0xkylerli pfp

0xkylerli

@0xkylerli

83 Following
10 Followers


WebHash.com pfp
WebHash.com
@webhash.eth
Join us for a Webhash Twitter Space with our special guest co-founder of @ensvision , @furyan 🎙️ 🗓 Saturday, 10 AM EST 🎤 Hosted by Ana @lawsbyana and hid.eth @hid.eth 💡 Topics: Digital Identity, future of domains and more! Space : https://x.com/i/spaces/1DXGyqQYWnWGM
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0xkylerli pfp
0xkylerli
@0xkylerli
meme
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0xkylerli pfp
0xkylerli
@0xkylerli
e卫兵勇敢向前冲 2000-5000指日可待
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0xkylerli pfp
0xkylerli
@0xkylerli
gm
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Dan Romero pfp
Dan Romero
@dwr.eth
Introducing Composer Actions - Create frames while you're writing a cast - Discover new actions right in the app - Available on Warpcast mobile - Developers can now build and submit an actions for listing Here's a demo of the new animated GIF action (!) by @0xconca.eth featuring a GIF from @miguelgarest.eth.
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0xkylerli pfp
0xkylerli
@0xkylerli
lol
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Dan Romero pfp
Dan Romero
@dwr.eth
From the weekend - salt sugar wet brine grilled chicken work aioli - Alison Roman lemon potato salad - basic vinaigrette and salad - homemade peach ice cream
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0xkylerli pfp
0xkylerli
@0xkylerli
zk 1u?
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Vitalik Buterin pfp
Vitalik Buterin
@vitalik.eth
There's a fascinating analogy between coding in python using hyper-optimized vectorized libraries (numpy, cupy, torch...), and living in Singapore. In python, whatever you're not vectorizing takes the longest, even if it's utterly trivial. Literally picking merkle branches out of a pre-built tree is taking me longer than an entire fast fourier transform. In Singapore, whatever you get from international brands (as opposed to eg. hawker centers) is the most expensive, even if it's utterly trivial. I've literally had meals where the starbucks green tea I had right after a hawker center meal cost more than the meal.
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0xkylerli pfp
0xkylerli
@0xkylerli
A warm Farcaster welcome to @fangcheng!
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0xkylerli pfp
0xkylerli
@0xkylerli
nice
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Vitalik Buterin pfp
Vitalik Buterin
@vitalik.eth
The differences between the APIs of numpy, cupy and torch are so fascinating.... ``` >>> import torch as np >>> np.arange(10) tensor([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) >>> a = np.zeros(20) >>> a[19:-1:-2] = np.arange(10) ``` Torch doesn't let you have ranges that go backwards 🤣 Would love more consistency
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0xkylerli pfp
0xkylerli
@0xkylerli
zk 1u
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0xkylerli pfp
0xkylerli
@0xkylerli
wow eth etf approved
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0xkylerli pfp
0xkylerli
@0xkylerli
十五亿融资 好项目
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0xkylerli pfp
0xkylerli
@0xkylerli
马上搬新家咯
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0xkylerli pfp
0xkylerli
@0xkylerli
wow
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0xkylerli pfp
0xkylerli
@0xkylerli
degen wake gm!
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0xkylerli pfp
0xkylerli
@0xkylerli
degendegenwakewake
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0xace🎩🍖 pfp
0xace🎩🍖
@0xace
Is there any alpha?
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