This is a linkpost for https://docs.google.com/document/d/1Vva6AW_udvfavtldWuGbqf8NbbzsgEH8mESEX6NlOvM
Overview
- The linked document contains a collection of AI Forecasting research ideas, prepared by some Epoch employees in a personal capacity
- We think that these are interesting and valuable projects that research interns or students could look into, though they may vary in difficulty (depending on your background/experience)
- This is the result of a quick brainstorming and curation, rather than a thorough deliberative process. We encourage a critical outlook when reading them
- You may also be interested in these other forecasting research ideas suggested by Jaime Sevilla
- You can use Epoch’s database as a resource for finding notable machine learning papers with parameter, compute, and dataset sizes. On Epoch website you can also find our past research, a tool for visualising the dataset, and some other tools like this compute calculator.
- Please feel free to contact us for clarification about these questions!
> Re: "Extrapolating GPT-N performance" and "Revisiting ‘Is AI Progress Impossible To Predict?’" sections of google doc
Read Section 5.6 titled "The Limit of the Predictability of Scaling Behavior" of "Broken Neural Scaling Laws" paper:
https://arxiv.org/abs/2210.14891v4