PulseAugur
EN
LIVE 17:15:32
Русский(RU) Как я оформляю тренировки и питание в Obsidian с помощью LLM и что она теряла по дороге Что теряется, когда LLM превращает свободные записи в таблицы: 360 запро

LLMs convert notes to tables in Obsidian, losing data

This article details a method for organizing training and nutrition data within Obsidian using Large Language Models (LLMs). It explores what information is lost when LLMs convert free-form notes into structured tables, referencing 360 queries across three models. The piece also touches upon prompt injection vulnerabilities and the capabilities of a free Obsidian plugin called Veynrel. AI

IMPACT This exploration of LLM data conversion highlights potential challenges in structured data generation from unstructured text, impacting how users manage personal information.

RANK_REASON The article discusses a specific application of LLMs with a note-taking software, focusing on a plugin and data conversion process.

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLMs convert notes to tables in Obsidian, losing data

How we ranked this

Signal score
6 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
The article discusses a specific application of LLMs with a note-taking software, focusing on a plugin and data conversion process.
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
product, other
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

Full methodology in our editorial standards.

COVERAGE [1]

  1. Mastodon — mastodon.social TIER_1 Русский(RU) · [email protected] ·

    How I organize workouts and nutrition in Obsidian using LLM and what it loses along the way What is lost when LLM turns freeform notes into tables: 360 queries

    Как я оформляю тренировки и питание в Obsidian с помощью LLM и что она теряла по дороге Что теряется, когда LLM превращает свободные записи в таблицы: 360 запросов к трём моделям, пример prompt injection и новые вохможности бесплатного плагина Veynrel для Obsidian. https:// habr.…