@AntithesisHQ – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages. https://t.co/AKYm4cbVCU
@AntithesisHQ – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages. https://t.co/AKYm4cbVCU
There is something powerful and strange about how LLMs diffuse knowledge and capabilities, while perhaps also nudging us all simultaniously and independently toward building the same things.
LLMs constantly hallucinate and cannot be trusted. I still have to verify and iterate a lot but now I usually focus on architecture and design instead of code style.
And so basically everything that we can verify reasonably well with some feedback loop, the AIS are doing pretty well on. And that's sufficient to make AR and D go quite fast and to continue. But there's some parts of of developing uh aligned and safe AIs that are more subtle, hard to check, depend on, you know, detailed in the weeds things.
I think the skill nowadays is less about prompt engineering and more about figuring out how do you give Claude a hard task that seems a little bit too hard. And then how do you make it possible for Claude to verify its work along the way? And the verification I think is probably the single most important thing that people do not get right
You don't need slash goal, you don't need slash loop. These help, but really all you need is give the model the task, give it a way to verify the output of its work so it doesn't get stuck, and it will just go.
I came to the same conclusions independently before I encountered Krashen's work, and decades of learning across 20+ languages have only reinforced them. The research supports the intuition: input is where acquisition happens.
Yeah, what what's the smallest experiment I can run to verify to my own satisfaction and everybody's level of satisfaction is going to be different whether or not this claim is true. That's That's the skill that is suddenly in the last year become a thousand times more valuable is that skill of saying, "What's the least I can do to validate for my to my own satisfaction whether this claim is true?
So, we're now in a situation where suddenly people can generate thousands of theories for a given scientific problem. And now we have to to verify them, evaluate them and this is something which we we have to to change our structures of science to actually sort this out.
My one little bit, the one little bit of of fundamental uncertainty even on long time scales is this thing about tasks that aren't verifiable. Like, planning a mission to Mars, like, uh you know, doing some fundamental scientific discovery like like CRISPR, like, you know, writing a writing a novel. Hard to hard to verify those tasks.
You need reproducible builds in order to verify that the app really does what it claims, really encrypts data in a way that it is described on its website. For that you need to make your apps open source for any researchers to have a look at it.
Don’t base your life choices on whether parents and teachers constantly tell you that you’re “smart.” They’re not trustworthy assessors of your intelligence.
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