I get that, motivating young founders is difficult, and I think he has a charming geeky way of provoking some thoughts. But on the other hand: Why mainframes with time-sharing from the 60s? Why operating systems? LLMs to tell you how to boil an egg, seriously?
Putting my engineering hat on, I understand his idea of the "autonomy slider" as lazy workaround for a software implementation that deals with one system boundary. He should aspire people there to seek out for unknown boundaries, not provide implementation details to existing boundaries. His MenuGen app would probably be better off using a web image search instead of LLM image generation. Enhancing deployment pipelines with LLM setups is something for the last generation of DevOps companies, not the next one.
Please mention just once the value proposition and responsibilities when handling large quantities of valuable data - LLMs wouldn't exist without them! What makes quality data for an LLM, or personal data?
This talk is different from his others because it's directed at aspiring startup founders. It's about how we conceptualize the place of an LLM in a new business. It's designed to provide a series of analogies any one of which which may or may not help a given startup founder to break out of the tired, binary talking points they've absorbed from the internet ("AI all the things" vs "AI is terrible") in favor of a more nuanced perspective of the role of AI in their plans. It's soft and squishy rhetoric because it's not about engineering, it's about business and strategy.
I honestly left impressed that Karpathy has the dynamic range necessary to speak to both engineers and business people, but it also makes sense that a lot of engineers would come out of this very confused at what he's on about.