I do find myself reading papers often for my work, and I share the once I find interesting or feel might have impact in future of my chosen domain. This is no advertisement, I don't know the authors or anyone related to the paper.
My father was a PhD psychologist and family therapist. He was on the witness stand during a custody case explaining a theory of personality when the cross-examining lawyer said scornfully "I'll bet you got that out of some book." To which my dad replied: "Why yes, in fact. In my profession, in order to learn things, we often read books."
TLDR;
1. InternLM2 is an open-source Large Language Model that has shown improvements over previous models, particularly in long-context modeling.
2. The model uses a unique approach, combining traditional training with Supervised Fine-Tuning and Conditional Online Reinforcement Learning from Human Feedback.
3. It offers a variety of model sizes and training stages to the community, demonstrating significant advancements in AI research and application.
