Rule-based in comparison with corpus-based Corpus-based AI (the “Tanks” type; cf. introductory AI post) successfully overcame its weaknesses (cf. preceding post). This was the result of a combination of “brute force” (improved hardware) and an ideal window of opportunity, i.e. when during the super-hot phase of internet expansion, companies such as Google, Amazon, Facebook and many others were able to collect large volumes of data and feed their data corpora with them – and a sufficiently big data corpus is the linchpin of corpus-based AI. Brute force was not enough for rule-based AI, however, nor was there any point in

Two AI variants: rule-based and corpus-based In the preceding post, I mentioned the two fundamental approaches to attempting to imbue computers with intelligence, namely the rule-based approach and the corpus-based approach. In a rule-based system, the intelligence is situated in a rule pool that is deliberately designed by people. In the corpus-based method, the knowledge is contained in the corpus, i.e. in a data collection which is analysed by a sophisticated program. The performance of both methods has been massively boosted since the 1990s. The most impressive boost has been achieved with the corpus-based method, which is now regarded as