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Implication, necessary and sufficient conditions are usually taught inadequately Here is how I would teach these concepts: blog.naz.ooo
how is it that solana bloom sniper bot gets front-ran quite often are they selling their orderflow?
solana and its black-boxed closed-source everything kingdom of guesswork
this post is complete misinformation LLMs are lossy compressors! of *training data*. LLMs losslessly compress *prompts*, internally. that’s what this paper shows. source: i am the author of “Language Model Inversion”, the original paper on this
One of the quiet privileges of academia: you spend your days surrounded by some of the brightest people on the planet — all trying to understand something deeply. Not to sell it, not to exploit it, just to understand. That changes you.
farms on meteora who even falls for this he is literally buying and selling from the same wallet
The dependency graph for defining Brownian Motion in Lean4 is actually so cursed
Exactly. I learned a ton of math during my PhD, and it was fun and easy *because I had a goal* to use it in my research. Coding it up is also a great way to detect gaps in your understanding. Totally different from learning in class. Another common fallacy is that you need to…
This is empirically incorrect. Hundreds of thousands of fast.ai students have learned the required math for ML as they go. By *far* the biggest problem we've seen is from people who try to learn the math first. They learn the wrong stuff & have not context.
just discovered @MetaDAOProject such a cool concept it looks to be quite helpful in sparking that initial interest too, if the project raises the intended amount you immediately get that initial distribution if the project doesn't raise the target, then you save yourself time…
on one hand i want to build something big and aim for the stars, but this is risky, especially after i have been building the last product for a year on the other hand, a diversified stream of income from small bets would be nice at this point. especially, since it could allow…
so i guess i will be looking for the next $1b idea in robin hanson's blogs
we have been developing a rust solana sniper bot for about ~1 year 50us tick to trade 150k+ rust, python, typescript loc immense amount of lessons learned, probably 10+ different iterations of the strategy, a whole architecture re-write at one point, a very interesting risk…
you start with $1,000 you onramp, pay 3% → $970 you deposit at 6% for a year → $1,028 you offramp, pay another 3% → $997 congrats, you just lost $3 (+ inflation) for the privilege of using crypto
was close to selling some of my satoshis yesterday but, realistically, where else would you park the money? dollars? hell no even if this was top, i would rather hold btc than anything else. it was literally built for times like these
There is no reason why graduate students must be in their twenties. It should be a possibility to study and research later in life and we should reshape our work culture to make it far easier than it is
In the Weinberg group there was a GR grad student around his sixties
how trading on CT works: step 1/ size into the position with everything you have at 10x leverage step 2/ start to incessantly make all sorts of theses about why you are right step 3/ create private trading journals and newsletters and repeat step 2/ step 4/ eventually enough…
This is an elementary example, but it illustrates how real order flow trading actually works. It’s never about some retail based indicator like MACD, RSI, etc. One of the earlier prop firms I worked at did a phenomenal job instilling in me how this type of trading really…
We invited @dwarkesh_sp to tackle a foundational question in quant trading: What does it take to build a predictive signal from market data? We loved showing him what makes work at HRT so fun — and why, in Marc’s words, “it occupies a lot of very smart people for years.”
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