The video from the factored cognition lab meeting is up:
Description:
Ought cofounders Andreas and Jungwon describe the need for process-based machine learning systems. They explain Ought's recent work decomposing questions to evaluate the strength of findings in randomized controlled trials. They walk through ICE, a beta tool used to chain language model calls together. Lastly, they walk through concrete research directions and how others can contribute.
Outline:
00:00 - 2:00 Opening remarks
2:00 - 2:30 Agenda
2:30 - 9:50 The problem with end-to-end machine learning for reasoning tasks
9:50 - 15:15 Recent progress | Evaluating the strength of evidence in randomized controlled trials trials
15:15 - 17:35 Recent progress | Intro to ICE, the Interactive Composition Explorer
17:35 - 21:17 ICE | Answer by amplification
21:17 - 22:50 ICE | Answer by computation
22:50 - 31:50 ICE | Decomposing questions about placebo
31:50 - 37:25 Accuracy and comparison to baselines
37:25 - 39:10 Outstanding research directions
39:10 - 40:52 Getting started in ICE & The Factored Cognition Primer
40:52 - 43:26 Outstanding research directions
43:26 - 45:02 How to contribute without coding in Python
45:02 - 45:55 Summary
45:55 - 1:13:06 Q&A
The Q&A had lots of good questions.
Ought will host a factored cognition “Lab Meeting” on Friday September 16 from 9:30AM - 10:30AM PT.
We'll share the progress we've made using language models to decompose reasoning tasks into subtasks that are easier to perform and evaluate. This is part of our work on supervising process, not outcomes. It’s easier for us to show you than to tell you about it in a post (though written updates will hopefully follow).
Then, we'll cover outstanding research directions we see and plan to work on, many almost shovel-ready. If the alignment community can parallelize this work across different alignment research teams, we can make progress faster. We'd love to coordinate with other alignment researchers thinking about task decomposition, process supervision, factored cognition, and IDA-like approaches (where efficient to do so). We want to save you time and mistakes if we can!
What is the agenda?
There will be more to discuss than we can fit into an hour. We’ll get to what we can and consider making this a regular meeting if there’s appetite (likely with more sharing from other researchers)!
Who should attend?
You should attend if:
How can I attend?
You can register for the Lab Meeting here. Email jungwon@ought.org if you have any questions!
The meeting will be recorded & shared.