I remember the first time I had to migrate an authentication system for a business unit: months of planning, frantic late-night debugging, and a growing pile of post-it notes stuck to the monitor. Passwords were everywhere—hard-coded in scripts, reused across subsystems, and guarded by brittle rules that made users invent predictable variations. Moving to passwordless felt like a security and...
I’ve been living with a privacy-first smart home setup for a couple of years now, and every week I find one more way...
I test a lot of tiny devices—fitness bands, smart rings, and the occasional prototype smartwatch—and one question...
When I started exploring padel as a complementary sport to my usual tech reviews and gadget testing, I quickly realised...
Keeping a large language model (LLM) healthy in production feels a bit like tending a high-maintenance houseplant:...
I’ve spent the last few weeks alternating between my living room, a noisy coffee shop, and a shared office desk,...
Fine-tuning GPT-style models on proprietary customer data is one of those tasks that promises huge value—better, more...
When I started exploring padel as a complementary sport to my usual tech reviews and gadget testing, I quickly realised that choosing the right padel racket in the UK is as much about fit and feel as it is about raw specs. If you're searching for padel racket uk, this article is meant to take you...
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Keeping a large language model (LLM) healthy in production feels a bit like tending a high-maintenance houseplant: ignore it for too long and it wilts, water it too much and you drown it. In the last few years I’ve watched teams move from “deploy and forget” to continuous monitoring and...
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I’ve spent the last few weeks alternating between my living room, a noisy coffee shop, and a shared office desk, testing several budget AI noise-cancelling earbuds against my long-time reference: the Sony WH-1000XM4. The question I wanted to answer was simple but practical: can cheap AI earbuds...
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Fine-tuning GPT-style models on proprietary customer data is one of those tasks that promises huge value—better, more contextual outputs; fewer hallucinations for domain-specific prompts; and a competitive edge in automation and support. It’s also a task that can easily turn into a data leak or...
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I used to dread the monthly cloud bill email. A spike in egress charges would arrive like clockwork after a product launch, blamed on "unexpected traffic" or "downloads from Region X." Over the years I've helped several engineering teams rework their multicloud topology so that customer-facing apps...
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Buying an enterprise AI observability tool is one of those decisions that looks simple on a feature sheet and quickly becomes painful in production. I’ve sat in more vendor demos than I’d like to admit, built my own ad‑hoc monitoring stacks, and seen observability gaps turn into customer...
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I’ve spent the past year benchmarking vector databases as part of larger semantic search projects, and one thing became quickly clear: choosing a vector database is less about raw recall numbers and more about trade-offs between usability, latency, and price. In this article I’ll walk you...
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I’ve spent the last few years building and evaluating machine learning systems for real teams, so when customers ask whether they should “retrain” a large language model (LLM) on their proprietary data, my first reaction is: there’s no single yes/no answer. The right approach depends on the...
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I’ve spent years testing gadgets and poking at the settings screens most people never touch. Smart home gear can make life easier, but it also opens a lot of new privacy and security questions. If you want a smart home that respects your data, the hub—the piece that ties sensors, speakers, and...
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I’ve been watching WebAssembly (Wasm) evolve from an intriguing runtime curiosity into a practical tool I reach for when building browser-based apps. Over the last few years I’ve ported libraries, benchmarked compute-heavy tasks, and explored the developer experience. In this article I want to...
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