Articles & Trends Quo Vadis Generative Learning? Where Are We Headed? Previous years were centered around large language transformers for generating text. While transformers for text and vision remain a focus area for many researchers and AI companies, diffusion models recently stole their spotlight.
Hi Sebastian! Congratulations for your excellent work. It really helps to stay update and learn.
In the 'Educational Nuggets' section, you referred to techniques that can optimize performance during inference. However, the Parallelization technique discusses the splitting of training data that does not pertain to the inference phase. Could you please provide further details regarding this matter?
Hi Sebastian! Congratulations for your excellent work. It really helps to stay update and learn.
In the 'Educational Nuggets' section, you referred to techniques that can optimize performance during inference. However, the Parallelization technique discusses the splitting of training data that does not pertain to the inference phase. Could you please provide further details regarding this matter?