10 Posts
The latest pretrained language models have shown a remarkable ability to learn facts. A new study drills down on issues of scale, showing that such models might learn the approximate weight of a dog or cost of an apple, at least to the right order of magnitude.
The latest pretrained language models have shown a remarkable ability to learn facts. A new study drills down on issues of scale, showing that such models might learn the approximate weight of a dog or cost of an apple, at least to the right order of magnitude.
Language models like Bert, Ernie, and Elmo have achieved spectacular results based on clever pre-training approaches. New research applies some of those Sesame Street lessons into image processing.
Language models like Bert, Ernie, and Elmo have achieved spectacular results based on clever pre-training approaches. New research applies some of those Sesame Street lessons into image processing.
Earlier language models powered by Word2Vec and GloVe embeddings yielded confused chatbots, grammar tools with middle-school reading comprehension, and not-half-bad translations. The latest generation is so good, some people consider it dangerous.
Earlier language models powered by Word2Vec and GloVe embeddings yielded confused chatbots, grammar tools with middle-school reading comprehension, and not-half-bad translations. The latest generation is so good, some people consider it dangerous.
As language models show increasing power, a parallel trend has received less notice: The vogue for naming models after characters in the children’s TV show Sesame Street.
As language models show increasing power, a parallel trend has received less notice: The vogue for naming models after characters in the children’s TV show Sesame Street.
Watson set a high bar for language understanding in 2011, when it famously whipped human competitors in the televised trivia game show Jeopardy! IBM’s special-purpose AI required around $1 billion. Research suggests that today’s best language models can accomplish similar tasks right off the shelf.
Watson set a high bar for language understanding in 2011, when it famously whipped human competitors in the televised trivia game show Jeopardy! IBM’s special-purpose AI required around $1 billion. Research suggests that today’s best language models can accomplish similar tasks right off the shelf.
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