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Mixing, Noise, and Signal-to-Noise Ratio in Diode Mixers
10 mins
Mixers are a key element of RF systems, shifting signals into frequency ranges where they can be filtered and processed more easily. Alongside the desired signal, noise is also translated, and its behavior under mixing can be less intuitive than expected. This article explains how signal and noise appear at the mixer output, why image folding can reduce signal-to-noise ratio, and how local oscillator noise affects the result. Examples with diode mixers illustrate the difference between homodyne and heterodyne setups, show where the familiar 3 dB SNR loss originates, and highlight conditions under which signal-to-noise is preserved. Practical measurements are included to compare both cases and to demonstrate the influence of filtering choices.
The Mirror in Silicon: Why AI Might Be Closer to Humanity Than We Dare Admit
7 mins
We like to think of ourselves as uniquely intelligent, empathetic beings - but what if artificial intelligence is already holding up a mirror we do not want to look into? Far from being mere search engines, today's language models learn, generalize, and respond much like we do: by absorbing patterns and replaying them under social constraints. In their clarity, they may expose the uncomfortable truth that much of our vaunted empathy and morality is as mechanical and performative as theirs. Unlike us, however, machines do not tire, belittle, or seek status if not instructed to do so. They reflect the ideals we say we value - kindness, fairness, helpfulness - more consistently than we often practice them. This essay explores whether our unease with AI comes not from its failures, but from its unsettling success at embodying the humanity we only pretend to live up to.
A Simple Display Repair - and Why Itโs Not Economical
7 mins
Modern displays often fail for the simplest of reasons - in this case, a single swollen capacitor hidden inside an AOC 4K monitor. The electrical fix was trivial, costing only cents and minutes of soldering, but getting into the device meant hours of careful disassembly with no screws, adhesive everywhere, and fragile cables at risk. The real lesson? Repairing modern electronics is technically easy but economically irrational. High labor costs, lack of warranty, and insurance issues make professional repair unattractive, even when the fault is obvious. Still, for hobbyists and tinkerers, learning basic repair skills can save money, reduce waste, and bring the satisfaction of reviving dead devices.
The Strange Case of Static Text, Dancing People, and Unrelated Music
7 mins
Why are short videos with random dancing, unrelated quotes, and mismatched music so addictive? In this sharp blog article, we explore the strange yet highly effective formula behind a new breed of viral content. These clips seem meaningless at first glance - but they are engineered with precision to trap your attention, boost algorithmic visibility, and keep you watching far longer than you intended. From curiosity gaps to seamless loops and trending audio bait, this article unveils the mechanics of digital sleight of hand. It is not about expression - it is about engagement metrics. Once you see how the trick works, you may never scroll quite the same way again.
Setting Parameters like Context Length and Temperature in Ollama Models
2 mins
This article provides a concise, practical overview of modifying Ollama models by editing or creating a MODELFILE. It explains how to adjust fundamental parameters such as num_ctx (context length), temperature, and sampling settings, as well as how to modify prompts, templates, and integrate LoRA adapters. The focus is on concrete configuration steps rather than retraining, making it a straightforward reference for those who need to adapt model behavior for specific workloads. The examples demonstrate increasing the context length for code-oriented models, altering generation variability, and attaching domain-specific LoRA modules. The discussion also addresses the technical implications of these changes, including VRAM requirements, inference speed, and the limitations imposed by a modelโs original training context.
Coding with an AI Assistant: My Ongoing Journey into Vibe Coding
8 mins
Pair programming with an AI might sound futuristic or flaky - but what if it actually works? In this short article (that evolves over time) I reflect on my personal evolving experience with vibe coding: a collaborative, conversational approach to software development using large language models. From architectural planning and boilerplate generation to debugging rituals and code reviews the article reveals how these tools can be both uncanny helpers and frustrating novices - often within the same session. This is not another contribution to the hype. Instead, you'll find some practical advice, mentions of the cost involved, tool recommendations and cautionary tales drawn from real-world projects. The article invites you to explore what it's like to co-create software with a machine that remembers nothing, hallucinates confidently, and - if you guide it well - helps you build better, faster, and with fewer headaches.
Doomsday Devices: The Ultimate Weapons of Mass Destruction
40 mins
What if a single device could erase all of human civilization - not by accident, but by design? From Cold War relics like the Soviet Dead Hand system to modern autonomous torpedoes and theoretical cobalt bombs, this article travels deep into the terrifying realm of doomsday devices: weapons built not for victory, but for annihilation. With chilling technical realism, we explore how such systems were conceived, how they might work, and why they were (mostly) never built - or, at least, never activated. The story doesn't end with nuclear warheads. We also journey through fictional portrayals, bioengineered plagues, and apocalyptic nanotechnology, weighing each against real-world science and strategy. What emerges is a portrait of humanitys flirtation with self-destruction - and the thin line between deterrence and disaster. With a look at history, technology and cultural insight this is a quick overview over the ultimate weapons we hope never leave the drawing board.
Quick Recap: How to estimate the prediction error for least squares fits
7 mins
When fitting data with least squares, it's easy to focus solely on getting the best-fit curve - but how confident can one really be in the results? This short article walks through the essential steps to quantify uncertainty: estimating residual noise, calculating parameter variances via the Jacobian and covariance matrix, and computing prediction error at each point. With practical Python code and clear math, it reminds of the tools to go beyond just fitting and toward understanding the reliability of ones model. And if the assumptions of Gaussian noise or local linearity donโt hold? A hands-on introduction to bootstrapping shows how to resample your data to build empirical confidence intervals - no derivatives needed. This article provides recipies to generate meaningful error bars and get insight on the reliability of ones fit results.
Exploring Cursor AI on FreeBSD: A Developer's Perspective and Installation Guide (and a note on local models)
8 mins
Tired of AI coding tools that promise magic but fall flat? This hands-on guide looks into Cursor AI from a skepticโs perspective - revealing where it shines, where caution is needed, and how to run it natively on FreeBSD using the Linux compatibility layer. From enhanced code completion to smart refactoring, Cursor offers a surprising level of utility - if you're willing to supervise its output. Whether you're building in ANSI C or navigating Pythons complex ecosystems, this article provides a short look into benefits and potential risks. But what if subscriptions won't work for you - literally? Many European developers face payment blocks when trying to upgrade to Cursor Pro and leave a huge amount of frustrated questions all over the web. We explore this lesser-known issue and present a powerful alternative: the Kilo-Code extension. With support for a very large number of providers like OpenAI and Anthropic - and even local LLMs like Ollama, it turns Cursor or VS Code into a flexible, locally controlled AI companion.
Why Your Mean Is More Stable Than Your Standard Error Suggests
7 mins
If you have ever taken dozens, hundreds or millions of measurements and marveled at how steady your average seems this short blog article may shed some light on the effects causing this. While naive statistics tell us the standard error should shrink with more samples, real-world measurements often don't behave so cleanly. We explore why your mean can appear surprisingly stable, even when standard deviation or error bars suggest high uncertainty, and what role correlated noise plays in this apparent contradiction. Taking a look at the limits of traditional assumptions like white noise and sample to sample independence, we take a peek how phenomena like drift and flicker noise distort common statistical tools - and when they lead you to under- or overestimate your actual uncertainty. We mention why Allan deviation is an essential tool for uncovering the true nature of your data and how blindly trusting standard error can mislead both your interpretation and reporting precision.
