Run step

Step 3: assistant

2026-11-11 20:23:13 UTC · previous step · next step

thinking

Calls code_execution

{
  "code": "import json\nfor q in [\"iterated amplification training language model 2025\",\"iterated distillation and amplification Deep Cogito method\",\"recursive reward modeling amplification experiment fuzzy task 2026\"]:\n    r=await web_search({\"query\":q})\n    for x in r[:6]:\n        print(x.get('title'),'|',x.get('url'),'|',(x.get('content') or '')[:200].replace('\\n',' '))\n    print('---')"
}

Calls web_search

{
  "query": "iterated amplification training language model 2025"
}

web_search_tool_result

{
  "type": "web_search_tool_result",
  "caller": {
    "type": "code_execution_20260120",
    "tool_id": "srvtoolu_01CUhmVf9ybwtQrER2vR9Z8u"
  },
  "content": [
    {
      "url": "https://arxiv.org/pdf/2605.01130",
      "type": "web_search_result",
      "title": "Iterative Finetuning is Mostly Idempotent",
      "page_age": null,
      "encrypted_content": "Es4NCioIFRgCIiRhOGFlOWMyMy1iYWVmLTRiYzctOWJjYS04YTM3MTE5YWVhMGMSDPMKHdxIiEjsa0n1AhoM3FUuD65z9WWX1At+IjB8NneYmS0ORXdwVJdnN2k40gTzZRD5+ZvUq0sBvqes3CfZAf5pu77/Gc9aTRudQcoq0QxSzdkRhFYvu96wYNHgwgZtYeyfy86EKRSXEAvBzaTYH0rr7pswpHSYVaiM2vYomaTa1Hpq2kUS4PMC15i+dAPC91q5wujLgOPPMfqaXchyybno+J3i+Qm4U/HhTbkrzoP0nI7iPCrfCBGndqhIWRCwW9P7QLZFZ+gt0T6T+os+sLNoOvkVooSRFk7mExavudHj7+uOk7F2MoJhi1nLFlSF1jVql+gqFtTEPw6IKkJ8Oi+fh9bSSEEoA0pAiYvGhXAyFRpC32T7WTQ99sj70JOBCjlUkJHEOjNbXIZDI7rbPm1qmR8JbjN2K/d+z+Mhzua1vLVUGIzANdsLym0Xr/OiThSBtowsMXjb+gyXKer7pnrbbrlDoW+aZkDSd1gQQg57TnEIrmfJ3wCiYJceCcB8Iv380Qk27Ny4q3tdxYj7W4ThA0Bhw4voK1t6asHnEy4wP1v2eXaNSIErRy41iK5/0K394C4uYjFbPqY220IM1QY9wUondcHufBaGGAFQY87t+/E2a04tf11lgUNg0rraUQUahQv5GTVURMt+4RurnIACVggtevC0BscnGr6h10XL2e/0q8uN26WQDfLiy6WBA9Jcj7uFLRsJZ9SD+R0l8NgJ80opGPoAtf91XJETbnyUHbRBgBJyUh1bk+NUbpFtW2BWglS9PuLRakUcurRKUHt0Ky9wxUnW6riw+iC1XGgBX2Lq4A8js7bLIc7tEVZrozg5CRY975aJet92VEK00dyyoZ3AWMDpp5TtvcfH4pzLa/WrEO6ks5Ux3wmyB70I8tiVnHLhKd/cWTSXsEyD5vfPOFGYWUvq0Go4wPBWbReRlC0AvirRCZxE3GplwBDglqy4SLcZmkA86Tn7yYnhuMD8R3b5MFoDNO1NZOf5oyu5K0+y8fm9RXB6/MLcqbPPs9miC/yo0WI0OFUjuuuePppoM4yODTmOG4m0WV1AtH41E/85SHy+LKZpIVMaiySzSO1WzBXk9pypl3tanReUe7+iboioBNIwuv+wPmJb4sLgZEnLemOGN72+J2uQbk/rku9X/Cj9ECldfoo4F27xP08jml/Gt3wnGTvd7aNswona4qh6FSyT5GGmMZq1DNr85kVG6VUW36wlFeMQMK3P2tdgWsVUgMmTUSMVoMUSlyV7Tzo+Ic1jrqNC3oy9bos6QqYLAxvGzj+j1A3lRlDaq1pYMD9ZO+tnXHROcPspcKcCnRV+7dmeve1852jrmEwPkQHj1vMSxr5Mbe+9W2rROoCqHzXHR7TlfoYNf2WHpGqDwjfQ0QgV1+uioEzcK7QlgOwumwNckYKMjqouq154COqipUtORzErbWkwWXHN8V/WD9v/LumA7D/cNgT6/7o4KY+MS3QtrnR1gdpei6JfivWHmdbAS0ghiH3l0qnuauBIxFwVSNLqJWqv7Dx56adw+nMr+lZuLEpnmybyK2e2XNmLO2j0ftEfOjsyRuw0oKwp+BteT/76iWKXRPcFqK0zk2jKnvzkan1Ix9+60szQUymLFZusiYHyU9o011HY4j/fEinK6Nhif2CENsdUDztK5hZJ7NjYKTeKxuPC6Mb2jL925+8bqwK8BngMxwgTQghF7weOassSk7H3gzSTn7EAmMcVCqQp4C1R6dMw+V8gTNnZwO1SN0OELjQ6BdE/MzZACyx0WaZ++Xtl2zzeG1QxYMYnaj6c7zWcnklehdmFE/sV+ID5XUY8XbR43H78R3MBGARsCdkDwYOSfbT5CAVz7bLzmwWe9/hFvn48krp6dPqVK4EH+U8jFbE9OjsAipeQ1G4iv84EMBxMUMzGKcw1LI72cHMVvxfLqR5Z1+wwsNph4mbLBNytN5Fw6aQ4XWiEKqzif20s4c1ryLPcV4N42WmYNWKREoJpQ1MqZAD9LudqMgBoqThUU+eVmycLsMLUzy/bQ/iwCizElwiHaUEIck+YesSPKEd4O+UpymcrtUWkgsgzGVV4mBTh3n4SUXhGfK7gO4ohPaUo1rwwmiz+sBgleYx5k/b5P3y6HWQbkJXj1a3phWJTgGQtTZigPz5kJZ2TkXhFcjfNxdC3V7Bnm/NKLi7drj3hhRxZUgZDaeHQMwiSSkE0us9qwYSS9AXhXk8rS+Elyz9OJdqL2QnF5AfYMqHgckvgp9OaVzUOw2EYAw=="
    },
    {
      "url": "https://arxiv.org/pdf/2603.25681",
      "type": "web_search_result",
      "title": "Self-Improvement of Large Language Models: A Technical Overview and Future Outlook",
      "page_age": null,
      "encrypted_content": "EtUNCioIFRgCIiRhOGFlOWMyMy1iYWVmLTRiYzctOWJjYS04YTM3MTE5YWVhMGMSDNFQdaGbXagq+9vSfBoM3XDQchnpwnJhe805IjA6JMAFpz0/7tL60Qc0ksh/DPSW5ny+/q+Nws3o2GuiYHuWSEOhj71nj/pJExQFX5sq2AzrtrYDt60jUV+ux8CcG0oWRJlObVogzznSX/cxO0M95w3oXnpw+dcoLwUmXGnJNuew1UsjYPh4yZmJOsDnzZ4cPinemt8Jys+oQIp+/KvcrWSQR40SNeXmhSPUzK6a7j+gLAu/WdYIC3meLcYjuzeVMwPZE0Wh11XaZmDy92kbq71uAEv9awZuq2utZv8HS74hW8Fu3xLgttbbdOB03s4TZjVTr4A1FfHZlF3IAKIFRZbv6hW1nipHR4wHWjSPFh5drO+yhQZ1PPwYACn99x9MugZfKXfgu3ld6JsgPBghdnxXuncDCzQSWd6O23tZxZz9aah15IOQjecHOS4BZeBmMDq+kQpm2X1PWzNd50SHbreXyP6hQkvtMAE2KZKKV/e/oNauuAH4d5c/V29UCF8pd81JuF04KTyXBL/9t0pQvI0dGcGcMXmaeV/kbi43ozA7SHQ6IC7DE2+qyS4nAd6CnS7pxDKk0A8ap+ne/VxL/WC7vIN+v0355tsdkZQ9+RjWeAWqYef9WoIb3Bc7B3mOc0xmJifZo7EEQ3DSeBQ4ADXgivcK53ELsE03U2z3ceeCh8ypCu9wc4madZddhKWpI07AAuJ5MEICMiDv2J//GNdDKSRS19lKr7NLAUZ2yBeJcbBcgcO6roypmc1Z2OHLd7tdf6JQ5x4CwdHK7Krp/r3yQpbr4TCtSW9fI3a7xo91OawAQOWWuj+gjtKVSHbAQEcrRGDLp5rXldNw7LZ41D//nygHFrxtfRZ+rK4tcj5PROywF98/EdjGThLL4IGcbdnCDHZwLbUSnFTrGWAMQ06lRkmV/jTxD7Icp7IOPg7Ju0ZJ8xyC22fogImJnX0MnC6HAxG7Ll/3F+b0PFQtKtldxNCMI2iFQ2QQWlxAmT2RytQRtO4yAcvIEUOimxaqEgS5F/9uxHGyjkMuubfPCnzRoQ+RCLcvGiS7AohCcXEpmeLYAkV5ho/D08VPeY4wLymjcj0LIKGtOtUbu5KuBhIxoNaFW2qovhwK+/BEu28uC33gItshPCuulo/qkUMNCxTCrvBmz0cK59rKDa/dbv9C7yuHO/IaDk3X4o1zWjPN0czQ1c+DORFCkmLgUM8Pa2Goe120N1Eeybz5w+r3amI/Ug3kDtIzwv9jKukb1yL1oLFYtz5jTOpWDH/k2trF7f6eLWC3FpLOqREY9h9KyvBi6oKzuRd8rSVtU1WFtrfPW+CMUMTkUtHNp5X420W2D/V61afO+lYQaSnS4EWAWM356X9Y327WF+Cmuh5KL3/BwS+hW5WQVb2Ns5ebtFtVtetX+2WnusEGaNhEewKJZvhWrlpeayuHj1mXA6OYW7QajpDcBK3cI8SR4awk0DzCiYMwfgGqw2tkIX0A145X5FEvDl28OHSKsggYQuY1pNFQP3Xk+VlwqvabzI4HXWZNWj1cRYazQnH4W7ggxWVRjozMueFiO8e5PbUTbxX4uyHEUruqyvZuJY1k3KcEo/RtJlx/0qWQ6FW61JEA8oBEYllkm9AVh3s1DkyJAI7WRhAlqSVTN/nVMBd+BoCEDA99rWtPgyHGUSL16Er86p1XQZ8zeR5FhUhgBsQCx5YPevss/KcNzwByjwVOLFtWIZV0eQWySHddGaLyo7KhiVlUoRoHK7BidysmDB9/GsfuTaUOqSo9N7gwsudQM3PL9yiJj3d5rDKGmsaLJXK+RgBuZzocvX54na+zUTo0sEPLYUYGY3NVpCx+Dq9Ri+dATjlCH+Rrg6O7wk6CunABVuzj+5MM9/EW0ebZB48BR9iH7KRzxfg+UIyTq1Dp9XzInkdxSdQ1C8WiRxxoUI0KPkU5VygqteCSEL9jlBpk14b05/jWxGnfPDfQ8/XXJk7FWZv85igLo2Rc7rYu4sK2hi783O3RpcLszvkYVPt/f3LhIJN5Pcw/EhSRcIf3EpgJ+y0N0lNfKADewCqi2N1z98Ucee7JupzcjCa9hurcvlvyzE052/vP7J66ZMxC9B3oujVuEJW9UTDVmA973usbZ5YPDAlNVLTjZ7llg3VfRpTrl0OlR4p8LlhC7fnDyNGfuGf+tvUrYq0yhGPyhJhKzKlEBY46WAl30/T72RtowOFzAOPFeqpTdnpx0qTGAQdyf45gc9hjSh7wZOotxO8HKLjXnOYO9S3t1eGXGAM="
    },
    {
      "url": "https://arxiv.org/html/2404.04286",
      "type": "web_search_result",
      "title": "Bias Amplification in Language Model Evolution:An Iterated Learning Perspective",
      "page_age": null,
      "encrypted_content": "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"
    },
    {
      "url": "https://arxiv.org/pdf/2608.24949",
      "type": "web_search_result",
      "title": "Demystifying Reinforcement Learning Post-Training of Language Models",
      "page_age": null,
      "encrypted_content": "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"
    },
    {
      "url": "https://clay-atlas.com/us/blog/2025/07/01/en-iterated-distillation-and-amplification/",
      "type": "web_search_result",
      "title": "Personal Interpretation of Cogito Trained with Iterated Distillation and Amplification (IDA) - Clay-Technology World",
      "page_age": "498 days ago",
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    {
      "url": "https://koshurai.medium.com/understanding-iterated-distillation-and-amplification-ida-in-llms-the-secret-sauce-to-superhuman-5d02cf64522a",
      "type": "web_search_result",
      "title": "Understanding Iterated Distillation and Amplification (IDA) in LLMs: The Secret Sauce to Superhuman AI?",
      "page_age": "577 days ago",
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      "url": "https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/12430515",
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    },
    {
      "url": "https://arxiv.org/pdf/2602.16490",
      "type": "web_search_result",
      "title": "From Growing to Looping: A Unified View of Iterative Computation in LLMs",
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    {
      "url": "https://openai.com/index/learning-complex-goals-with-iterated-amplification/",
      "type": "web_search_result",
      "title": "Learning complex goals with iterated amplification",
      "page_age": "2942 days ago",
      "encrypted_content": "EtkNCioIFRgCIiRhOGFlOWMyMy1iYWVmLTRiYzctOWJjYS04YTM3MTE5YWVhMGMSDCcn7CFN8OJJN94JxhoMEDcNYJha6PUrCKhtIjDo19nVOxfLMXfNcfF7YuW//zJAKSporVDmSZdmvL2X1RTmTmQ4AvE0m3ShnSaJhSgq3AzDWE/vrORFA0NY0fcSS9r9s7fvWWgf688G+7GoinfMNfsIerJFSy9J2oAsGf8bIWprYY5EEEadDYrSz89v1a07V+j/bp0SKQqv6jSIhijDX2zuLQMBwSxLAMATQCltaLSDWOynCEV8yAASxH7DJWRqAOM4tVIcSGxbdvRP6zOkVHWGw5g1eOx1eXr4V5IhtKbGj3zXZHcIegLpCBH96QjxCP9FQz9N3GQnM3mH5BpLHI++r8P0/oXMwM4paRSVsyW0LdHTOhtReDBngQ1PpLt0SOcfZTk0Q99cm1xMPUEWDDDuSyjAk3oK6cX4fgf6ryH70eoKXUYbsxcxX2pA+qZumt4roEdd2CJzYYmItP7vFPpBekBHmATlOvlJ7huJinBFVc/VXw+LDU9TXjzv6ZTKFKixhZhSxarDCABE4Csg5rNXRad7FEYcP8o+9JBsN/BZAPDjBSARlJNKiJZw4tOsXVQDeW9aIsf1s1rjqk5z4V2fq4vFGhHdLLVAvvgM3nLINxqv8aVXJpW6sI2DXNTyYs9ibmUaYQEZjII+hKndXEeQ0k5NtWGUeS5GgDuAmXh9+bw5zWiCeSzNOlxV43/oJfZMYfurCHrvgXwXoPwK8EMR3cUdH3TICR/SxBoOJB/xZCubxYhz5UjXqAdGJ92GZDYfvgubfftnwhQnU9BS36D9UaPd9SO2zLIpd3T4hHBObwe8Nn7jGc+FusocIRXXbuI3OFtHcG8LlAT/o6AyNpDeiXwZAXpZA8caDocnVKfXiY1IIopJ/CyosVuvJrIJ5UEezu3v36CBxTo2INASjCorT8RVoAGYvaz+u0l+xjqwEPRUOUsSYKv+U1DP3XglWYxx7k6Bu6rRe/hTZ+vIIiZBFay5un6egPxKotYkT3K/RyKlR9eTk8J5dBR3gvKNUlR6J5LqWF5TDzAsWOQ9R2/xKS0Iiyx8+nCZTMGpAGeUmxcteHsKnVUUySpZ+QzWf950XEhv1+K2AqoQrbi3SlYvlATyEg4HzYCBQILekzeVl9y0go6xu+PzXJF9H8APXekTfRKYsYPEetqwxyRoF6gcCP+oriuq65Ormh4JHHMNXu4PRO1nPSYzy+54dGcYcpnOq4VuYh5tqm8nZE74yTOWAcqsFsEMDOIYUCI/pk4XeWue/YJQn/TMAHBXppztQovyT9PuT2aeO8h1RES/6bdpQLKr8UuNPZL3JDiuktdp3QpXG4XGbARRwNFi3UjZr5WpVkaB4wubevyNWInq+nnr3bwV/suFLqjBRcxIMWKXh0o1Aubxft3JWz2Jqwb7f0BIU+NYQekVbywHXJaXF84/AbDw790hfAV6LeJV14LikeU8fm7uH1sww+FrqVVPn6EsNGnnYw5sAFaqNTYXu+4JjD+VXa6CUD6U7r7efpcR328oq8QmvOOLHm8yBqYGRiznKi1qw/hwN+fxgGuX0xyY4ME2S5fIFO3tAjF41ERSqyewI0PJDVGD29VY0cdWf8l9JKoN6/qFpTSMgTpw1TouiKxe2ON08lK1jQTXN/tkhUBf3sJp7prXyJ8gMR5KCeEJc8lnzpIu6yYUkANBg0rLxQp0xZ9FT1I2ZrOhUr7gDLrKIC636Aq7G16uWWeDQPXgANkiwcQxv2CKYu7IGkIGN1vab6aT2W4BN40K1sZEcBITG92P4k6cjSvi8Bi31W2ymulsaQExF/syHrL5lh0/QCRnlXI10ZyEf3RifNuTjBK9SIBgriQKjp2qWaIj/5tGmW5LIJStMopodWaSYiB1+gn4PGiqYgJ6yD8AEtZ77ei7zVus9PtIRLOLoUx8hudjvFK/gV9p95HB4TbSsMl3cn1fWxySZqSxu6p7kq9EGYtLfUOj2eOAFD2taTTCspOaL1A386wODyTL+2nPtRBQvkkBOsQS/fQ+qho5asYDJvlGLy2W7Bm+Dxqg3dvnyDdK+vREtH4dUDEqpomC8v0ajSSwHCbgf4y1fhaaRTHHW0Dg6Qs7qWckLsXBD7P8JaVCl2AxB9mzZodl3w2DOUMwExSz3v7OGMp882VN0SUcwDGjEmfJsHJnbtDWJ8qf+uxNNtflI88Rnzu/LDzLnjRfWo5aD2B2TRJglycGk/6kP9ztpSLBVD/eq31qOOiNNb9MOKT+4TsBL4HK5zkHub3Q9xEXLBvBajStJBgD"
    }
  ],
  "tool_use_id": "srvtoolu_017ifynjbHvTBJuMwTQLZDu3"
}

code_execution_tool_result

{
  "type": "code_execution_tool_result",
  "content": {
    "type": "encrypted_code_execution_result",
    "stderr": "Traceback (most recent call last):\n  File \"/usr/local/lib/python3.11/asyncio/runners.py\", line 190, in run\n    return runner.run(main)\n           ^^^^^^^^^^^^^^^^\n  File \"/usr/local/lib/python3.11/asyncio/runners.py\", line 118, in run\n    return self._loop.run_until_complete(task)\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/usr/local/lib/python3.11/asyncio/base_events.py\", line 654, in run_until_complete\n    return future.result()\n           ^^^^^^^^^^^^^^^\n  File \"/tmp/srvtoolu_01CUhmVf9ybwtQrER2vR9Z8u/cell.py\", line 12, in <module>\n    print(x.get('title'),'|',x.get('url'),'|',(x.get('content') or '')[:200].replace('\\n',' '))\n          ^^^^^\nAttributeError: 'str' object has no attribute 'get'\n",
    "content": [],
    "return_code": 1,
    "encrypted_stdout": "Eo4BCioIFRgCIiRhOGFlOWMyMy1iYWVmLTRiYzctOWJjYS04YTM3MTE5YWVhMGMSDFJkAvOSnm5UTLfk4hoM4qGi4Zg+GJUDW981IjCW6tFZhJoFkCkOlnOg+WOco8fcUslPfQIhUDJld6ibbKlAcvu5o8YPCjYr9kS4kPsqEn9tJqFxgu2azY2wBXz5LBg3mhgD"
  },
  "tool_use_id": "srvtoolu_01CUhmVf9ybwtQrER2vR9Z8u"
}

Calls code_execution

{
  "code": "for q in [\"iterated amplification training language model 2025\",\"iterated distillation and amplification Deep Cogito method\",\"iterated amplification empirical demonstration real-world task\"]:\n    r=await web_search({\"query\":q})\n    if isinstance(r,str): r=json.loads(r)\n    for x in r[:6]:\n        if isinstance(x,dict): print(x.get('title'),'|',x.get('url'),'|',(x.get('content') or '')[:200].replace('\\n',' '))\n        else: print(str(x)[:200])\n    print('---')"
}

Calls web_search

{
  "query": "iterated amplification training language model 2025"
}

web_search_tool_result

{
  "type": "web_search_tool_result",
  "caller": {
    "type": "code_execution_20260120",
    "tool_id": "srvtoolu_01P7nNxbmCLWzGWZozYSFPTd"
  },
  "content": [
    {
      "url": "https://arxiv.org/pdf/2605.01130",
      "type": "web_search_result",
      "title": "Iterative Finetuning is Mostly Idempotent",
      "page_age": null,
      "encrypted_content": "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"
    },
    {
      "url": "https://arxiv.org/pdf/2603.25681",
      "type": "web_search_result",
      "title": "Self-Improvement of Large Language Models: A Technical Overview and Future Outlook",
      "page_age": null,
      "encrypted_content": "EtUNCioIFRgCIiRhOGFlOWMyMy1iYWVmLTRiYzctOWJjYS04YTM3MTE5YWVhMGMSDLi+MklWHnDwIZeJjRoMO6xuBXDbqohrAg7KIjDHuxKc5vBwIkUYHkBH3x33V/NDDNkfvk59XjpiZEAv9O/GT/knI+Sc/PQxRy9CwkYq2AwRTKb48xKSDCsvl43vI0YWfqu9UuUJvQlEv6nLwrKSXmv3IMt5bvpVZBJgPWQAaN+E05LTwEpY9L9cfrXBbIFUTTNvj8zMP48RVYPcfy5UC8m/UL9IdJ3DETvXj4L8weIRUHtbLFb6uaIV5fJrTz1rNSadkx0bASijPVLajmw21JE5fmM4sQyAWjJ2HLaRpa2pEfJCK7iX8KHRB6LhphAEbMBc7Gd8BZmJFMBnnKykZ8hVNSCxAWMHkvDcb7vw8WFb0ps3L8txx2Hn1tY1nYs3BHiRfOI9bwyWGr7s/qvGlQtQZHEIdI1NTpl3NPkJOZbmNviaz0QCL8lC+iH8EmcRIrt2MNwepgWimKOX9MTyjwwMzci5dPjwDa5vwA0JVfBdJapEvL8lbU62ueh473MhwvbazgI+UdX3Md4bdiir1oiObiFHbyvQHlOMSe//+i7MFAH4btLRezUdWqXHrCqjHY4xG2wjPh8mUGhPnLpu4bE7+2KJCHqhYmqy/MWVqfYRDTWXVCXQP9SalhWa1/ttVpomLhMM1JVpkVkdrYY9XUqw4Xdq1Df8PtIG9i9iQr3z76d1D65z9QNfXtQtzOyfJNDmqhO9KFyp2U9u3ChwLMKTFteys9oWiFbpQi0Iaegk8nMDKAiiH8m8HvRZYo044X0R94xE6vmPv5GbnNETJmmubycVg3NOdTcvGFaxCP0xNQpCzg7F5GCPhqIxnu5QKVBBFNpt2tm/t86NFTzEas+VzznUyHQ66Gwa4/ieDSoTrtQ2oor7p1ED+HEjAG9FAB/jBKWbssBbueQVXUN9tV0Iv3WNlaRdbYXs/tuIn0X4unF1LnY3ss8Z6xaEXPRn5QMrfreEks8oZpDNwmIIGrfuRgESJkOZ4/szyzcJ2f796LRrjRb90tHk4EeX37kTOAs1NY8q7MKkH8CufgwB/QRlBodsEr8OYVf6spAteoo/PsZcBUYxA1XXp22A5CS7Cgd8KCFfzlVEckFZ9KS4rimEXPDMVyupsny6h1M5cKZuq5asd0otdNjOVq9InnRgMe5GEZUrYcHqfN3Rin4A2sKGwC8VBZfUBllzczRVLd7j4ggOfqS64waPsiHHziJnz5wuK1jNTAops6CG8oaoIR7fyKW0ls71xpO1cWwq45YOQKYGxd8se7WeiI54p1CZp41vrFZdyENS3JSqGGVzoQQ1Hjksp96+Bk/QvW51H+IKC0ygj6tAUJCDUFbgK0++mwx5z7atTxiZmQ28TqQob/DVTFqI2lUMRL77/hVOdr1W21e7bXDzwMRF782XQRIklyROAS3u0tFXS3MLQa1SHaKW0wdo0tjrEnRbu9yGZ4rRLK+S3bVkycxUOaUb/FYgNboJaELNYalPyrgAOyPItvJxC8PVq1ja0h2WwguVnHQQ0gFZ0rttb3r+3uHDNUqGkXTQQDpcTtoM5T3QthifDG/t+RQi9iwPzV719imkMd66CxpXxcoX6UEul1aqVTjJqvYIJ6IudnvZ5dCxLG++8ThAxeEdMa0krSlCWi8OfLlTLDvEKGx0MO/kqjLJ/mfIm3THa/qdLa8JwHWHvc7hJNCI5fSelo65JwSOezUs++iMERAOKhPmU3dNil4x4QbqpBGffUrLEbJSz3/DZQ51QvFGQsslPO/bljvpfcbp5f1yXr9Rm+s+EYfwj5jGnZJ2IDVx0GUZY8/WfFXziWX4CiH0oBWScPVzzpah5tpw02uQb+tsT0tKfwHwoqBOWw2gEflqv8Dq3435cv6CUEt/l/MLTjk0pQ5jwKW0r0xR7ZtBJfFayu1zOELhLh4BBFoYUIwiCkjUDhC5/BIh0rdMRmCTPayAKdCPU2NraRQoLxIbeOm3kiHAT8IhION7+4cG5bs2aDk5g/F8uTshpnKxqYtacHGQMUJDKXrf1rvZ+Nznw78ELRUI5FDzIQz30bgTxiHtj/mX2GNp6wxA1oV72JaPWAAhy3XmU3KyM0YK+49kAWK29kuszBVhQyXKHCbECFwpQZteE/YOJjvT9x+nu9Uvbzv89VRQ4fZdfPgz1BPYGnnXJ+rQDZ1qFx3DIx4TWUe1XcyvcHhAx1b1ITpShHCIdIjQzug4pl5TMf8qWXLPJzXSzJJueqbDgz1vHRb2d6/M3A6koxe1QzgePvmiltSbbaOZsP5rGAM="
    },
    {
      "url": "https://arxiv.org/html/2404.04286",
      "type": "web_search_result",
      "title": "Bias Amplification in Language Model Evolution:An Iterated Learning Perspective",
      "page_age": null,
      "encrypted_content": "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"
    },
    {
      "url": "https://arxiv.org/pdf/2608.24949",
      "type": "web_search_result",
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      "url": "https://clay-atlas.com/us/blog/2025/07/01/en-iterated-distillation-and-amplification/",
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      "title": "Personal Interpretation of Cogito Trained with Iterated Distillation and Amplification (IDA) - Clay-Technology World",
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      "type": "web_search_result",
      "title": "Understanding Iterated Distillation and Amplification (IDA) in LLMs: The Secret Sauce to Superhuman AI?",
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      "title": "From Growing to Looping: A Unified View of Iterative Computation in LLMs",
      "page_age": null,
      "encrypted_content": "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"
    },
    {
      "url": "https://openai.com/index/learning-complex-goals-with-iterated-amplification/",
      "type": "web_search_result",
      "title": "Learning complex goals with iterated amplification",
      "page_age": "2942 days ago",
      "encrypted_content": "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"
    }
  ],
  "tool_use_id": "srvtoolu_019ZdrT9XQJtg3L23Fn2PKcT"
}

Calls web_search

{
  "query": "iterated distillation and amplification Deep Cogito method"
}

web_search_tool_result

{
  "type": "web_search_tool_result",
  "caller": {
    "type": "code_execution_20260120",
    "tool_id": "srvtoolu_01P7nNxbmCLWzGWZozYSFPTd"
  },
  "content": [
    {
      "url": "https://venturebeat.com/ai/deep-cogito-goes-big-releasing-4-new-open-source-hybrid-reasoning-models-with-self-improving-intuition",
      "type": "web_search_result",
      "title": "Deep Cogito goes big, releasing 4 new open source hybrid reasoning models with self-improving 'intuition'",
      "page_age": "467 days ago",
      "encrypted_content": "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"
    },
    {
      "url": "https://venturebeat.com/ai/new-open-source-ai-company-deep-cogito-releases-first-models-and-theyre-already-topping-the-charts",
      "type": "web_search_result",
      "title": "New open source AI company Deep Cogito releases first models and they're already topping the charts",
      "page_age": "581 days ago",
      "encrypted_content": "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"
    },
    {
      "url": "https://techround.co.uk/news/what-deep-cogito-how-does-work/",
      "type": "web_search_result",
      "title": "What Is Deep Cogito, And How Does It Work? - TechRound",
      "page_age": "581 days ago",
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    {
      "url": "https://clay-atlas.com/us/blog/2025/07/01/en-iterated-distillation-and-amplification/",
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      "title": "Personal Interpretation of Cogito Trained with Iterated Distillation and Amplification (IDA) - Clay-Technology World",
      "page_age": "498 days ago",
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    {
      "url": "https://www.nextbigfuture.com/2025/07/cogito-v2-inference-time-search-and-new-ai-self-improvement.html",
      "type": "web_search_result",
      "title": "Cogito v2",
      "page_age": "466 days ago",
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    {
      "url": "https://yespress.io/deep-cogito",
      "type": "web_search_result",
      "title": "Deep Cogito: The Open-Source Lab Teaching AI to Learn From Itself",
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    },
    {
      "url": "https://www.deepcogito.com/research/cogito-v1-preview",
      "type": "web_search_result",
      "title": "Introducing Cogito v1 Preview",
      "page_age": "582 days ago",
      "encrypted_content": "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"
    },
    {
      "url": "https://www.deepcogito.com/research/cogito-v2-preview",
      "type": "web_search_result",
      "title": "Introducing Cogito v2 Preview",
      "page_age": "468 days ago",
      "encrypted_content": "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"
    },
    {
      "url": "https://arxiv.org/pdf/2503.05705",
      "type": "web_search_result",
      "title": "Inference Scaling Reshapes AI Governance",
      "page_age": null,
      "encrypted_content": "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"
    }
  ],
  "tool_use_id": "srvtoolu_016XYvNZt6gQfkVTQuDomR36"
}

Calls web_search

{
  "query": "iterated amplification empirical demonstration real-world task"
}

web_search_tool_result

{
  "type": "web_search_tool_result",
  "caller": {
    "type": "code_execution_20260120",
    "tool_id": "srvtoolu_01P7nNxbmCLWzGWZozYSFPTd"
  },
  "content": [
    {
      "url": "https://www.alphaxiv.org/abs/2109.10862",
      "type": "web_search_result",
      "title": "Recursively Summarizing Books with Human Feedback",
      "page_age": "1871 days ago",
      "encrypted_content": "Eq4NCioIFRgCIiRhOGFlOWMyMy1iYWVmLTRiYzctOWJjYS04YTM3MTE5YWVhMGMSDOJMzofORYOqc+eWLxoMpbvRU/sJUcZgPQYTIjChOQ7exQj2JCiTrNEvrBEy00YH9mBO5l2nCKQgE0j5llw2LhcuXxACECVVcFGuINsqsQx8U443VMEW1mioLzl36zxRGGk0zrUeb4o22ERzPcAKH/NZLF6gsBkVLjlwr06LJ+I3zQBIuw4sHhH2cCYRAAkWEjCkJq3h6ZRsfWITYRyDA1vbeXFymcEfKiHKACuvAyHsZNd6DlERCOeHwGYEeRvD0fbl9T0XdSefTQ6iJWnBej3E5mn06ISFF+MQFr20gNYV4IFirngmVSrjm0BhyDHr5zeYZxGZ8vHF6BqEgNHTLjbLw/zpcCYbI4wCBr2N16+zZb3dXjoeJMKjK3VaP+NDUGw89D5dw6FZCd/q5SAANyOSjYuyACAqk87U2xgvsNnTEKHnA52GXB8FBFOrKIDs0g5p9veXmU27uLmok3Nld/gSnCwVVHRA9bV2PQDhB37KpBsM8Ao0H1v3X+G2KuIQ3m+NHUrFI4zmDw9drfhrorZlycNh3ntiw3eqXjvOTNVuJXIWVf/lX+h6o1RRjGQ4g612/cxBSiFC2A3jl1pvQbE4LhkK0nEB7er77H/mhNSh4BR1Og5cotOEBnq4OE5eKzsYjSdKjVW2k1JJke56yOc23GSTJmPSe6hDzfvc49xZ84DoWTUvI02W7SmlajZCp0LailaMzAd19rkf5PmqCwfcGgEKtaD531iRXq8BCcy6lgNQd9AKGZx8Muu7EQi66Cz60TY0lss9r6fHH8GkdAOIwQBOVyKgpQq+WAoUS/28J/JXo5slaiL7ZWlZMl75dNsrkuDLnTiR5d8z7NvbJrefJUCUQfh6rhNhfmnFQdWK5hnu2AlpZBMCOqygXz5KCqAecCcv63MZcL9uEkzjlzgGVmOuRhlVQZzCVN1QMBJn8aAAfgxtk8HPMG6gRDrvno0xHj3CY1W39HTivMw5gBEm60EFwf7ukcL2UtEWP2SZ/bwTh8dd6+p+dYlLeX+2XSJBfx0PqX7CWos9fSI3eppO4Evqrqk47GTNFIcyFAfS94s521GO2HRxd/30pIbxp6j1tYU71XrM7LuaknGfEYAJ5Az0YIi1gH8fMjfYNpkNnRgI8VOkJNLLv2XUuY92D4BgxmvstXtNhhMVee6bUvkxn7m4zC3tlX61FTHA0ovJHBH8uL0LMiYeg6vwoIyFL0pocphtY+ppCOxtb0D6J7CYJssg9fH2gIwcnG5id5JPZfHKHG+FDnbpQNx4TbbCAVVgmJKpByEMiTwzaYE82eTy83hpPYdhp1s2f/VlAKO9IWIHO63YNLTpIjZ/mlGmACdshLxGO+oQ49u3T/q1HR1Wr3Umtipq6/7vEiPfMKPK7PG8Ytss31vFqyz2atuZGGYdv3X4MxG30Jb3knQsXKqvdQOTQPG0ViDuIxZbpUe0/84qCZaJt9zIKtyeDbjGQWsnZpE4/rJA+31LrQ5/UOTbRFYlnR5tP2RtH5QtYIjHf3MHR64cug0ZxxP/ORQvFOci2VpI35bQGLs0lY2CjeuFCddTv+pRmEyZIMpdSY4rG6LT2VAn4vLVgOkqt9Bwty8Vshb04RuD7ZxdVSQqZhvgm+TqoBRgHCbzCPn6EmhhyvhAJy45AdPN+hlc8Iqxx1czIksUVpR/qhi15Yw6Ddjf5n/5c15QSoorlGUxMzTof5+qPjdv/U/g4vbiSvd3PsiUgEBQ7IiRV6IKUO5BHzBkLiBoFVd1R7V4ofpIwaRFDPLg29TEC0mhZxrf0Wx9gfgd84JXuHx6ziTtk/Kufrsbz/T33fSMUadeLlpqjWy0/BITNnX12dlfzKI9L1xHsLiYToPU25fg+EnnYojAqEFgImLpDnGVU3pqL4qTLIZrLWbhuUqaNGHhDa+IHIGCAhquZ/rUTQR4/rZhpu8syg23oieUpLLAhRZ5uT3/G9iFYiQEO6aI9RuRTnfKjYkesXi1jfzsGDD3BSXoSKN/SDKdC5C0CkCPKo7k19SLdNaZ8ld8oxPUIkonAW980NVBV9GxUQdKAJlM76ccaHfdv/k+F5h8XT6dAX1VNEchirTLlJeCpMOcCyC79oJOML5sVIEiwFu88zDKd0TXYNkWwgnD6mJfkHbI4eAz2gPpiMIZ5xWASvverLCOoAH6dfaFsAzCLIqTYeRn9+4ZiGYnn9ZWflYy4dVrFL0aPzC0EqYsGAM="
    },
    {
      "url": "https://blog.openai.com/amplifying-ai-training/",
      "type": "web_search_result",
      "title": "Learning Complex Goals with Iterated Amplification",
      "page_age": "2941 days ago",
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    },
    {
      "url": "https://openai.com/index/learning-complex-goals-with-iterated-amplification/",
      "type": "web_search_result",
      "title": "Learning complex goals with iterated amplification",
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    },
    {
      "url": "https://www.alphaxiv.org/abs/2404.04286",
      "type": "web_search_result",
      "title": "Bias Amplification in Language Model Evolution: An Iterated Learning Perspective",
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    {
      "url": "https://ar5iv.labs.arxiv.org/html/1810.08575",
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    {
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      "type": "web_search_result",
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    "return_code": 0,
    "encrypted_stdout": "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"
  },
  "tool_use_id": "srvtoolu_01P7nNxbmCLWzGWZozYSFPTd"
}

thinking

Calls read_page

{
  "url": "https://openai.com/index/learning-complex-goals-with-iterated-amplification/",
  "max_chars": 6000
}