{
  "id": 16754002,
  "title": "Machenta Raises $40 Million in Seed Funding to Train Robots Without Real-World Data",
  "url": "https://urgent.news/2026/10/27/machenta-raises-40-million-in-seed-funding-to-train-robots-without",
  "topic": "business",
  "section": "Business",
  "published": "2026-10-27T13:54:50.000Z",
  "source": {
    "name": "Ventureburn",
    "slug": "ventureburn",
    "url": "https://ventureburn.com/machenta-raises-40-million-seed-robots-without-real-world-data/"
  },
  "original_language": "en",
  "account": "Machenta, a London-based startup, has acquired $40 million in seed funding to revolutionize robotics by training robots without relying on real-world data. Founded in 2025 by Imperial College London professor Edward Johns and former PhD student Vitalis Vosylius, the company aims to train robots through simulated environments that mimic real-world physics. The $40 million round was led by Creandum and Union Square Ventures, making it a significant investment for a startup with just 11 employees. Unlike traditional robotics companies that collect real-world data, Machenta's model learns entirely inside computer-generated worlds, enabling robots to learn new tasks from just one demonstration. This approach could potentially reshape the robotics industry by reducing the cost and time required to train robots, while also allowing smaller teams to compete with larger players.",
  "summary": "Most robotics companies are racing to collect mountains of real-world data. Machenta is doing the opposite. Machenta raises $40 million in seed funding to train robots without any real-world data. The post Machenta Raises $40 Million in Seed Funding to Train Robots Without Real-World Data appeared first on Ventureburn .",
  "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."
}