{
  "$type": "site.standard.document",
  "bskyPostRef": {
    "cid": "bafyreiczqidechslcnta5eicckwqxecm5gpmcp7nbr2cddbcab344szjte",
    "uri": "at://did:plc:ox2kiwcr2xmn32p25g472pp7/app.bsky.feed.post/3miskr7f3wjq2"
  },
  "coverImage": {
    "$type": "blob",
    "ref": {
      "$link": "bafkreidwm26voarvskkqqagif7pnyocb4pvyevhyolm4z4znorls2mslgu"
    },
    "mimeType": "image/webp",
    "size": 194164
  },
  "path": "/releases/2026/04/260405003952.htm",
  "publishedAt": "2026-04-05T21:23:54.000Z",
  "site": "https://www.sciencedaily.com",
  "textContent": "AI is consuming staggering amounts of energy—already over 10% of U.S. electricity—and the demand is only accelerating. Now, researchers have unveiled a radically more efficient approach that could slash AI energy use by up to 100× while actually improving accuracy. By combining neural networks with human-like symbolic reasoning, their system helps robots think more logically instead of relying on brute-force trial and error.",
  "title": "AI breakthrough cuts energy use by 100x while boosting accuracy"
}