The Quantified Uncertainty Research Institute Blog
webQURI's blog hub covers forecasting, uncertainty quantification, and epistemic tooling relevant to AI safety, including LLM evaluation methods, AI-driven epistemic risks like belief lock-in, and tools like Squiggle for probabilistic reasoning.
Metadata
Importance: 52/100homepage
Summary
The QURI blog is the primary publication outlet for the Quantified Uncertainty Research Institute, a nonprofit focused on forecasting and epistemics for long-term decision-making. It publishes research on LLM evaluation, uncertainty quantification tools (Squiggle), automated research workflows, and AI-driven epistemic risks. The blog bridges technical AI safety concerns with practical epistemics tooling.
Key Points
- •Develops and maintains Squiggle, a probabilistic programming language for uncertainty quantification in forecasting and decision-making.
- •Explores LLM evaluation methods including 'opinion fuzzing' to systematically sample variance across models, prompts, and perspectives.
- •Investigates AI-driven epistemic risks such as belief lock-in, where AI could entrench false beliefs at scale.
- •Builds practical tools like RoastMyPost for automated document quality evaluation using LLMs.
- •Collaborates on technical AI safety reviews and automated research wiki production workflows.
Cited by 5 pages
| Page | Type | Quality |
|---|---|---|
| QURI (Quantified Uncertainty Research Institute) | Organization | 48.0 |
| Survival and Flourishing Fund (SFF) | Organization | 59.0 |
| Longterm Wiki | Project | 63.0 |
| Metaforecast | Project | 35.0 |
| SquiggleAI | Project | 37.0 |
2 FactBase facts citing this source
| Entity | Property | Value | As Of |
|---|---|---|---|
| QURI (Quantified Uncertainty Research Institute) | Founded Date | 2019 | — |
| Guesstimate | Founded Date | 2016 | — |
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Quantified Uncertainty Research Institute
QURI is a nonprofit research organization researching forecasting and epistemics to improve the long-term future of humanity.
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Ozzie Gooen
29 Jan 2026
Paid
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Upcoming Workshops: Automated Research Wikis with Claude Code
I’ve been using Claude Code to automate wiki and book production. Lately, it’s become surprisingly straightforward to generate useful, many-page research documents, especially when paired with online document libraries.
If you’re in the Bay Area, I’m running two workshops soon:
* MoxSF (next Thursday, San Francisco)
Ozzie Gooen
20 Dec 2025
Paid
Members
Opinion Fuzzing: A Proposal for Reducing & Exploring Variance in LLM Judgments Via Sampling
Summary
LLM outputs vary substantially across models, prompts, and simulated perspectives. I propose "opinion fuzzing" for systematically sampling across these dimensions to quantify and understand this variance. The concept is simple, but making it practically usable will require thoughtful tooling. In this piece I discuss what opinion fuzzing
Ozzie Gooen
17 Dec 2025
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Members
New Collaboration: Shallow Review of Technical AI Safety, 2025
We recently collaborated with the Arb Research team on their latest technical AI safety review. This document provides a strong overview of the space, and we built a website to make it significantly more manageable.
The interactive website: shallowreview.ai
The review examines major research directions in technical AI safety
Ozzie Gooen
10 Dec 2025
Paid
Members
Announcing RoastMyPost
Today we're releasing RoastMyPost, a new application for blog post evaluation using LLMs.
Try it Here
TLDR
* RoastMyPost is a new QURI application that uses LLMs and code to evaluate blog posts and research documents.
* It uses a variety of LLM evaluators. Most are narrow checks: Fact Check,
Ozzie Gooen
01 Nov 2025
Paid
Members
Beyond Spell Check: 15 Automatable Writing Quality Checks
I've been developing RoastMyPost (currently in beta) and wrestling with how to systematically analyze documents. The space of possible document checks is vast, easily thousands of potential analyses.
Building on familiar concepts like "spell check" and "fact check," I've made a taxonomy
Ozzie Gooen
31 Oct 2025
Paid
Members
Updated LLM Models for SquiggleAI
We've upgraded SquiggleAI to use Claude Sonnet 4.5, Claude Haiku 4.5, and Grok Code Fast 1. This is a significant upgrade over the previous Claude Sonnet 3.
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