๐Ÿฆ Twitter Post Details

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@karpathy

How to build a thriving open source community by writing code like bacteria do ๐Ÿฆ . Bacterial code (genomes) are: - small (each line of code costs energy) - modular (organized into groups of swappable operons) - self-contained (easily "copy paste-able" via horizontal geneโ€ฆ https://t.co/0xVX3NAMhC

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                                  "text": "I love this. A couple of notes/additions to your thoughts. \n1, this coding concept also allows for proper genetic reproduction of code (whether by humans or AI), which ties this paradigm into the GA branch of AIโ€”which is very cool. \n2, if we examine eukaryotic life, itโ€™s a combination of prokaryotes that specialized upon merger (energy production vs security, complex instructions, etc). Is there a way to create complex repos from simpler, more specialized blocks (which we do already) but in a way where even the complex repos are clearly built from the very simple LEGO blocks of this โ€˜prokaryoticโ€™ code? Likely yesโ€”and if so we can really hit a hockey stick in the curve of software development.",
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                              "full_text": "@karpathy Bacteria also lose junk DNA (nonfunctional stuff) as they evolve for genome efficiency in whatever environment theyโ€™re put in ๐Ÿ™‚always evolving ๐Ÿ‘Œ",
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                              "full_text": "@karpathy i really like this and found myself playing with someones RL gist the other day. it feels like something structural is missing though, do you think there should be a platform that makes it easier to mash these gists together ? maybe something like the original replits?",
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                                  "text": "Interesting analogy and thanks for sharing.\n\nI believe that a common adversary (game theory) is an often overlooked catalyst for open source cooperation among otherwise competitive actors. During the early months of the pandemic, nearly all COVID-19 research (97%)  became open access as publishers and institutions dropped paywalls to  accelerate innovation, recognizing that collective benefit outweighed  individual interests. \n\nSimilarly, in the recent open source AI wave, OpenAIโ€™s perceived dominance has united many contributors, making it a  common adversary that spurs collaboration. A common adversary is that what created Germany during the Franco-Prussian War. The victory led to the unification of Germany and the end of French dominance in continental Europe.\n\nDrawing on my experience leading open data initiatives in healthcare, Iโ€™ve seen how hard it is to turn a narrative into a movement against a common adversary. The industry remains locked in a โ€œgame of thrones,โ€  where business models treat data derivatives as exclusive assets,  driving up the cost of life-saving innovation by ten- to fiftyfold and creating artificial scarcity. \n\nI really appreciate your post drawing inspiration from bacterial code. However, without a clearly defined common adversary, fostering collaboration becomes much more challenging. \n\nDo you think the open  source AI ecosystem would have flourished as it has without the controversies surrounding OpenAIโ€™s complete lack of openness since GPT3 came out?",
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                              "full_text": "@karpathy Interesting analogy and thanks for sharing.\n\nI believe that a common adversary (game theory) is an often overlooked catalyst for open source cooperation among otherwise competitive actors. During the early months of the pandemic, nearly all COVID-19 research (97%)  became openโ€ฆ",
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