A small tool to view real-world ActivityPub objects as JSON! Enter a URL
or username from Mastodon or a similar service below, and we'll send a
request with
the right
Accept
header
to the server to view the underlying object.
{
"@context": [
"https://www.w3.org/ns/activitystreams",
{
"ostatus": "http://ostatus.org#",
"atomUri": "ostatus:atomUri",
"inReplyToAtomUri": "ostatus:inReplyToAtomUri",
"conversation": "ostatus:conversation",
"sensitive": "as:sensitive",
"toot": "http://joinmastodon.org/ns#",
"votersCount": "toot:votersCount",
"litepub": "http://litepub.social/ns#",
"directMessage": "litepub:directMessage"
}
],
"id": "https://neuromatch.social/users/fabrice13/statuses/112355851093497863",
"type": "Note",
"summary": null,
"inReplyTo": "https://neuromatch.social/users/fabrice13/statuses/112355833572884870",
"published": "2024-04-29T18:10:31Z",
"url": "https://neuromatch.social/@fabrice13/112355851093497863",
"attributedTo": "https://neuromatch.social/users/fabrice13",
"to": [
"https://www.w3.org/ns/activitystreams#Public"
],
"cc": [
"https://neuromatch.social/users/fabrice13/followers"
],
"sensitive": false,
"atomUri": "https://neuromatch.social/users/fabrice13/statuses/112355851093497863",
"inReplyToAtomUri": "https://neuromatch.social/users/fabrice13/statuses/112355833572884870",
"conversation": "tag:neuromatch.social,2024-04-29:objectId=12580489:objectType=Conversation",
"content": "<p>I have found a sort of hidden thread (sounds a bit obsessive) in some research papers from close groups, but they failed (?) to converge on a small systematization and theory of deep learning layers, and then perhaps some extensive experiments to confirm theory driven design choices.<br />I'd like to work on that but I don't have has many person-months and TPU-months as those guys. <br />Might just post a 3 page something on arXiv and 2 lines of code for future collaborations/ruminations</p>",
"contentMap": {
"it": "<p>I have found a sort of hidden thread (sounds a bit obsessive) in some research papers from close groups, but they failed (?) to converge on a small systematization and theory of deep learning layers, and then perhaps some extensive experiments to confirm theory driven design choices.<br />I'd like to work on that but I don't have has many person-months and TPU-months as those guys. <br />Might just post a 3 page something on arXiv and 2 lines of code for future collaborations/ruminations</p>"
},
"attachment": [],
"tag": [],
"replies": {
"id": "https://neuromatch.social/users/fabrice13/statuses/112355851093497863/replies",
"type": "Collection",
"first": {
"type": "CollectionPage",
"next": "https://neuromatch.social/users/fabrice13/statuses/112355851093497863/replies?only_other_accounts=true&page=true",
"partOf": "https://neuromatch.social/users/fabrice13/statuses/112355851093497863/replies",
"items": []
}
},
"likes": {
"id": "https://neuromatch.social/users/fabrice13/statuses/112355851093497863/likes",
"type": "Collection",
"totalItems": 1
},
"shares": {
"id": "https://neuromatch.social/users/fabrice13/statuses/112355851093497863/shares",
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}
}