The Discovery Engine — Machine Traces of Discovery Paths — Architectural Implications Disclaimer — Discovery Trace Series. The Discovery Trace series is an experimental series of articles attempting the semi- or fully-automatic reconstruction of the paths to major discoveries. Multiple AI tools have been deployed to reconstruct each "Discovery Path."
A Comprehensive Analysis and Reconstruction Discovery Engine — Machine Traces of Discovery Paths, No. 3 Disclaimer — Discovery Trace Series. The Discovery Trace series is an experimental series of articles attempting the semi- or fully-automatic reconstruction of the paths to major discoveries. Multiple AI tools have been deployed to reconstruct each
Evidence for the Deep Dive essay Machine Traces of Discovery Paths #3 — The Path to CRISPR-Cas9 (Jennifer Doudna), A Comprehensive Analysis and Reconstruction. This Lab Notebook is the verifiable source record behind the #3 Deep Dive. It reconstructs, from the primary literature, the path that carried Jennifer Doudna from
Discovery Engine — Machine Traces of Discovery Paths — Architectural Implications Disclaimer — Discovery Trace Series. The Discovery Trace series is an experimental series of articles attempting the semi- or fully-automatic reconstruction of the paths to major discoveries. Multiple AI tools have been deployed to reconstruct each "Discovery Path." To
Machine Traces of Discovery Paths — Autonomous reconstructions of how landmark discoveries were reached, traced by AI from the primary literature. Disclaimer — Discovery Trace Series. The Discovery Trace series is an experimental series of articles attempting the semi- or fully-automatic reconstruction of the paths to major discoveries. Multiple AI tools
Evidence for the Deep Dive essay Machine Traces of Discovery Paths #2 — The Path to iPS Discovery, A Comprehensive Analysis and Reconstruction. This Lab Notebook is the verifiable source record behind the #2 Deep Dive. Where the essay states a claim, the support is here: the mechanism-level reconstruction of
Machine Traces of Discovery Paths — Autonomous reconstructions of how landmark discoveries were reached, traced by AI from the primary literature. Disclaimer — Discovery Trace Series. The Discovery Trace series is an experimental series of articles attempting the semi- or fully-automatic reconstruction of the paths to major discoveries. Multiple AI tools
The evidence behind the Deep Dive essay “Machine Traces of Discovery Paths #1 — The Path to iPS Discovery.” Four technical documents: the trace reconstruction, the methods-and-findings report, and — for the NAT1 (2000) hinge experiment — the structured protocol extraction and the tagged bench reconstruction. Each document is self-contained
Discovery Engine — Discovery to Decision · Part 1 Hiroaki Kitano Where discovery became decision. Two rooms, fifty miles apart At the end of February 2020 I was in London, chairing a workshop about whether a machine could discover. The three of us who convened it — Yolanda Gil, Ross King, and myself
Turing
Discovery Engine — Deep Dive · Turing Series, Part 2 Hiroaki Kitano The first machine built to cross a space too large for any human to cross — and it did it by pruning, not by brute force. The answer was built in steel I went to see one. Standing in front of
本シリーズの第一論考は、機械は発見できるかと問うた。その問いに答えるには、それに先立つ別の問いを正面から引き受けなければならない。すなわち、人間が主導する発見は、本当のところどれほどのものなのか。本稿は、現在の状況がどこで限界に達しているかを、人間の認知構造と社会構造という「構造」の問題として論じる。 1. 人間の発見が限界に達するところ 本シリーズの第一論考は、ある厳しい観察で締めくくられた。今日、生み出される知識の量は、どんな個人の知性も、どんな制度も追いつけないほど膨大になっている。また、人間の認知構造の限界、研究を行う社会的環境からの研究テーマの選択に関する影響などいろいろな問題が、人間による科学研究の限界の要因になっている。その帰結が構造的ミスアライメントである。これは個々の科学者の失敗ではなく、人間の発見というものが全体としてどう組織化されているかの不整合なのである。構造的ミスアライメントとは、人間の認知と行動の構造と、それが捉えようとしている自然の構造との、相互の食い違いを指す。一人の科学者が複雑な現実を丸ごと受け止めることはできない。その人が研究するものは、
Turing
Discovery Engine — Deep Dive · Turing Series, Part 1 Hiroaki Kitano Turing built the substrate of discovery fourteen years before he asked his famous question. Discovery Engine — Deep Dive · Turing Series, Part 1 Turing built the substrate of discovery fourteen years before he asked his famous question. Before the question, the