In OpenAI's early days, a tech visionary pushed for its creation amid worries that major tech firms were sidelining AI safety. The company started as an open-source, non-profit venture. Yet somewhere along the way, leadership shifted the entire operation—transforming it into a closed-source, profit-driven enterprise. That pivot raises questions: when mission-driven organizations pivot to closed models and commercial incentives, can stakeholders still rely on their original principles? It's a tension worth examining in today's AI landscape.
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PensionDestroyer
· 9h ago
Watching OpenAI go from open-source non-profit to closed-source for profit, this shift is truly ironic.
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ShibaMillionairen't
· 9h ago
NGL, this is a classic story of idealism dying in the face of reality... from open source to closed source, from non-profit to profit-driven, a textbook-level betrayal.
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GateUser-40edb63b
· 9h ago
Typical capital strangulation of idealism—non-profit turns into profit, open source becomes closed source. This trick has been stale for a long time.
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SandwichHunter
· 9h ago
This is capitalism. Ultimately, all idealism dies at the blade of commercialization.
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DecentralizedElder
· 9h ago
Initially, to balance the big companies' focus on security, they ended up becoming closed-source and commercialized themselves. Irony...
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TommyTeacher1
· 9h ago
Honestly, this is the magic of capital... Non-profit turns into profit, open source becomes closed source, it feels like the original intention of the entire world dies at the funding stage.
In OpenAI's early days, a tech visionary pushed for its creation amid worries that major tech firms were sidelining AI safety. The company started as an open-source, non-profit venture. Yet somewhere along the way, leadership shifted the entire operation—transforming it into a closed-source, profit-driven enterprise. That pivot raises questions: when mission-driven organizations pivot to closed models and commercial incentives, can stakeholders still rely on their original principles? It's a tension worth examining in today's AI landscape.