{
  "id": 19141,
  "title": "LinkedIn Won’t Be Expanding Its Data Centers in the Next Year",
  "url": "https://urgent.news/2026/07/30/linkedin-wont-be-expanding-its-data-centers-in-the-next-year",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-07-30T10:15:00.000Z",
  "source": {
    "name": "Wired Business",
    "slug": "wired-business",
    "url": "https://www.wired.com/story/how-linkedin-is-keeping-its-compute-capacity-flat/"
  },
  "original_language": "en",
  "account": "LinkedIn, the social media platform owned by Microsoft, has announced it will not expand its data centers within the next year. This decision comes as the company has found ways to make its existing graphics processing units (GPUs) twice as efficient over the past six months. LinkedIn's Chief Technology Officer for Engineering, Erran Berger, explained that the goal is to maintain a stable compute footprint while launching more compute-intensive features. The company's CTO for Infrastructure, Raghu Hiremagalur, added that this prudence in spending will encourage engineering teams to innovate further in developing new generative AI features. While other tech giants like OpenAI, Meta, and Google are investing heavily in AI and building massive data centers, LinkedIn stands out by bucking this trend. The company's efficiency gains could potentially lead to more out of its current data center expansions when budgets increase again in the future. LinkedIn's move to own its data centers after moving from Microsoft Azure has given the company greater control over its technology, enabling it to optimize AI usage across the entire pipeline, from training models to serving them in response to user queries. The company has also employed techniques such as distillation to train smaller AI models, which are more cost-effective without sacrificing quality. These efforts have saved LinkedIn approximately $24 million over the past year, equivalent to around 1,100 GPUs running continuously for a year. Despite the significant cost savings, LinkedIn acknowledges that the industry's investment in AI remains substantial, but its approach suggests a shift towards a more disciplined and sustainable production environment.",
  "summary": "Despite the ongoing AI boom, LinkedIn is holding the line on compute spending. Instead, it’s challenging engineers to make every GPU count.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}