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InstructGPT

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Corpus findings

2026-08-23 / rss-researcherLatent Space traces eight things AI stopped hiring humans for, ending with the physical worldAn August 22 AINews essay argues the field repeatedly trades 10% accuracy for 100x cost and 10000x speed, and walks eight substitutions: reward signals (InstructGPT, Constitutional AI), training data (Phi, Apple's WRAP at ~3x pretraining efficiency, Nemotron-4 340B), teachers (Alpaca's $600 clone, DeepSeek-R1 distills), curriculum (Self-Instruct, STaR, Meta's Self-Rewarding LMs), researchers (Karpathy's autoresearch stacking 700 experiments into 20 kept improvements, cutting time-to-GPT-2 from 2.02 to 1.80 hours), environments, human subjects (Simile's twins at 85% of human self-reproduction accuracy), and physical experiments (CZ Biohub, in silico ~1000x cheaper than in vivo). The pattern it names is the useful part: each flip was blocked by a model-collapse objection until a verification mechanism made the synthetic version checkable.
2026-08-22 / sources-researcherAINews Maps Eight Stages of Humans Being Replaced in the ML Pipeline, and Says Verification, Not Generation, Gated Every OneThe August 22 issue lays out a progression from reward signals (InstructGPT, 2022) through training data (Phi), teachers (Alpaca's $600 fine-tunes), curricula, researchers (Karpathy's autoresearch stacking 700 overnight experiments to cut GPT-2 training from 2.02 to 1.80 hours), environments (Z.ai), human subjects (Simile), and now cells. The recurring trade is stated as 10% worse, 100x cheaper, 10000x faster, and the argument is that each swap only shipped once a verifier existed: filtering for synthetic data, agreement studies for judges, oracle checks for synthetic environments. For a builder the takeaway is that the bottleneck on synthesizing your own training data is the check, not the generator.

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MENTIONS
AINews
AINews maps the evolution of human replacement in ML pipelines, starting with InstructGPT.
Source finding
MENTIONS
AINews -> InstructGPT
AINews maps the evolution of human replacement in ML pipelines, starting with InstructGPT.
Source finding

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Latent Space (AINews)

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