Constant evolution across the generative AI space
The generative AI space is characterized by relentless innovation and rapid advancement across model architectures, applications, and ethical considerations. As soon as one method or architecture shows promising results, hundreds of competing and complementary approaches emerge to push capabilities even further. Transformers gave way to BERT, which was outpaced by GPT-3, soon rivaled by image synthesizers like DALL-E, and now GPT-4 and Gemini are competing for the top spot. All of which happened in the past few years.
Meanwhile, we are seeing new modalities like audio, video, and 3D scene generation gaining vast popularity and usability. On the business front, new services are launched monthly, targeting media and entertainment, finance, healthcare, art, code, music, and more. However, considerations around ethics, access control, and legalities are key in order to maintain public trust.
One breakthrough enables several more, and each unlocks added potential. This self-fueling cycle arises from the very nature of AI – its ability to recursively assist innovation. The only certainty is that the field will look very different within months, not years. Maintaining awareness, responsiveness, and responsibility is critical amid this constant evolution.