If the main contribution here is the quality of the model and its interesting and powerful representation of text, I hope OpenAI does something distruptively different and releases the weights and trained model.
The accidental sentiment neuron is a function of the model, distribution of the input dataset, and the optimizer finding nice saddle points. Insight into these foundational components would make these results amazing. It sounded like training on other datasets doesn't have the same sentiment properties, which provides a lever to explore these concepts more.
At the moment it feels like the Google cat neuron. It attracted a lot of intrigue but the individual contribution from that in terms of research was more on the infrastructure side, and few people seem to refer back to that publication at this point.
That said OpenAIs mission in itself doesn't necessarily require novel research. For example, the gym is fostering a competitive atmosphere for the community to work on RL which hopefully leads to more progress in the field.
Training a model for a month is difficult and if it has captured interesting phenomena it seems in the interest of the community to release the weights and model. It would be hard for the community to reproduce this without a month of compute and 83M Amazon reviews.
The accidental sentiment neuron is a function of the model, distribution of the input dataset, and the optimizer finding nice saddle points. Insight into these foundational components would make these results amazing. It sounded like training on other datasets doesn't have the same sentiment properties, which provides a lever to explore these concepts more.
At the moment it feels like the Google cat neuron. It attracted a lot of intrigue but the individual contribution from that in terms of research was more on the infrastructure side, and few people seem to refer back to that publication at this point.
That said OpenAIs mission in itself doesn't necessarily require novel research. For example, the gym is fostering a competitive atmosphere for the community to work on RL which hopefully leads to more progress in the field.
Training a model for a month is difficult and if it has captured interesting phenomena it seems in the interest of the community to release the weights and model. It would be hard for the community to reproduce this without a month of compute and 83M Amazon reviews.