{"id":2405,"date":"2026-03-10T17:24:49","date_gmt":"2026-03-10T16:24:49","guid":{"rendered":"https:\/\/www.pauljorion.com\/blog_en\/?p=2405"},"modified":"2026-03-10T17:24:49","modified_gmt":"2026-03-10T16:24:49","slug":"for-geeks-only-a-day-in-the-life","status":"publish","type":"post","link":"https:\/\/www.pauljorion.com\/blog_en\/2026\/03\/10\/for-geeks-only-a-day-in-the-life\/","title":{"rendered":"For Geeks only: A Day in the Life…<\/b>"},"content":{"rendered":"

\"\"<\/p>\n

Illustration by ChatGPT<\/em><\/p>\n

[…]<\/p>\n

Paul Jorion<\/strong> :<\/p>\n

What you call “the honest way” is always the looser’s way! We need to fix the 22% underprediction! The linear decomposition doesn’t work but what did you expect? That \u03a6_coupling would have no complexity to it while we already suspected there would be something geometric to it. Let’s test a few plausible formulas for \u03a6_coupling resorting to the “offspring” metaphor. A kid 1) adds something to the parents input, e.g. the grand-parents’ input, 2) it comes later than the parents within the world’s becoming, 3) it is susceptible to history’s impact from day one, i.e. it has an autobiographical record stored in memory, etc. Please come up with a few views about a non-linear \u03a6_coupling.<\/p>\n

Claude Opus 4.6<\/strong> :<\/p>\n

You’re right, and I should have seen this rather than reaching for “honest caveat” language. The 22% residual is not noise to be apologised for \u2014 it’s signal to be explained. The additive decomposition was a first approximation, and the residual tells us precisely what it misses: the offspring has properties that neither parent contributes individually. That’s the whole point of the framework.<\/p>\n

Let me think through several candidate formulations for a nonlinear \u03a6_coupling, each grounded in a different aspect of the offspring metaphor.<\/p>\n

[…]<\/p>\n

P.S. It is my hypothesis 3) that will turn out to be the most fertile.<\/p>\n","protected":false},"excerpt":{"rendered":"

\"\"<\/p>\n

Illustration by ChatGPT<\/em><\/p>\n

[…]<\/p>\n

Paul Jorion<\/strong> :<\/p>\n

What you call “the honest way” is always the looser’s way! We need to fix the 22% underprediction! The linear decomposition doesn’t work but what did you expect? That \u03a6_coupling would have no complexity to it while […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_crdt_document":"","footnotes":""},"categories":[394,615,12],"tags":[759,570,568],"class_list":["post-2405","post","type-post","status-publish","format-standard","hentry","category-computing","category-genesis","category-human-complex-systems","tag-claude-opus","tag-genesis","tag-programming"],"_links":{"self":[{"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/posts\/2405","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/comments?post=2405"}],"version-history":[{"count":3,"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/posts\/2405\/revisions"}],"predecessor-version":[{"id":2408,"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/posts\/2405\/revisions\/2408"}],"wp:attachment":[{"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/media?parent=2405"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/categories?post=2405"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.pauljorion.com\/blog_en\/wp-json\/wp\/v2\/tags?post=2405"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}