Active learning is the future of generative AI: Here's how to leverage it

During the past six months, we have witnessed some incredible developments in AI. The release of Stable Diffusion forever changed the artworld, and ChatGPT-3 shook up the internet with its ability to write songs, mimic research papers and provide thorough and seemingly intelligent answers to commonly Googled questions. However, most of these generative AI models are foundational models: high-capacity, unsupervised learning systems that train on vast amounts of data and take millions of dollars of processing power to do it. Currently, only well-funded institutions with access to a massive amount of GPU power are capable of building these models. The majority of companies developing the application-layer AI that's driving the widespread adoption of the technology still rely on supervised learning, using large swaths of labeled training data.