3 ms·

This blog post certainly is pretty flawed on attribution of ideas - it attributes word2vec as the first to introduce word vectors (which is.... very wrong). "W

This blog post certainly is pretty flawed on attribution of ideas - it attributes word2vec as the first to introduce word vectors (which is.... very wrong). "Word2Vec showed that we can use a vector (a list of numbers) to properly represent words in a way that captures semantic or meaning-related relationships (e.g. the ability to tell if words are similar, or opposites, or that a pair of words like “Stockholm” and “Sweden” have the same relationship between them as “Cairo” and “Egypt” have between them) as well as syntactic, or grammar-based, relationships (e.g. the relationship between “had” and “has” is the same as that between “was” and “is”)."

KasianFranks 8y ago
True, we built NLP/NLU vector representations from the ground up to tackle hypothesis generation and hidden relationship detection connected to genes, genomic pathways and therapeutics related to extending human lifespan, DNA repair and LET radiation chromosomal damage repair at Lawrence Berkeley National Lab from 2002 to 2008 https://www.google.com/patents/US7987191 https://www.google.com/patents/US7987191 followed by Tomas Mikolov's/Google's work and preceded by countless others of course.