0xSuco

@suco

71 Following

87 Followers

Dan Romero pfp

Question for devs: is Claude still the best model for actual coding? If so, by how much?

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Varun Srinivasan pfp

Varun Srinivasan

Meow is a great product! Good opportunity

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0xSuco pfp

I'm definitely pulling up

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Plaza Finance pfp

Who is pulling up tomorrow? 🙋‍♂️

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0xSuco pfp

built on base ✔️ built on ethereum ✔️

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Varun Srinivasan pfp

Varun Srinivasan

Snapchain testnet went live at 4pm today. Over 20,000 blocks have been produced already with a million messages processed. This is real data from mainnet that is mirrored over to test Snapchain's integrity.

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0xSuco pfp

Yeah! Let's have it, please 🥺

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Plaza Finance pfp

Yesterday was the biggest liquidation event in crypto history. Today prices recovered. 🙏 We designed levETH exactly for this scenario - so you don't get stopped out of your trade during a short-term drawdown, and can play for the recovery 🥽 Launching on Base soon and expanding everywhere 🚀 https://cointelegraph.com/news/crypto-market-liquidation-bybit-10b

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0xSuco pfp

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ace pfp

Excited for next week, but what’s coming next week? 👀

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Dan Romero pfp

hbd @vitalik.eth

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Plaza Finance pfp

levETH is cross-chain composable levered exposure to $ETH LSTs and LRTs 🧐 More below 👇

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Jonny Mack pfp

losers focus on winners, winners focus on winning

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Base pfp

The /blueprint Cohort is working with creators making short-form video, podcasts, digital art, and music. Here's their latest round of drops: How to Make a Beat: Dancers - @devanibiza https://zora.co/collect/base:0x20bcdc34647585ede7d61f3ac511a3492b758030/4?referrer=0x5c88585422E5631bd3Fd95B804BcA64cBd7924eF

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0xSuco pfp

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Plaza Finance pfp

bondETH is a decentralized high-yield bonds backed by $ETH LSTs and LRTs that pays income in $USDC 🤔 More below 👇

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ace pfp

"reasonable" degens will be using ______ instead of pumpfun because it extracts sol. lol as if degens aping rely on "reasons." who tf thinks about that in all honesty? they find where the most potent apable assets are. flock. ape. end of story

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Dan Romero pfp

Primary Address FIP https://github.com/farcasterxyz/protocol/discussions/141

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July pfp

I think of “normal” as a Gaussian - in high dimensional space we’re always descending to some local minima(s) normality (gradient descent) in retrospect but the loss function is nonlinear (and unknowable because of the continuously changing landscape)- since there’s always new data, new context that’s emerging faster than ever In way - sort of normality is a kind of emergent property that isn’t fixed but more dependent on framing of the data w.r.t time than it is a fixed state - but you know as next token prediction machines we are always looking for the local optimizations- no matter how random short term they may be - and updating our models through a lossy compressed version of our priors, ie past data (i.e. reality) Also the way we navigate the loss field changes the path we choose as well (path dependence)

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Jonny Mack pfp

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