power, and boundless possibilities. Whether you’re a tech visionary pushing the limits of artificial intelligence or an adventurer…

[auto2mation1]

The Honeywell 51401088-100 Computer Network Interface PC Board is a high-performance industrial automation component designed for seamless data communication. It ensures efficient network connectivity, enhancing system reliability and performance in critical applications. Built for durability, this PC board is ideal for Honeywell process control systems, ensuring smooth operation in demanding environments. With advanced technology, it supports fast data exchange, minimizing downtime and optimizing industrial processes. The 51401088-100 is a trusted solution for industrial automation, offering precision and stability. Upgrade your automation system with this reliable Honeywell interface PC board for enhanced connectivity and efficiency.

[mostlysignssomeportents]

Frank Wilhoit described conservativism as “exactly one proposition”:

There must be in-groups whom the law protects but does not bind, alongside out-groups whom the law binds but does not protect.This is likewise the project of corporatism. Tech platforms are urgently committed to ensuring that they can do anything they want on their platforms — and they’re even more dedicated to the proposition that you must not do anything they don’t want on their platforms.

They can lock you in. You can’t unlock yourself. Facebook attained network-effects growth by giving its users bots that logged into Myspace on their behalf, scraped the contents of their inboxes for the messages from the friends they left behind, and plunked them in their Facebook inboxes.

Facebook then sued a company that did the same thing to Facebook, who wanted to make it as easy for Facebook users to leave Facebook as it had been to get started there.

Apple reverse-engineered Microsoft’s crown jewels — the Office file-formats that kept users locked to its operating systems — so it could clone them and let users change OSes.

Try to do that today — say, to make a runtime so you can use your iOS apps and media on an Android device or a non-Apple desktop — and Apple will reduce you to radioactive rubble.

- Let the Platforms Burn: The Opposite of Good Fires is Wildfires

[drchristophedelongsblog]

Does the Age Tech take into account the fact that the arrivals are baby boomers who know what tech and AI are?

The Age Tech is evolving as baby boomers, who make up a significant portion of today's seniors, become increasingly familiar with technology.

Here's how it manifests itself

Designing more intuitive interfaces

Tech age developers strive to create user interfaces that are simple, clean, and easy to navigate, drawing inspiration from design principles used in consumer apps and devices.

This includes large touchscreens, self-explanatory icons, voice commands and interactive tutorials

Integration of artificial intelligence (AI) 

AI is increasingly used in the tech age to personalize experiences, anticipate needs and provide proactive assistance.

For example, AI systems can analyze health data to detect anomalies, recommend personalized exercises or remind people to take medication.

Chatbots and AI-powered virtual assistants also facilitate communication and access to information.

Adapting to Baby Boomers' Technological Habits

Age tech companies are conducting studies to understand how baby boomers use technology and what their specific needs are.

This allows us to develop products and services that fit seamlessly into their daily lives, taking into account their preferences in communication, entertainment and health management.

For example, knowing that many Baby Boomers use social networks like Facebook allows companies to create products that use this platform as a means of communication.

Training and support 

There are many initiatives aimed at providing older people with personalized training and support to help them use age tech technologies.

This may include workshops, online tutorials, in-home demonstrations and telephone support.

In short, the tech age recognizes that baby boomers are increasingly comfortable with technology and adapts its solutions accordingly.

The goal is to create technologies that are user-friendly, useful and tailored to the needs and preferences of this generation.

Go further

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Programming Embedded Systems (with C and GNU Development Tools)

[Programming Embedded Systems (with C and GNU Development Tools). By Michael Barr & Anthony J Massa. 2nd Edition, 1 October 2006. Publisher: O'Reilly Media. Paperback: 301 pages, Dimensions: ‎ 17.78 x 1.98 x 23.34 cm. ISBN: 978-0-596-00983-0]

In the past 15 months or so I elected to expand my personal and professional skill set to include working with small computing systems, sometimes referred to as microcontrollers.  These devices have become virtually omnipresent, in everything from automobiles and bar-code scanners to toasters and doorbells.  If you operate a late-model vehicle, for instance, you may have as many as 70 (!) of these devices in the car controlling everything from the fuel mixture to emissions to anti-lock brakes and collision avoidance sensing.

I was interested in moving into this arena as part of my career, as there were many openings for people with a strong understanding of the imperatives attendant on both the software and hardware of embedded systems.  I knew a bit about the electronics side of things and I have done software development of one sort or another most of my 40+ years as a professional, but this arena poses unique challenges and opportunities.  I knew I needed to do some specialized self-teaching, and this book seemed like a great place to start.

To start with, what exactly is an embedded system?

As the name implies, it is a system - in this case a miniature computing device - that is a component of a larger framework.  This larger framework can take on myriad forms.  Some of the largest such frameworks are satellite networks.  The embedded system comprises hardware - a central processing unit, or CPU, along with some (minimal) on-board memory and one or more electrical interfaces (e.g. a USB or RJ45 jack) through which it can communicate with the outside world. 

Unlike the computers most of us are familiar with, such as Windows or MacOS-based laptops or Linux servers, these devices often do not have an operating system (WIndows, MacOS and Linux are all operating systems) that performs many of the low-level functions needed to keep the device running and useful. 

This keeps the device flexible in terms of how it can be used, but at the expense of more detailed and subtle development and maintenance requirements.  Thus, the "software" on an embedded system may be a very small bit of computer code that simply turns on the interfaces electrically and then waits for something to happen.

Programming software for these systems is intriguing but fraught with issues that an ordinary computer user never sees.

For example, given that the memory and interface resources on these devices tend to be rather modest, it's necessary for the programmer to take care of any bookkeeping that is necessary to keep the basic functions from colliding.  If one of the interfaces is used to provide a scanned barcode to a waiting receiver, it must pass that information through some on-board memory first.

The embedded software designer needs to be sure that this information can't be corrupted, or "clobbered", by a competing task that might be, for instance, putting the scanning laser into sleep mode to save power.  Moreover, there are cases where the same locations in memory need to be shared by tasks as a part of getting work done.

But what happens if one task is trying to write data to a specific memory location while another task is trying to read from it?  Is there always a specific order in which this happens?  What happens if either operation is incomplete for some reason?  Will the device recover and continue to operate, or will it lock up?  The aforementioned are but a tiny set of examples that the developer must bear in mind.

Messrs Barr and Massa have many decades of experience between the two of them in just these kinds of environments. I was delighted to see just how easy this book is to read and how thoroughly they cover all of the issues that accompany such a software development enterprise.  They are careful to create and explain examples that use commonly-available development kits (I use an STM32 ARM Cortex-M Development Board myself; there is a photo of one such system below) and free or nearly-free software tools to break down the barriers to entry in this field.

This book is really as much about operating system design as it is about microcontroller software development; if one is interested in what nearly every operating system must do, this volume talks all about it. 

Above and beyond this, it is a wealth of anecdotes, sample code, and general wisdom that will really ease the novice into this exciting world of programming and small-device control.

I highly recommend it to anyone who wants to get down on the bare metal with computers.  It is necessary to be at least familiar with the C programming language (almost all of the examples are coded in C) and it would be very helpful to have worked with at least one Assembly language as well.  Beyond that, the only requirement for getting the most out of the book is a willingness to experiment and be delighted.

Image Credits (from above down; with thanks to copyright owners): (1) STM32 ARM Cortex-M Development Board © Copyright Owner, date unknown (2) Book Cover © O'Reilly Media 11 October 2006 (3) Michael Barr © Barr Group 2012-2025. (Anthony J Massa, no photograph found)

Kevin Gillette

Words Across Time

4 February 2025

wordsacrosstime

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https://www.futureelectronics.com/p/interconnect--modular-ethernet-connectors--modular-jacks/5569381-1-te-connectivity-2896884

Modular plug connectors, what is a modular jack, Ethernet jacks, Networking,

8 Position 2x1 Right Angle Through Hole Stacked RJ45 Modular Jack

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Optimizing Your BirdDog X1, X1 Ultra, or X4 Ultra for Wi-Fi Connectivity

New Post has been published on https://thedigitalinsider.com/optimizing-your-birddog-x1-x1-ultra-or-x4-ultra-for-wi-fi-connectivity/

Optimizing Your BirdDog X1, X1 Ultra, or X4 Ultra for Wi-Fi Connectivity

Setting up your BirdDog cameras (X1, X1 Ultra, or X4 Ultra) for optimal Wi-Fi performance is key to achieving high-quality video and minimizing latency. In this guide, we’ll walk you through the best practices for configuring your BirdDog camera system to ensure seamless wireless connectivity for NDI applications.

The Importance of High-Quality Wi-Fi for BirdDog Cameras

A reliable Wi-Fi connection is essential for the best performance when using BirdDog cameras with NDI (Network Device Interface) technology. A poor network connection can lead to increased latency, disrupted video feeds, and lower overall video quality. Ensuring your Wi-Fi setup is optimized can make a significant difference in the performance of your BirdDog camera system.

How to Plan Your Wi-Fi Network with NetSpot

Using NetSpot, a free Wi-Fi analysis tool available for Windows and Mac, is a great way to plan and optimize your network. NetSpot helps you visualize available Wi-Fi networks and their operating channels, making it easier to identify the least congested channels. This step is crucial for avoiding network interference and ensuring the best possible performance for your BirdDog cameras.

Understanding Wi-Fi Channels and Their Impact on Performance

Wi-Fi operates on two frequency bands: 2.4GHz and 5GHz. These bands are divided into multiple channels, and selecting the right channel can significantly improve your wireless connection. By avoiding congested channels that are being used by nearby networks, you can minimize interference and ensure a stable, high-performance connection for your BirdDog cameras.

Configuring Your Wi-Fi Router for Optimal Performance

To enhance your Wi-Fi connection, access your router’s web interface and adjust the settings to select the least congested channel. Most modern routers support both the 2.4GHz and 5GHz bands, and it’s essential to pick the appropriate channel on each band to avoid network interference. This simple adjustment can help improve your BirdDog camera’s Wi-Fi performance.

Automatic Channel Selection by BirdDog Cameras

Once your Wi-Fi network is properly configured with the optimal channels, your BirdDog cameras will automatically connect to these settings. This allows for improved range, lower latency, and a more stable video feed, ensuring you get the best possible performance from your BirdDog X1, X1 Ultra, or X4 Ultra.

Conclusion: Optimize Your Wi-Fi for BirdDog Camera Performance

By taking the time to plan and configure your Wi-Fi network, you can significantly enhance the performance of your BirdDog cameras. Using tools like NetSpot for network planning, selecting the right channels, and configuring your router settings will ensure you achieve the best possible performance, with minimal latency and maximum video quality.

[thegadgetgurus]

PartnerStack: Empowering Partnerships for Growth

If you're diving into the world of partnerships and affiliate marketing, you've likely come across PartnerStack—a platform that’s revolutionizing how businesses and partners collaborate. Whether you’re a growing business looking to scale through partnerships or a marketer eager to expand your income streams, PartnerStack is here to make it happen.

Let’s break it down and see why PartnerStack is a game-changer for businesses and affiliates alike.

What is PartnerStack?

Simply put, PartnerStack is a partner management platform that helps businesses build, manage, and scale their affiliate, reseller, and referral programs. It's designed to streamline the way partnerships work, ensuring both companies and their partners succeed together.

Why Choose PartnerStack?

1. All-in-One Platform

With PartnerStack, you get everything you need in one place: program management, tracking, payments, and even built-in tools to recruit partners.

2. Automation at Its Best

No more manual tracking or tedious spreadsheets. PartnerStack automates onboarding, tracking, and payouts, so you can focus on growing your network.

3. Partner-Centric Approach

This platform doesn’t just benefit businesses—it also creates a seamless experience for affiliates and resellers, making it easier for them to promote and earn.

How Does PartnerStack Work?

For Businesses:

Launch Programs: Quickly create affiliate, referral, or reseller programs.

Recruit Partners: Attract top-notch marketers and resellers to join your team.

Track Performance: Use real-time analytics to monitor success.

Automate Payments: Pay your partners on time without lifting a finger.

For Affiliates and Partners:

Discover Opportunities: Browse and join programs that align with your niche.

Get Paid Easily: Enjoy automated payouts and detailed earnings reports.

Access Resources: Use tools like banners and links to promote products effectively.

Who is PartnerStack For?

For Businesses:

Whether you're a SaaS company, an eCommerce brand, or a service provider, PartnerStack helps you expand your reach by leveraging the power of partnerships.

For Affiliates:

From bloggers to influencers, anyone can join PartnerStack’s network to promote products and earn commissions.

Benefits of Using PartnerStack

Ease of Use: No technical expertise? No problem. PartnerStack’s interface is intuitive and easy to navigate.

Scalability: Whether you’re just starting or managing hundreds of partners, PartnerStack grows with you.

Community: Join a network of like-minded businesses and affiliates, all striving for success.

Get Started with PartnerStack

PartnerStack simplifies partnerships, making it easy for businesses and affiliates to achieve their goals. If you’re ready to take your affiliate marketing or partner program to the next level, why wait?

For Businesses:

Ready to grow your business with PartnerStack? Launch Your Partner Program Today! 👈

For Affiliates:

Want to start earning with PartnerStack? Find Partner Opportunities Now! ✔️

With PartnerStack, partnerships aren’t just easier—they’re smarter. It’s time to unlock your growth potential.