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Meet Transformers: The Google Breakthrough that Rewrote AI's Roadmap
You may not know that it was a 2017 Google research paper that kickstarted modern generative AI by introducing the Transformer, a groundbreaking model that reshaped language processing.
Insiders talk about informal brainstorming sessions, where researchers from different teams compared notes on how attention mechanisms were helping solve translation tasks or improve alignment between source and target sentences. Experiments found that as you increase the number of parameters in a Transformer and the size of its training dataset, performance continues to improve in a predictable manner... this linearity became an invitation for an arms race of sorts: bigger models, more data, more GPUs. Training such models consumes enormous computing power ( Nvidia is too happy about that one) and electricity – transforming AI research into an endeavor that is much closer today to industrial engineering than the academic tinkering it once was.
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