Websauna Co / AI
I’ve been testing compressed vector embeddings for search pipelines for a while now, because the promise is irresistible: save storage and speed up retrieval while keeping relevance high. In practice it’s a balancing act. Below I share...
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I spent the last few weeks pushing a Pixel Tablet through a set of pro-photography chores: rapid culling, raw adjustments, masked edits, and a handful of “magic” fixes that promise to save time. My aim was simple: figure out whether the Pixel...
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I wanted a private, offline note-taking assistant that I could carry around on a cheap, low-power device. The Raspberry Pi 5—when paired with the right model and software—lets you do exactly that: run a local language model that summarizes,...
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I test a lot of tiny devices—fitness bands, smart rings, and the occasional prototype smartwatch—and one question always comes up: how do you meaningfully evaluate on-device AI when battery life is the limiting factor? It’s tempting to point...
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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...
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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,...
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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,...
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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...
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I test AI products for a living, and one thing that never stops surprising me is how often "explainability" is treated as either a checkbox or a vague marketing line. Reviewers will praise a model for being "transparent" or criticize it for being a...
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I’ve spent years watching teams drown in time-series telemetry: terabytes of sensor data streaming into lakes, dashboards overflowing with metrics, and engineers still caught off guard when a pump or motor fails. The irony is that more data rarely...
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