Recent submissions

Comment · 1 month ago
ayy cool! i spoke to you at yc sus this year :)
Comment · 2 months ago
this is pretty cool! it feels very good for getting a brief summary/overview of something and getting a beginner's level grasp.
Comment · 2 months ago
this is rich coming from the company that shreds books for training data
Comment · 2 months ago
will nixpkgs still get updates? how will maintenance work (i am not familiar at all with the nix ecosystem so maybe this is a dumb q)
Comment · 5 months ago
It is a little ironic that this article reads so much like an AI-generated one.
Comment · 6 months ago
Comment · 6 months ago
we've reached another level of dopamine-hit chasing....
Comment · 6 months ago
I'm fine with it seeing as I can use my student email and get free usage
Comment · 6 months ago
While I can see this being a very useful skill for many, we must also remember sometimes reading slow is desired, especially when a deep understanding and analysis of a text is required (e.g reading and analysing literature)
Comment · 6 months ago
not too great, i submitted a photo taken of me at graduation. it got the location totally wrong and was around 50%-70% accurate on my hobbies and interests. it was able to correctly guess my sexuality and ethnicity, which is rather unsurprising.
Comment · 7 months ago
> MegaTrain stores parameters and optimizer states in host memory (CPU memory) and treats GPUs as transient compute engines. For each layer, we stream parameters in and compute gradients out, minimizing persistent device state

This is pretty awesome. The only compute I have at home is an RTX 3080 with 10 GB of VRAM, so I struggle with training larger models (>40M, 50M params). I get OOM errors and have to optimize a lot.

I have a lot more CPU RAM in my PC, and this would likely increase the size of models I can train locally.

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