Get Ready for Transformational Transformer Networks – EE Times

Got some grainy footage to enhance, or a miracle drug you need to discover? No matter the task, the answer is increasingly likely to be AI in the form of a transformer network.

Transformers, as those familiar with the networks like to refer to them in shorthand, were invented at Google Brain in 2017 and are widely used in natural language processing (NLP). Now, though, they are spreading to almost all other AI applications, from computer vision to biological sciences.

Transformers are extremely good at finding relationships in unstructured, unlabeled data. They are also good at generating new data. But to generate data effectively, transformer algorithms often must grow to extreme proportions. Training language model GPT3, with its 175 billion parameters, is estimated to have cost between $11 million and $28 million. That’s to train one network, one time. And transformer size is not showing any sign of plateauing.

Transformer networks broaden their view

What makes transformers so…

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source: https://news.oneseocompany.com/2022/10/06/get-ready-for-transformational-transformer-networks-ee-times_2022100632407.html

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