The time limits seem pretty generous

Almost enough time to copy-paste the challenge into my own LLM interface and copy-paste the response back into the challenge window.

Or just some random online tool. I could easily pass the test multiple times with half the time left.

Almost

That is my understanding as well, so the title is misleading at best

> DeepSeek is going to go buy 20,000 fake IDs for their fake distillation accounts

I'm rooting for China here, feels strange but well

> As a non-US citizen

...

> My next step is exploring OpenRouter and other models

May I suggest using Cortecs.ai then? OpenRouter is US-based as well and since you have been bitten by this already perhaps it's really time to change course? :)

Thanks for the suggestion, I am looking into it, it looks promising and I like that the pricing model is very upfront

That's pure comedy

Since it was created by _Open_AI surely it's really open and we can check, right? SCNR

"Without AI" is the new "Written in Rust", SCNR

'Have you considered rewriting it without AI' seems like something I could see myself saying.

But it also shows the number of removed reviews (in a range like 0-50, 50-100 and so forth). If you encounter a restaurant with 5 starts but a lot of removed reviews you know whats up.

That's a fairly new workaround that took Google years to come up with.

What is the problem with using a middleman with XMR?

So can VRAM actually be used like regular RAM? E.g. if I have a 16GB module and my GPU has 16GB VRAM, could it be made so that my system reports 32GB RAM? What would be the implications of that?

It behaves like slower ram I assume, due to the increased distance from the CPU and overhead. Still, it’s much faster than normal SWAP which uses a disk or SSD.

How it is reported? As SWAP space, not as RAM.

Typical desktop GPU ram does not support being write-back cached by the CPU. With PCIe resizable BAR, you could map the area into ram, so you could technically fit 32GB to memory, but it would have to be uncached (or write-combine cached), which would make it really, really slow.

There are a bunch of datacenter GPUs that support full cache coherency, but if you used them like that the VRAM would be very high latency from the CPU. So it would only be really slow.

Isn't the problem with write back cache mode just due to the GPU being unable to invalidate cache lines in the CPU?

I assume on Linux you could use something like daxctl to tell the kernel to treat the vRAM as normal RAM, but I think this would be Intel/AMD only.

I don't think it would help. It's not just a software issue that can be fixed in the kernel, the hardware fundamentally isn't part of the cache coherency system of the CPU.

This is correct, look at IBM's CAPI for an example of the needed hardware