observations
observations on Beyond Market Intelligence: a running collection of 2 stories we have gathered and hand-picked because they are worth your time. Every post here touches on observations in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around observations, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
What We Miss About Missing Values
Missing values are a ubiquitous challenge in data science, yet their implications often go unexamined. "What We Miss About Missing Values" explores the hidden assumptions embedded within the data we *do* observe—recognizing that what's absent can be just as informative as what's present. This post delves into the biases introduced by missingness and offers a framework for more thoughtful analysis. For a related perspective on navigating complexity in data systems, see "Why RAG Complexity Should Be Earned."
New Fable5/Opus4.8 harness called "Schema" claims 99% on ARC-3 [R]
Introducing Schema, a new Fable5/Opus4.8 harness achieving impressive results on the ARC-AGI-3 benchmark. Schema attains 99% accuracy with Claude Opus 4.8 and 95.35% with GPT-5.6 Sol—all without modifying model weights. This innovative harness refines the interaction process, optimizing how observations inform models, predictions are tested, and plans are executed. A fixed fallback rule prioritizes Opus 4.8 and Sol, ensuring robust performance across all games, as noted by ARC Prize. Explore the technical details and methodology at [https://schema-harness.github.io/](https