Unveiling PAGI Gen v1
In the fast-evolving world of generative models, there have been some exciting breakthroughs, especially in models based on Transformers and Diffusion. These models have shown exceptional performance in tasks related to generating images. However, when it comes to video generation, they have encountered a roadblock that we’ve observed mostly in Large Language Models (LLMs), known as the hallucination issue. As of the current year, 2023, in the context of video generation tasks utilizing the img2img framework, the Vanilla Autoencoder architecture remains the preferred choice. Despite the inherent challenge associated with interpolating the self-reconstruction vectors in contrast to the more intricate highly interpolable Variational Autoencoder vectors, it is noteworthy that once this hurdle is overcome, these vectors exhibit a high degree …
