The April 2021 archive looked at the use of algorithms in investment tools, beyond public interest in buying shares in AI companies. It described systems that process financial statements, market data and other signals to support decisions.
The original discussion highlighted the speed with which software can organise large datasets. It also described the growth of consumer-facing applications that make automated portfolio tools more accessible.
Speed and access to data do not establish investment quality. Models can inherit problems from their inputs, assumptions and evaluation methods; removing a person from one step does not make the whole process unbiased. This archival adaptation retains the technology overview and omits the original article’s assurances of superior results. It describes a historical application of AI, rather than recommending a financial product or strategy.
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 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.
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.
Tell us about your project — we'll tell you honestly whether we can help.