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CrashCourse AI episode 10

Posted on: October 22, 2019

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This week’s episode focused on symbolic artificial intelligence (AI). This is where AI represents real-world objects as symbols.

What does symbolic AI look like? Modern video games depend on such AI.

Neural networks rely on huge amounts of data, best guesses, and probabilities. Symbolic AI is the opposite in that it does not require massive data, training, or guesswork. It uses logic and symbols instead.

A symbol can be any letter, number, word, or object. Symbols are linked by relations. If symbols are nouns, then relations are verbs and adjectives.

Symbols as nouns and relations as verbs and adjectives.

A voice assistant like Siri might take a question we ask and turn a noun into a symbol and a verb into a relation.

That is probably as much as I can explain as a lay learner because the next part involved the mathematics of truth tables. The host used these to introduce the logic of AND, OR, NOT, and IF/THEN.

For me it was a cognitive leap to see how such logic statements helped AI make inferences and then to become expert systems.

But I took this important message away: A neural network remains a black box, but symbolic AI can show you the reasons for its decisions.

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