[uptownfunk]

Thanks for your work and also for your comments of AF3 and Chai-1. It sounds like you are implying there are potentially gross and subtle types of data set leakages taking place between the train and test which are resulting in what seem to be inflated performance metrics? These are pretty serious issues if so. Also I would agree with previous authors that marginal Improvement over sota is proof more that they have recreated something than really made significant new progress. But this has been an issue with LLMs for sometime now. But it sounds like they have some bright engineers from good brand name companies who are coming together with some VC backing of the team to try and do something in this space. I do appreciate that the weights are open. I would like to learn more about their future direction and their training methods