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Role play with large language models

As dialogue agents become increasingly human-like in their performance, we must develop effective ways to describe their behaviour in high-level terms without falling into the trap of anthropomorphism. Here we foreground the concept of role play. Casting dialogue-agent behaviour in terms of role play allows us to draw on familiar folk psychological terms, without ascribing human characteristics to language models that they in fact lack. Two important cases of dialogue-agent behaviour are addressed this way, namely, (apparent) deception and (apparent) self-awareness. By casting large-language-model-based dialogue-agent behaviour in terms of role play, it is possible to describe dialogue-agent behaviour such as (apparent) deception and (apparent) self-awareness without misleadingly ascribing human characteristics to the models.

All languages are NOT created (tokenized) equal

Social media bots can be detected by their similar human traits, Penn researchers say

Social media bots can be detected by their similar human traits, Penn researchers say
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News - Volunteers develop first machine translation

News Author: Wiida Fourie-Basson Published: 28/04/2021 ​From Khoekhoegowab to Igbo and Sepedi – these are only three of the low-resource languages in Africa that a group of over 400 volunteers from more than 20 African countries are targeting to address the lack of diversity in the field of natural language processing. Natural language processing (NLP) is a branch of artificial intelligence that helps computers understand, interpret and manipulate human language. But while Africa has more than 2000 living languages, most of these have very little data, making it difficult to develop speech and language technologies relevant to the African context. Hence the term low-resource languages.

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