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ngiyabonga

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Just pasted the whole thing into the system prompt for Qwen 3 30B-A3B. It then:

- responded very thoroughly about Tianmen square

- ditto about Uyghur genocide

- “knows” DJT is the sitting president of the US and when he was inaugurated

- thinks it’s Claude (Qwen knows it’s Qwen without a system prompt)

So it does seem to work in steering behavior (makes Qwen’s censorship go away, changes its identity / self, “adds” knowledge).

Pretty cool for steering the ghost in the machine!

Hi Andrej!

First, thank you for your teaching, it has helped me a lot, didn't think I'd ever have the chance to say thank you, but here you are and I hope this gets to you!

Question - what's a relevant (05-2024) baseline to compare the performance of c code to? Back when you made nanoGPT you were seeing "the file train.py reproduces GPT-2 (124M) on OpenWebText, running on a single 8XA100 40GB node in about 4 days of training". So twice the memory on the c node, but unsure of data size /epochs, any other details I may be missing. I.e. what's the net uplift of running c vs "legacy" torch code?

Thanks again for everything.

Pairing With GPT-4 3 years ago

This is my experience as well, and not just for coding, but quite a few "knowledge-worker" type tasks I've been experimenting with: summarisation, translation, copywriting, idea generation to name a few.

GPT really shines as an uncomplaining sidekick and I'm not sure I believe the doom and gloom about comoditizing professions yet.

I'm skeptical someone with no domain knowledge can use any of these emerging AI tools to replace someone with domain knowledge + chatGPT. The latter will just breeze through a lot of grunt work and enable more time and inspiration needed for even more value adding work.

I find these two concepts [1, 2] at odds with each other. Not a critique on the author - on the contrary, empathy: I felt the same when applying to YC (did not make a batch).

On one hand, the general impression you get when preparing for your application (via FAQs, Startup School, YC videos, etc) is very much in line with [1] - YC is looking for _very_ early stage.

But once you go through the actual application you feel focus shift towards [2] - metrics and $. That is to say (with admittedly some not-having-been-selected bias), I feel [2] is a significant factor in deciding on applications. So as I weigh in on whether to apply for the next batch, I'm not sure whether a product I've just finished building makes sense for YC and whether I should gamble on attempt #3.

I think it would help both YC and founders if they take some steps to make this clear(er) for potential applicants.

[1] > In general, there is an evident focus on the very early stage without a product. The main theory and advice are about how to figure out what to do, how to build an MVP, how to launch, how to talk to customers, where to find the first 10 customers, how to raise the first money, and so on. Needless to say, for companies with tens or even hundreds of thousands in revenue it won’t be very valuable.

[2] > [...] present dry facts—how much money customers already paid you, what the size of the market, if you count all the units you can sell, what you have actually built and what is working today. And this will always sound bad for anyone, it just can't sound good in the early days.

Thank you. You got me down quite the rabbit hole. Exploring having a server I control act as Wireguard server and have a VPS act as a client to proxy requests from the outside world inside the tunnel on NGinx machine(s). Been reading into subresource integrity in the browser as well, that seems like it may prevent tampering at another level as well (ISP?). Again, thank you.