onyx-zero-software t1_iv57n5r wrote on November 5, 2022 at 12:06 PM

Reply to [D] NVIDIA RTX 4090 vs RTX 3090 Deep Learning Benchmarks by mippie_moe

> In summary, the GeForce RTX 4090 is a great card for deep learning, particularly for budget-conscious creators, students, and researchers.

Lol what?

onyx-zero-software t1_iv0bgza wrote on November 4, 2022 at 10:14 AM

Reply to comment by PassionatePossum in [D] What are the major general advances in techniques? by windoze

Agreed

onyx-zero-software t1_ir839jv wrote on October 6, 2022 at 12:51 AM

Reply to comment by suflaj in Time Complexity of Detach() in torch "[R]" by mishtimoi

Copy is always O(n) unless you've got a tensor of N items operating with N threads and N ports to the memory you're copying.

onyx-zero-software t1_iqowjnc wrote on October 2, 2022 at 12:35 AM

Reply to [D] New Laptop for Deep Learning/ Machine Learning by MyActualUserName99

I ended up getting an Asus Zephyrus G15 with a Ryzen 9, 32GB Ram and a 3080 mobile. It's been just fine for getting baseline numbers and being able to run most things for debugging purposes. You wouldn't want to run long training sessions on any laptop as the other comments say, but when I bought mine it was ~$2k. It's absolutely not worth spending more than that for a machine that is going to be limited to approximately the same performance that lower-priced laptops will have because of thermals. Don't buy the $5k system (or frankly the $3k system either). Way overpriced and the extra $ won't buy you any performance or productivity over much cheaper systems. It's all flash and marketing.