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....
Ought is an applied machine learning lab. We’re building Elicit, the AI research assistant. Our mission is to automate and scale open-ended reasoning. To get there, we train language models by supervising reasoning processes, not outcomes. This is better for reasoning capabilities in the short run and better for alignment...
We can think about machine learning systems on a spectrum from process-based to outcome-based: * Process-based systems are built on human-understandable task decompositions, with direct supervision of reasoning steps. * Outcome-based systems are built on end-to-end optimization, with supervision of final results. This post explains why Ought is devoted to...