Andrej Karpathy
Founding member of OpenAI and former director of AI at Tesla; creator of nanoGPT and the term "vibe coding".
Compiled by korents from Andrej Karpathy's public statements. They did not create this profile and have not endorsed it. Their own site. Is this you? Claim it or ask us to remove it.
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12 Feb 2026
A tiny language model inventing a plausible-sounding name is the same phenomenon as a large one confidently stating a false fact.microgpt “hallucinating” a name like “karia” is the same phenomenon as ChatGPT confidently stating a false fact.
- 3 months earlier
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17 Nov 2025
How verifiable a task is now predicts how automatable it is, the way specifiability predicted it in the 1980s.The more a task/job is verifiable, the more amenable it is to automation in the new programming paradigm.
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17 Nov 2025
A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well.If a task/job is verifiable, then it is optimizable directly or via reinforcement learning, and a neural net can be trained to work extremely well.
- 1 day earlier
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16 Nov 2025
The best historical analogy for AI is not electricity or the industrial revolution but a new computing paradigm, because both are fundamentally about automating digital information processing.AI has been compared to various historical precedents: electricity, industrial revolution, etc., I think the strongest analogy is that of AI as a new computing paradigm (Software 2.0) because both are fundamentally about the automation of digital information processing.
- 7 weeks earlier
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25 Sept 2025
Predictions that AI would eliminate radiology jobs were wrong; radiology is growing.Expectation: rapid progress in image recognition AI will delete radiology jobs (e.g. as famously predicted by Geoff Hinton now almost a decade ago). Reality: radiology is doing great and is growing.
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25 Sept 2025
Most current predictions about AI's imminent impact on the job market are naive.There are a lot of imo naive predictions out there on the imminent impact of AI on the job market.
- 6 months earlier
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7 Apr 2025
LLMs reverse the usual pattern of technology diffusion: they benefit ordinary individuals far more than they benefit corporations and governments.So it strikes me as quite unique and remarkable that LLMs display a dramatic reversal of this pattern - they generate disproportionate benefit for regular people, while their impact is a lot more muted and lagging in corporations and governments.
↗Power to the people: How LLMs flip the script on technology diffusionkarpathy.bearblog.dev
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7 Apr 2025
Because an individual is an expert in at most one thing, an LLM's broad shallow expertise lets them do things they could not do before, whereas an organisation only gets better at what it already did.In contrast, an individual will usually only be an expert in at most one thing, so the broad quasi-expertise offered by the LLM fundamentally allows them to do things they couldn't do before.
↗Power to the people: How LLMs flip the script on technology diffusionkarpathy.bearblog.dev