{
  "video_id": "reddit_1wgazy4",
  "channel_slug": "MachineLearning",
  "channel_handle": "r/MachineLearning",
  "title": "RSI is not happening [R]",
  "url": "https://www.reddit.com/r/MachineLearning/comments/1wgazy4/rsi_is_not_happening_r/",
  "external_url": null,
  "upload_date": "20260914",
  "published_at": "2026-09-14T18:03:41+00:00",
  "transcript": "A new paper (I'm not a coauthor BTW -- I just found it interesting) argues, basically, that RSI is not on the horizon, because current (at the time the study was done) agents cannot do open-ended ML research.\n\nSpecifically, they took some accepted, but unpublished papers from NeurIPS, and tried to get the agents to do the same work, which was then graded by the original authors. And the agents  (Codex/GPT-5.6 Sol and OpenClaw/Opus 4.8) could not do it.\n\nAnd since they cannot do open-ended ML research, they cannot recursively self-improve -- this is their argument.\n\nLink: [https://arxiv.org/abs/2607.27191](https://arxiv.org/abs/2607.27191)\n\nI think I've regretted the last 10 or so times I posted any kind of \"research\" in this subreddit -- either people downvote it, or it gets upvoted, but there is zero meaningful discussion. This might be the last time I'm trying this.\n\n\n\n--- Top Comments ---\n\n\n[167 upvotes] \"argues, basically, that RSI is not on the horizon, because current (at the time the study was done) agents cannot do open-ended ML research.\"\n\nso because they cant do it yet, its 'not on the horizon'? how do they bridge the gap between those things?\n\nThis is still a really good paper tho\n\n[95 upvotes] I read the abstract and I think you made a big claim that the authors don't themselves make. \n\nThe paper is titled \"Can agents conduct open-ended AI research?\" And the last sentence of the abstract is, \"Our results provide early evidence that today's agents can do the engineering of AI research, but struggle with critical parts of the research lifecycle.\"\n\nNowhere, absolutely nowhere, do they make the claim that RSI is not on the horizon. \n\nAnd in fact, I think your claim on that is a bad take.\n> Since they cannot do open-ended ML research, they cannot recursively self-improve\n\n**(1) RSI doesn't have to mean \"fully autonomous RSI\"; AI models and their harnesses are already meaningfully accelerating the pace of AI research.** \n\nAlmost all of the coding is being done by these systems and not by people. Smaller teams are able to do more research more effectively. Things like hyperparameter optimization, even basic architecture selection, are able to be largely automated. LLMs can help people do literature reviews for ideas. They can help pressure-test experimental hypotheses. By no means are they doing a closed-loop end-to-end speedup of the process but they are an indispensable part \n\n[59 upvotes] ...doesn't that methodology only prove that these models in question (GPT 5.6 and Opus 4.8) aren't capable of RSI - something we already knew? \n\n[37 upvotes] Maybe people are downvoting because the papers are bad. This one is definitely bad for the following two obvious reasons.\n\n1. They use one agent per task. RSI will be a coordinated effort between quite literally millions of agents. Just look at the navier stokes setup. And that was a tiny side project to generate some headlines.\n2. There's an obvious bias on the part of the graders. Our entire social environment rn is defined by people pretending AI can't do their jobs. AI researchers are not immune.\n\nI’m sure there are more flaws that a deeper dive would uncover.",
  "transcript_chars": 3168,
  "ingested_at": "2026-09-15T01:30:09.585790+00:00",
  "source": "reddit",
  "yt_meta": {
    "score": 178,
    "upvote_ratio": 0.81,
    "num_comments": 110,
    "author": "we_are_mammals",
    "is_self": true
  }
}