We asked three AI systems to generate content using the same prompt. The results illustrate how quickly the technology has advanced.
of training AI, called the Transformers model. This method allows the technology to process large blocks of language quickly and to test the fluency of the outcome.To understand how the model works, consider a simple sentence: “The cat went to the litter box.”
To make sure the AI performs correctly, the transformers model builds in a testing step. It masks a word in the sentence to see if the AI can predict what’s missing. Additionally, companies such as OpenAI have humans rate the quality of the response. For example, if the word “cat” is masked and the computer offers “the dog went to the litter box,” it’s likely to get a thumbs down.
Another new training method, called diffusion, has also improved AI image generators such as Dall-E and Midjourney, allowing nearly anyone to create hyper-realistic photos with simple, even nonsensical, text prompts, such as: “Draw me a picture of a rabbit in outer space.”Researchers feed these AI models billions of images, each paired with a text description, teaching the computer to identify relationships between images and words.
Previous data sets had lower quality content, Riedl said, like addresses or phone numbers, which aren’t helpful for learning natural speech.
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