Blog / Machine Learning
Engineering write-ups tagged Machine Learning — practical lessons from real projects, not marketing copy.
Training/serving skew, silent data drift, and unowned retraining pipelines — the ordinary cost of running ML as a real product feature.
The original November 2022 explainer introduced three terms often grouped together under artificial intelligence: narrow AI, general AI and superintelligence. They describe different levels of capability, rather than three interchangeable labels for the same technology.
Our October 2022 industry overview looked at five areas exploring machine learning: healthcare, transport, finance, retail and property valuation. Each used prediction or pattern recognition, but with very different data and consequences for mistakes.
The October 2022 archive explored how computer-aided systems could support clinicians by organising images, records and monitoring data. Its central theme was assistance with information-heavy work, with diagnosis and treatment remaining clinical responsibilities.
This September 2021 archive article examined where AI could fit into everyday enterprise software. Its examples were tied to operational decisions: what to stock, when to service equipment and how to plan work.
The September 2021 manufacturing overview brought together six areas of interest: predictive maintenance, automation, quality inspection, generative design, workplace safety and production costs. The emphasis was on using operational data to improve specific factory processes.
Our June 2021 archive examined three recurring claims about AI: that it would eliminate all jobs, inevitably exceed people at everything, or inevitably take control. The original discussion contrasted these broad predictions with task-specific systems.
The April 2021 article considered how AI-assisted testing might support healthcare app development. Its starting point was the importance of reliable behaviour when an application collects or displays health information.
The March 2021 archive explored how companies used AI around customer experiences. Examples ranged from digital financial tools and leisure-venue ticketing to video discovery and delivery planning.
This March 2021 article surveyed education technology ideas involving AI and machine learning. It considered personalised learning, progress tracking, accessibility and support for decisions about further study or careers.
Published in March 2021, this archive overview described machine learning as one response to the operational changes of the pandemic. It focused on healthcare, finance, media, retail and manufacturing.
In March 2021, researchers at UC San Diego reported a device designed to perform a neural-network activation function directly in hardware. The work explored a way to reduce the circuitry and energy involved in that part of a network.