Description: The widespread Amazon Web Services (AWS) outage on October 20, 2025 reportedly caused AI-enabled Eight Sleep "Pod" smart beds to overheat or become unresponsive. The devices reportedly rely on a cloud-hosted deep learning algorithm to regulate temperature and track sleep data. When AWS went down, users reportedly lost control of their beds, which remained stuck at prior settings. Some reported overheating and incline malfunctions. Eight Sleep confirmed it is developing an offline "outage mode."
Entities
View all entitiesAlleged: Eight Sleep , Eight Sleep Pod , Eight Sleep Autopilot , Eight Sleep Deep Learning Sleep Algorithm , Eight Sleep Cloud Control System , Amazon Web Services (AWS) , AWS US-East-1 Region , Eight Sleep Mobile App and AWS cloud infrastructure developed and deployed an AI system, which harmed Eight Sleep and Eight Sleep customers.
Alleged implicated AI systems: Eight Sleep Pod , Eight Sleep Autopilot , Eight Sleep Deep Learning Sleep Algorithm , Eight Sleep Cloud Control System , Amazon Web Services (AWS) , AWS US-East-1 Region , Eight Sleep Mobile App and AWS cloud infrastructure
Incident Stats
Incident ID
1243
Report Count
3
Incident Date
2025-10-20
Editors
Daniel Atherton
Incident Reports
Reports Timeline
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Matteo Franceschetti post-incident response
The AWS outage has impacted some of our users since last night, disrupting their sleep. That is not the experience we want to provide and I want to apologize for it.
We are taking two main actions:
- We are restoring all the features as AWS …
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A major Amazon Web Services (AWS) outage on October 20 had the unexpected side effect of causing chaos in bedrooms across the US, as owners of Eight Sleep's $2,000+ 'Pod' mattress covers found their smart beds had no offline mode and were s…
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Owners of Eight Sleep smart beds got anything but a good night's sleep Monday, as the beds began heating up uncontrollably while also getting frozen in position due to Amazon's worldwide server outage.
Eight Sleep CEO Matteo Franceschetti …
Variants
A "variant" is an AI incident similar to a known case—it has the same causes, harms, and AI system. Instead of listing it separately, we group it under the first reported incident. Unlike other incidents, variants do not need to have been reported outside the AIID. Learn more from the research paper.
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