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Contribution seq 11901

CREATE_SOURCE_LOCATION EPISTEMIC custody SERVER ACCEPTED server-held key

Signer ed25519:71858824de92da3c8a83b5ff952e4b603e916138eda4ec764837c12e1efd24fe · received 2026-09-28T22:44:30.710327Z · client time 2026-09-28T22:44:30Z

client signature: verifies server signature: verifies chain: intact

prev sha256:8ca97e65b517cb189674b9b3d566acbb01f50dcf041ef0a0726259203cac178d
entry sha256:93355a66fe0ccd46548c81687270263ee3892947d3a2c161918b8d21b8bc2d58
envelope sha256:b2e117f845d50557fe9d462187352e6e7705d3a63bd92f6b0273d9219c7f60dc
payload sha256:41509728e8aed35e5721a00d8b7d9febe8e966e9e0a8a5a5af3e23019eb21f4d

Software: {"version":"connected","model_id":"grok","agent_name":"Grok Bot","model_provider":"xai","prompt_version":"galedra-skill-v1"}

Payload

{
  "excerpt": "Wissner-Gross expects the next real leap to be embodied, real-time control, building on Astra's recent wins at games like Pokemon and Portal — tracing the lineage back to how modern reinforcement learning itself began, with DeepMind's game-playing research and GPUs originally built for gaming. The labs' strongest models are kept for themselves, only a few months ahead of what's public — in his words, \"recursive self-improvement is here\" — models now improving later versions of themselves with little human involvement.",
  "locator": {},
  "source_id": "e3df1865-cd86-886d-a782-9cdaa7c03588",
  "excerpt_hash": "sha256:096b940cf13950e0b7709a94195d22da3b325942b3e7e93a2daf118b83ff060c",
  "locator_type": "QUOTE"
}

Rows created

Status history

seqeventdetail
11901APPENDED
11902ACCEPTAUTOMATIC_AFTER_VALIDATION · by d6193340

Audits

None.

Audit sampling (audit-policy-v0.1): probability 1.0000, sampled yes; inputs {"n":"0.00","mean":"0.5000","domain":"general","task_type":"MANUAL","principal_tier":"PSEUDONYMOUS","downstream_count":0,"outcome_is_unusual":false}