Pith. sign in

REVIEW 2 cited by

Compute at Scale: A Broad Investigation into the Data Center Industry

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2311.02651 v4 pith:D5CM2UDP submitted 2023-11-05 cs.CY cs.AI

classification cs.CYcs.AI
keywords datacenterscentercomputeindustryimportantlargelarge-scale
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
abstract

This report characterizes the data center industry and its importance for AI development. Data centers are industrial facilities that efficiently provide compute at scale and thus constitute the engine rooms of today's digital economy. As large-scale AI training and inference become increasingly computationally expensive, they are dominantly executed from this designated infrastructure. Key features of data centers include large-scale compute clusters that require extensive cooling and consume large amounts of power, the need for fast connectivity both within the data center and to the internet, and an emphasis on security and reliability. The global industry is valued at approximately $250B and is expected to double over the next seven years. There are likely about 500 large (above 10 MW) data centers globally, with the US, Europe, and China constituting the most important markets. The report further covers important actors, business models, main inputs, and typical locations of data centers.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. How to Catch a GPU: A Taxonomy of Verification and Enforcement Mechanisms for International AI Agreements

    cs.CY 2026-06 conditional novelty 6.0 of 10

    Verification of international AI agreements will fail first at detecting hidden compute facilities, around the 10,000-H100-equivalent scale, before other enforcement mechanisms break.

  2. AI Governance to Avoid Extinction: The Strategic Landscape and Actionable Research Questions

    cs.CY 2025-05 conditional novelty 6.0 of 10

    A MIRI governance agenda argues for an internationally coordinated halt to dangerous AI development and catalogs around 400 research questions across four strategic scenarios.

Pith tools