AI models are increasingly able to generate very high-quality text, images, audio, and video content.
promised much, but there has been something holding it back from being used successfully by billions of people: a frustrating struggle for humans and machines to understand one another in natural language.
These new models have delivered significant improvements to applications using natural language like language translation, summarization, information retrieval, and, most important, text generation. In the past, each required bespoke architectures. Now transformers are delivering state-of-the-art results across the board.
“Parameter count” is generally accepted as a rough proxy for a model’s capabilities. So far, we’ve seen models perform better on a wide range of tasks as the parameter count scales up. Models have been growing by almost an order of magnitude every year for the past five years, so it’s no surprise that the results have been impressive. However, these very large models are expensive to serve in production.
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