{
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  "created_at": "2026-11-10T16:00:21.480Z",
  "updated_at": "2026-11-10T16:04:58.068Z",
  "title": "Why enterprises are ditching hyperscalers for neoclouds",
  "description": "As GPU costs skyrocket to $200M, neoclouds are winning inference and training workloads. Here's why speed and cost-efficiency are reshaping enterprise infrastructure decisions.",
  "type": "clip",
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    "transcript_url": "https://reelsbuilder.ai/video/6af33f95f88ed367ecf3875a/transcript.txt",
    "transcript": "Today, they're $100 million. Okay, and when the Vera Rubens come out, 16 racks is gonna cost you $170 to $200 million. \n\nThese numbers are mind-boggling. People often ask me, why do we need so many neoclouds? Why don't they just go to the hyperscalers? It isn't necessarily either or, but for inference and training right now, those workloads, we are seeing the neoclouds being chosen. \n\nAnd we're faster. We're a lot less costly. We're more cost-effective as well.",
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    "summary": "As GPU costs skyrocket to $200M, neoclouds are winning inference and training workloads. Here's why speed and cost-efficiency are reshaping enterprise infrastructure decisions.",
    "topics": [
      "YouTube Clip"
    ],
    "source_links": [
      {
        "label": "The Mind-Boggling Cost of the AI Revolution",
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    "handle": null,
    "name": "Alec Furrier",
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