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Andrej Karpathy

@andrej-karpathy · 15 positions · 0 changes of mind

Founding member of OpenAI and former director of AI at Tesla; creator of nanoGPT and the term "vibe coding".

Andrej Karpathy did not write this page. We collected these quotes from things they published elsewhere, and every quote links to where it was said. They have no account here and have not endorsed this site. Quotes are word for word; the short line under each one is our own restatement, not their wording. Their own site. Is this you? Claim it or ask us to remove it.

  1. 9 Apr 2026

    People disagreeing about AI capability are speaking past each other, because they are using models of very different tiers on very different kinds of task.

    TLDR the people in these two groups are speaking past each other.

    @karpathy on Xx.com

  2. 5 days earlier
  3. 4 Apr 2026

    AI will let citizens make their governments legible and accountable, reversing the historical direction in which only states could read society.

    Something I've been thinking about - I am bullish on people (empowered by AI) increasing the visibility, legibility and accountability of their governments.

    @karpathy on Xx.com

  4. 7 days earlier
  5. 28 Mar 2026

    Because an LLM can argue almost any direction competently, the right way to use one for forming an opinion is to make it argue every side.

    The LLMs may elicit an opinion when asked but are extremely competent in arguing almost any direction. This is actually super useful as a tool for forming your own opinions, just make sure to ask different directions and be careful with the sycophancy.

    @karpathy on Xx.com

    LLMs

  6. 3 days earlier
  7. 25 Mar 2026

    LLM memory as currently built is a distraction to the model: one old question keeps resurfacing as if it were a lasting interest.

    One common issue with personalization in all LLMs is how distracting memory seems to be for the models. A single question from 2 months ago about some topic can keep coming up as some kind of a deep interest of mine with undue mentions in perpetuity.

    @karpathy on Xx.com

    LLMs

  8. 2 weeks earlier
  9. 11 Mar 2026

    The age of the IDE is not over; agents make it bigger, because humans now program at a higher level where the unit of interest is an agent rather than a file.

    Expectation: the age of the IDE is over Reality: we’re going to need a bigger IDE (imo). It just looks very different because humans now move upwards and program at a higher level - the basic unit of interest is not one file but one agent. It’s still programming.

    @karpathy on Xx.com

  10. 11 Mar 2026

    Agentic organisations will be forkable in a way that classical companies never were.

    You can’t fork classical orgs (eg Microsoft) but you’ll be able to fork agentic orgs.

    @karpathy on Xx.com

  11. 11 Mar 2026

    Outages at the frontier AI labs will become "intelligence brownouts" — the planet losing IQ points when the models stutter.

    Intelligence brownouts will be interesting - the planet losing IQ points when frontier AI stutters.

    @karpathy on Xx.com

  12. 4 weeks earlier
  13. 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.

    microgptkarpathy.github.io

  14. 3 months earlier
  15. 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.

    Verifiabilitykarpathy.bearblog.dev

  16. 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.

    Verifiabilitykarpathy.bearblog.dev

  17. 1 day earlier
  18. 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.

    @karpathy on Xx.com

  19. 7 weeks earlier
  20. 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.

    @karpathy on Xx.com

  21. 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.

    @karpathy on Xx.com

    AI and jobs

  22. 6 months earlier
  23. 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

    LLMs

  24. 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