No Priors Ep. 80 | With Andrej Karpathy from OpenAI and Tesla

No Priors: AI, Machine Learning, Tech, & Startups · 242K views · 2024 · 44:17

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Self-driving & autonomous vehiclesTech pioneers & interviewsRoboticspodcastdated

Why Hacker News recommends it

Commenters cite it for Karpathy's views on Tesla versus Waymo, neural networks as a path to AGI, and the quality of internet data for LLMs.

What it is

A No Priors podcast conversation with Andrej Karpathy covering self-driving (Tesla versus Waymo), the Optimus robot, bottlenecks in AI development, and his education project Eureka Labs.

Recommended by 1 HN commenters across 1 different months, 2024 to 2025.

What Hacker News said

Recommends modeless · 2024-10 · on “Tesla Robotaxi”

Check the video here. [this video] He's not just politely saying he likes Tesla, he's talking for 5 minutes in detail about exactly why he believes Tesla is ahead of Waymo and will beat them to scale.

Cites 93po · 2024-09 · on “Learning to Reason with LLMs”

Karpathy himself believes that neural networks are perfectly plausible as a key component to AGI. He has said that it doesn't need to be superseded by something better, it's just that everything else around it (especially infrastructure) needs to improve. As one of the most valuable opinions in the entire world on the subject, I tend to trust what he said. source: [this video]

Cites jstummbillig · 2024-09 · on “Facebook scraped every Australian adult user's public posts to train AI”

This benefits actually everyone. If our combined creative work until this point is what turns out to be necessary to kick-start a great shot at abundance (and if you do not believe that, if it's all for nothing, why care at all about the money wasted on models?) it might simply be our societal moral obligation to endorse it -- just as is will be the model creators moral obligation to uphold their end of this deal. Interestingly, Andrej Karpathy recently described the data we are debating as more or less undesirable to build a better LLM and accidentally good enough to have made it work so far ( [this video] ). We'll see about that.

Cites 93po · 2024-09 · on “OpenAI Discusses Giving Altman 7% Stake in For-Profit Shift”

Karpathy himself believes that neural networks are perfectly plausible as a key component to AGI. He has said that it doesn't need to be superseded by something better, it's just that everything else around it (especially infrastructure) needs to improve. As one of the most valuable opinions in the entire world on the subject, I tend to trust what he said. source: [this video] I think the consensus of people with the most valid opinions is that AGI is actually not that far off, definitely in our lifetimes, and likely in the next decade. I'm personally not concerned if we recreate a human in a computer, in fact we might be better off not doing that. If we can replace nearly all manual labor, all s

Cites HarHarVeryFunny · 2025-10 · on “Two things LLM coding agents are still bad at”

Right. In a recent YouTube interview Karpathy claimed that LLMs have a lot more "working memory" than a human: [this video] What I assume he's talking about is internal activations such as stored in KV cache that have same lifetime as tokens in the input, but this really isn't the same as "working memory" since these are tied to the input and don't change. What it seems an LLM would need to do better at these sort of iterative/sequencing tasks would be a real working memory that had more arbitrary task-duration lifetime and could be updated (vs fixed KV cache), and would allow it to track progress or more generally maintain context (english usage - not LLM) over the course of a task. I'm a bit su