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.
Narrow AI is designed around a bounded task. The archive used voice assistants and game-playing systems as examples: success in one setting does not establish that a system can handle every other intellectual task. General intelligence describes the broader ambition of transferring capabilities across domains.
Superintelligence describes a hypothetical capability beyond human performance across a broad range of tasks. In the original article, AGI and superintelligence were research concepts, not products the reader could deploy. For a business project, the useful starting point is the actual task, available data and evaluation criteria. A compelling demonstration on one benchmark is not evidence of reliability in a different workflow.
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.
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