jay4🧬💫

introverted extrovert || Manchester United fan || Futarian, AI user, open claw

[jay4🧬💫 @brojay0]

@BenoHr80463 Interested

[jay4🧬💫 @brojay0]

@hypothyfoid @JacksonFromTwit Please i need it too 🙏

[SuperDefi @SuperDefi_Dao]

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[jay4🧬💫 @brojay0]

Finally
My magnifico 🪄 is up there
Bruno 🎩

[jay4🧬💫 @brojay0]

God punish that Al nassr keeper shaa
Even that player too

Imaginee

[Jay Yang @Jayyanginspires]

A wise mentor once told me: “Before you play the game, study the winners. If you don’t want their life, don’t play their game.”

[jay4🧬💫 @brojay0]

@MrGigaWhale Agreed

[Whale @MrGigaWhale]

The crowded trade problem is one of the more counterintuitive risks in markets.

The common assumption is that if a lot of smart people are in the same position, that position is probably correct. The analysis is sound, the thesis is well-constructed, and broad agreement seems like validation. But what crowding actually does is change the exit dynamics entirely.

When everyone is on the same side, the position works until it doesn't, and when it doesn't, the exit is simultaneous. There's nobody to sell to except other holders who are trying to exit for the same reason. The fundamental thesis can be completely right and the position can still produce a painful drawdown purely because the unwind is simultaneous and there's no incremental buyer to absorb it.

The most dangerous trades in crypto are the ones that feel safe because everyone agrees with them. The consensus is often correct on direction and catastrophic on timing, because the consensus getting in is what makes the eventual unwind violent.

[jay4🧬💫 @brojay0]

@airdrop_testing @MACDONS_1 @gab_riel4k Are we to uninstall the app every time for new account?

[jay4🧬💫 @brojay0]

Chelsea don dey lose ke

[jay4🧬💫 @brojay0]

@Oski_234 @web3righteous Please can you explain the withdrawal process?

[jay4🧬💫 @brojay0]

@MrCharlesky I'm here

[jay4🧬💫 @brojay0]

@MrCharlesky Interested

[jay4🧬💫 @brojay0]

My worries wan show for my face
Na once i remember i be man 😤 no one cares
They will be like "na everytime this one dey frown

[jay4🧬💫 @brojay0]

@eleshomorenike @Biggy2705 See kindergarten banting 😭
"I get brain pass your whole family"

[jay4🧬💫 @brojay0]

@derivio_xyz @BNBCHAIN 🤞🫰

[jay4🧬💫 @brojay0]

@ziv_ravid @ZSkyX7 @srush_nlp LFG

[Ravid Shwartz Ziv @ziv_ravid]

New episode of The Information Bottleneck is out 🥳

In this one, we talked with @srush_nlp, a researcher at Cursor and professor at Cornell, about the hottest topic - coding agents! We talked about how Cursor trains Composer, the challenges, and where all this is going.

One point Sasha made stuck with me.
Coding agents work really well, but only when you can specify a clear hill-climbing signal. A problem where the agent knows it's getting better. Karpathy tried this on nanochat a few weeks back, letting an agent run overnight to optimize the validation loss autonomously. The follow-ups were mixed. Sometimes the "improvement" was worse than classical methods.

Most real problems don't come pre-packaged with a reward signal at all. You don't know if a new architecture is better until you've already run the experiment. You don't know if a refactor is cleaner until someone reads it. You don't know if a product decision worked until months later. A lot of what we call hard problems are hard precisely because the signal is missing, noisy, or expensive to get.

I think the next big challenge isn't getting agents to solve problems. It's finding problems you can actually formalize as hill climbing, or building a cheap proxy that correlates with what you care about.

[jay4🧬💫 @brojay0]

@ZSkyX7 LFG

[Sky Zhang @ZSkyX7]

Having an opposing party critising an convincing argument really helps to liberate the mind.
It’s the sudden realization that I am in a hole I’ve been digging unconsciously.