Joined June 2018
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22 Sep 2024
Implication, necessary and sufficient conditions are usually taught inadequately Here is how I would teach these concepts: blog.naz.ooo

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Palmer Luckey’s advice for founder-led communications “My advice to people would probably be to recognize that the value of your reputation is very high,” Anduril founder Palmer Luckey begins. “If people do not trust you; if they do not believe in what you’re saying; if they do not think that you’re a person worth listening to, they’re going to have a hard time working with you.” Palmer also argues that founders don’t need to be neutral: “You don’t need to be neutral. You can be a propagandist. You can advocate for a particular point of view . . . In general, people should recognize that if you say something where you caveat it and hedge it and basically end up saying something that most people would agree with, you might as well have said nothing at all.” He continues: “You are not going to build a following of people who say, ‘I just love Palmer’s right-down-the-middle, very-hedged takes that everyone agrees with.’ If you’re just restating common sentiment, it’s not going to get you anywhere . . . So one of the things I tell people is, ‘Make sure that when you’re saying something, you’re SAYING something. Make sure you’re trying to persuade and affect change.’ — maybe not in everybody, but in some people. If you make some people love what you’re saying and some people hate what you’re saying, that’s a lot better than having everybody lukewarm agree with you. Don’t waste your time communicating about the things everyone already agrees with you on. Focus on the things where you need to change their mind.” Source: @lulumeservey (Sep 2025)
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my @MochiCardsApp so far started brushing up / re-learning math end of April already down with Lay's Linear Algebra, and on chapter 3 in Colley's Vector Calc
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arclength reparametrization is quite involved when it comes to notation, it's always "let's abuse it" i wonder if this is the case with all the vector calculus books, or just colley
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genuinely learning **new things** interacting with Fable. all previous models would simply clarify known facts at best.
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Colley's vector calc is a decent book, but the notation is definitely crazy at times
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colley's vector calc notation goes crazy let's define function f, whose co-ordinate inputs are x, y, z; let's also define function x (just like a co-ordinate, but boldfaced), and let's have inputs s, t yikes
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problem from Putnam, that if you have the right idea can be solved pretty quickly: Let A and B be different n by n matrices with real entries. If A^3 = B^3 and A^2 B = B^2 A, can A^2 B^2 be invertible?
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Someone should build a version of polymarket where you can bet on something and then you win the bet if that thing happens
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Jane Street 的这篇文章写得也太漂亮了,把抽象群论和实际 ML 模型结合得非常漂亮,读完会有“原来位置编码的空间这么受限”的感觉。强烈推荐给对数学 深度学习感兴趣的人。 blog.janestreet.com/using-gr…
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linear algebra by lay and lay done took me just under 6 weeks, produced around ~1000 flashcards will write a blog post about how I self study math soon next on: hubbard's vector calclus. this one is going to likely take longer. but seems first 4 chapters overlap a ton with linear algebra anyway
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interference disappears the moment we ask which path it took? time to join the instrumentalists
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took me an hour to think through a => b, but now when I read it, seems "trivial" 🥲
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May 24
I really liked Eric's take on why alpha go is profound: A 10-layer network can only do 10 sequential steps of thinking, by construction. And yet those 10 steps can "amortize and approximate to very high fidelity a nearly intractable search problem."
Monte Carlo Tree Search training corrects the model move by move, while current LLM training only tells it whether the whole trajectory worked. MCTS is preferable if you can get it. But nobody's managed to get MCTS to work for language models. In his blackboard lecture @ericjang11 talked to me about why:
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May 22
All archive data now live via API
Remember when we dropped the full Polymarket order book archive? 30M rows per hourly dump, raw parquet files, everyone loved it The problem: you had to download 500MB-1GB parquet files, write your own parser, reconstruct the book yourself from tick deltas That's over. You can now query historical order books directly from the API. 4 lines of Python. 🧵
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Bir kişinin zekâ, çalışkanlık ve duygusal olarak dengeli olma özelliklerinin çok üst düzeyine aynı anda sahip olma olasılığı milyonda 85'tir.
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Confession: I never had a single work-related sleepless night or ever pulled an all-nighter during my career incl. PhD. Don’t sacrifice your health. Sleep is a superpower — your brain on 8hrs of sleep is a lot smarter than your brain on sleep deprivation. Don’t listen to people who tell you to chronically sacrifice sleep for work. Sacrificing sleep for your kids/family is a different story.
Replying to @npparikh
I doubt all those things are really possible. Infact I believe, you are not doing a good PhD unless you have sleepless nights. Definitely just working on your thesis is possible if you follow a 9-6 schedule, but a good PhD which involves exploring, colabs, etc needs extra hours
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me: claude, read every markdown file in the repo claude: i have read every markdown file in the repo honest caveat: i haven't read all of x.md, i am comfortable with the gap me: 🤦‍♂️
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Saylor is going to kill BTC because he will own too many bitcoins but also he's going to kill BTC because he will sell some bitcoins
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"our results suggest that understanding neural networks requires shifting from a dictionary of concepts to a geometry of representations; where meaning is encoded not in single atoms, but in the structure they collectively induce" 100% agreed.
Neural networks might speak English, but they think in shapes. Understanding their rich *neural geometry* is key to understanding how they work – and to debugging and controlling them with precision. Starting today, we’re releasing a series of posts on this research agenda. 🧵
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