ajb117

4 ms·

1.
by ajb117 11mo ago
Holy marketing
2.
by ajb117 2y ago
I get what you're saying, but I think confidence is actually more important than enjoyment. A lot of people confuse enjoying [x] with enjoying being good at [x]. This is why so many students switch subjects later on in life; when a fie
3.
by ajb117 3y ago
I'm curious about the AI research job market in fields that aren't LLMs and RL. They're all the rage now, but what about researchers in fields like vision or graphs or more fundamental topics like optimization?
4.
by ajb117 3y ago
Besides the the title being a bit exaggerated, it's been long-acknowledged in the GNN community that graph rewiring often helps learning; see [1, 2] for example. Also, at first skim, I'm surprised there's no discussion on ove
5.
by ajb117 3y ago
I don't know much physics, but is there a reason we should be hoping for superconductivity specifically rather than a cheap material that's just a very very good conductor? Also, even if LK-99 were superconductive, that wouldn&#x2
6.
by ajb117 3y ago
Makes me wish python had a pipe operator like Julia's |> and R's %>%
7.
by ajb117 3y ago
Besides Nvidia cards usually being faster and having higher memory bandwidth, Ada cards also have FP8 cores. I'm not sure how well Apples' M-series chips handle low/mixed precision tensors, but I wouldn't be surprised if
8.
by ajb117 3y ago
Well at least in the U.S. a lot of used 3090s are out for less than $800 on eBay which is a steal for 24GB VRAM. The 4090 is about $1600 and it's still a consumer-level card; gamers are buying it more often than the 4080. For ML worklo
9.
by ajb117 3y ago
I'm pretty sure you can't buy TPUs, but people usually buy GPUs instead. If you're building a personal rig, these days, you can get an Nvidia RTX 3090 for about $720 USD on ebay used, which is pretty cheap for 24GB VRAM. Ther
10.
by ajb117 3y ago
I think that's more in line with transfer learning, a variant of fine-tuning. If I'm reading this article correctly, they're fine-tuning the LMs end-to-end.
11.
by ajb117 3y ago
My guess is that it's because they've already done RLHF on top of the standard next token prediction. In other words, they can't cheaply fine tune ChatGPT without undoing the RLHF objective by training on next token predictio
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by ajb117 3y ago
I honestly don't know how people can stand Gnome/Unity. I've been running Xubuntu LTS with the Plank dock and have had nothing but smooth sailing save Nvidia drivers.