The
Allen Institute for AI (AI2) created by Paul Allen, best known as co-founder of Microsoft, has published new research on a type of artificial intelligence that is able to generate basic (though obviously nonsensical) images based on a concept presented to the machine as a caption. The technology hints at an evolution in machine learning that may pave the way for smarter, more capable AI.
The research institute's
newly published study, which was recent highlighted by MIT, builds upon the technology demonstrated by OpenAI with its GPT-3 system. With GPT-3, the machine learning algorithm was trained using vast amounts of text-based data, something that itself builds upon the masking technique introduced by
Google's BERT.
Put simply, BERT's masking technique trains machine learning algorithms by presenting natural language sentences that have a word missing, thus requiring the machine to replace the word. Training the AI in this way teaches it to recognize language patterns and word usage, the result being a machine that can fairly effectively understand natural language and interpret its meaning.
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