matrix2596

6 ms·

1.
by matrix2596 8d ago
search, verifiability and compute
2.
by matrix2596 17d ago
have u seen the dspark paper, they add a morkov head for light weight dependency, not sure whether it can be extended to multi step refining
3.
by matrix2596 6mo ago
looks like flash attention concepts applied to kmeans, nice speedup results
4.
by matrix2596 7mo ago
Gemini 3.1 Pro is based on Gemini 3 Pro
5.
by matrix2596 10mo ago
yea, they "officially" dont release benchmarks even if we asked the AWS reps
6.
by matrix2596 1y ago
awesome that sparse attention used in real world setting
7.
by matrix2596 1y ago
well said, just numbers with no plan or investment is worse even
8.
by matrix2596 1y ago
people dont realize how lucky US citizens have it just by luck of being born in US
9.
by matrix2596 1y ago
I wonder why India has not had the same success when its in a similar situation, is the domecratic power worse than the authoritarianism ( at least in the case of China). Or would you say India will eventually catch up and be better for the
10.
by matrix2596 1y ago
is is possible for your tokenizer to give different tokenization ever then openai tokenizer? i am asking because there are multiple ways to tokenize the same string?? sry if i am mistaken
11.
by matrix2596 1y ago
yes
12.
by matrix2596 1y ago
Really interesting to see the deep dive into PCB design and EMI considerations here. It's a great reminder how much thought goes into balancing cost, manufacturability, and compliance, even for hobbyist products. The point about using
13.
by matrix2596 1y ago
Best of luck.
14.
by matrix2596 1y ago
poring over it or pouring your attention :)
15.
by matrix2596 2y ago
what can people outside US and china do?
16.
by matrix2596 2y ago
i understand polar expeditions, but werent people already living in amazon
17.
by matrix2596 2y ago
Yes. I am Telugu and family name is usually not written or called out. So he would usually write D. Gukesh or Gukesh D. Most people also have a sort of middle name for example D. Gukesh Kumar. Middle name is spelled and used for calling tog
18.
by matrix2596 2y ago
seems more like a survey paper combining existing methods. But nice to read up.
19.
by matrix2596 2y ago
thanks
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by matrix2596 2y ago
Is there an easy way to separate the fantasy from science fiction books in the awards list? I would like to read books which are more science fiction than fantasy.
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by matrix2596 2y ago
they should call it barely plastic :)
22.
by matrix2596 2y ago
wouldnt presenting numbers in reverse order, with the least significant digit on the left and most significant on the right help with the reasoning?
23.
by matrix2596 2y ago
I also wondered the same and check the model configs. they are using bigger vocab size and the intermediate size of fully connected layer seems to be bigger.
24.
by matrix2596 2y ago
archive link plz
25.
by matrix2596 2y ago
I'm building upon insights from this paper ( https://arxiv.org/pdf/2403.03950.pdf ) and believe that classification can sometimes outperform regression, even when dealing with continuous output values. This is parti
26.
by matrix2596 3y ago
I would like these APIs to have prepaid options. Then you can control your max budget. Even OPENAI doesnt have that option.
27.
by matrix2596 3y ago
its funny but the large language models can be seen as billions of if statements learnt from data
28.
by matrix2596 3y ago
thats great news. I was using arxiv vanity to read on mobile phones. I am not seeing it on all articles, is it only for new papers?
29.
by matrix2596 3y ago
that actually makes sense. thanks.
30.
by matrix2596 3y ago
the model says 8x7B model, so its a 56B model. what is the GPU memory requirements to run this model for a 512 context size? are there any feasible quantization models of this available? I want to know if my 16GB VRAM GPU can run this model

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