Eevo – Consequential Decision Model
A potentially AI-related product surfaced from a public Show HN launch post.
Launch summary
Hi HN, I'm Juho from Upright. I think we may have stumbled upon an interesting approach to AI alignment. The idea is as follows: 1. train a decision model to be really good at comparative sizing of consequences, expected value problems, and modelling overlap between different consequences 2. create a harness around that model that accepts a decision context, list of options, and identified consequences, then runs pairwise comparisons and overlap modelling for the consequences using the decision model in (1), and finally solves implied relative consequences "sizes" and finally EV (for different stakeholders) 3. Make AI agents running on general purpose LLMs use (2) to make better decisions. So the agent provides the context, options, and identifies the consequences, Eevo model just sizes them, models their overlap, and computes EV. In practice this seems to improve agent judgement a lot (in addition to adding lots of practical observability) It seems the (well-motivated) emphasis on ins
Source: Hacker News Show HN. Public listings are automatically detected and can be corrected or removed by contacting TechRankr.