I finished my Ph.D. a year ago. Left academia and went to be a data scientist at a tech company. I like it, but still thinking about moving to a more research position somehow in the future. Not sure though. Anyway, an unfinished work of mine got picked by a friend which finished it and applied to ICML. It got accepted (yay!). I now wonder - beside...

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Long story short, a company has a budget for buying GPUs expected to fine-tune LLMs(probably 70B ones), and I have to the research to find which GPU setup is the best with respect to their budget. The budget can buy three H100 GPUs or five A100 GPUs. I tried my best but until now is not clear to me which of these setups is better. While five A100s...

I have some papers in top venus myself, but whenever I sit down and be brutually honest with myself. I feel my work is good but it is just not that impactful, like one more brick in the wall. I wonder how often we can see something as impactful as "Attention is all you need" for example. submitted by /u/oddhvdfscuyg [link] [comments]

Evidentially there’s an automated component to every level of understanding… Analgoue training: Read a little about fpgas and Fourier analysis generalization of computation… leading to real-time learning signal on chip… then the concept of better than real time time coded resynthesis… further after learning scratch is pretty fast and remembering max...

Please share your journey and lessons. Thanks! submitted by /u/20231027 [link] [comments]