MIT professor uses AI to boost data center efficiency and cut energy waste
Christina Delimitrou, an associate professor at MIT, is applying machine‑learning techniques to make large‑scale data centers run closer to full capacity. She notes that many facilities operate at only about 15 percent utilization, wasting power and increasing reliance on fossil‑fuel electricity. By redesigning cloud‑computing systems, managing shared hardware resources, and creating streamlined…
Key points
- Data centers typically run at about 15% capacity, leading to excess power use
- Delimitrou's group built Seer to anticipate web‑app issues and Ditto to emulate app performance
- Machine‑learning‑based resource management aims to push utilization toward 100% and cut emissions
The lab has produced tools such as Seer, a deep‑learning system that predicts and prevents problems in web applications, and Ditto, which mimics an app’s structure and performance to enable realistic studies. Delimitrou stresses the need for explainable AI so developers can trust the recommendations and avoid opaque decisions. While proprietary hardware in commercial data centers can limit direct applicability, the research offers a pathway to reduce energy consumption, lower costs, and improve reliability for users ranging from music‑streaming services to video‑conferencing apps.
The work highlights how AI‑driven resource management could curb the environmental impact of the rapidly expanding global data‑center footprint.
Using AI to mitigate the growing environmental threat of data centers
MIT News on AI · 8 October 2026
Loading the full article…
This text was published by MIT News on AI and written by Adam Zewe | MIT News. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗
The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.
More in Research
All →- Harvard physicist uses Claude to publish 36 manuscripts in 18 fields in three months · 1 src
- Python 3.15’s profiler finds line-ending code dominates web-edit app · 1 src
- Anthropic research suggests small AI models may self-replicate on IoT devices · 8 src
- DeepMind and Biohub debate AlphaFold’s limits in protein folding · 1 src
- Periodic Labs introduces synthesis superintelligence for materials discovery · 1 src
Comments
via GitHub Discussions