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The emergence of generative artificial intelligence has ignited a deep philosophical exploration into the nature of consciousness, creativity, and authorship. As we bear witness to new advances in the field, it’s increasingly apparent that these synthetic agents possess a remarkable capacity to create, iterate, and challenge our traditional notions of intelligence. But what does it really mean for an AI system to be “generative,” with newfound blurred boundaries of creative expression between humans and machines?

For those who feel as if “generative artificial intelligence” — a type of AI that can cook up new and original data or content similar to what it's been trained on — cascaded into existence like an overnight sensation, while indeed the new capabilities have surprised many, the underlying technology has been in the making for some time.

But understanding true capacity can be as indistinct as some of the generative content these models produce. To that end, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) convened in discussions around the capabilities and limitations of generative AI, as well as its potential impacts on society and industries, with regard to language, images, and code.

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