---
title: "Where Historians Fall Short for Physical AI"
url: https://daily.dev/posts/where-historians-fall-short-for-physical-ai-ahlwcig79
source_url: https://www.influxdata.com/blog/where-historians-fall-short
type: article
source: "InfluxData"
published: 2026-08-04T07:11:16.812Z
updated: 2026-08-04T07:11:37.287Z
tags: ["machine-learning", "iot", "edge-computing", "influxdb"]
reading_time: 7
upvotes: 0
comments: 0
language: en
---

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# Where Historians Fall Short for Physical AI

**[InfluxData](https://daily.dev/sources/influxdb)** · 7 min read · 0 upvotes · 0 comments

## Summary

Traditional data historians were designed for recording operational history, not for the real-time and high-resolution data demands of Physical AI in industrial settings. Four key gaps are identified: limited real-time data access, lossy compression that strips model-relevant signals, IT/OT fragmentation, and siloed site-by-site architectures. InfluxDB 3 is presented as a complementary layer that sits alongside existing historians, enabling low-latency edge inference, cross-site data consolidation, and multimodal training datasets by connecting telemetry with enterprise context from ERP, MES, and CMMS systems.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.influxdata.com/blog/where-historians-fall-short>

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---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#iot](https://daily.dev/tags/iot), [#edge-computing](https://daily.dev/tags/edge-computing), [#influxdb](https://daily.dev/tags/influxdb)

[View this post on daily.dev](https://daily.dev/posts/where-historians-fall-short-for-physical-ai-ahlwcig79)