flâneur

Kanupriya Banerjee

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on the atlas — 16

highlights — 27

  • The challenge, therefore, is not to moralise politics in some superficial sense, but to reconstitute its deepest ethical foundations. This calls for an education oriented toward critical thought and moral imagination rather than rote obedience, as well as a public sphere that privileges truth and deliberation over spectacle and viral outrage.
    The moral eclipse of politics in the modern age - The Hindu
  • What is absent across these contexts is not raw intelligence or tactical acumen but empathy or the vital capacity to recognise the other as fully human, worthy of the same moral consideration we claim for ourselves.
    The moral eclipse of politics in the modern age - The Hindu
  • In her red sleeveless outfit, she wore her emotions on her sleeve and let the world hear them: She shouted, celebrated and let every point show on her face
    Carolina Marín retires: Through the noise, the results rang loud - The Hindu
  • Compared to a control cohort whose brains were stimulated at the effector regions, the SCAN-targeted group showed significantly less tremors, rigidity, slowness, and instability within two weeks.
    Newfound brain network ‘SCAN’ implicated in Parkinson’s disease - The Hindu
  • Nevertheless, SCAN over-connectivity with basal ganglia represents a new network-level biomarker for Parkinson’s disease
    Newfound brain network ‘SCAN’ implicated in Parkinson’s disease - The Hindu
  • A new study in Nature addressed this hypothesis and found that Parkinson’s disease is associated with the abnormal strengthening of a brain network called the somatic cognitive action network (SCAN).
    Newfound brain network ‘SCAN’ implicated in Parkinson’s disease - The Hindu
  • the dynamic random access memory (RAM) inside your computer is based on the idea of having two tiny metal plates separated by a miniscule gap. Electric charge is stored on those plates, setting up an electric field between them. The 00 and 11 states of the bit correspond to two different configurations of charge on the plates
    Quantum computing for the very curious
  • the quantum state of a qubit is a vector of unit length in a two-dimensional complex vector space known as state space.
    Quantum computing for the very curious
  • In that sense, it’s quite a simple and beautiful statement. But it’s not an obvious statement,
    Quantum computing for the very curious
  • More specifically, the state of a qubit is a vector in a two-dimensional vector space. This vector space is known as state space. For instance, here’s a possible state for a qubit: [10][10​]
    Quantum computing for the very curious
  • In your computer’s memory chips, bits are most likely stored as tiny electric charges on nanometer-scale capacitors (i.e., little reservoirs of charge), just above the surface of the chip. Old-fashioned hard disks take a different approach, using tiny magnets to store bits. Furthermore, different types of memory use different types of capacitor; different types of hard disk use different approaches to magnetization.
    Quantum computing for the very curious
  • quantum computer. Those quantum computers can do everything conventional computers can do, but are also capable of efficiently simulating quantum-mechanical processes
    Quantum computing for the very curious
  • Deutsch pointed out that every algorithm is carried out by a physical system
    Quantum computing for the very curious
  • Is there a (single) universal computing device which can efficiently simulate any other physical system?
    Quantum computing for the very curious
  • Turing machine: a single, universal programmable computing device that Turing argued could perform any algorithm whatsoever
    Quantum computing for the very curious
  • Roughly speaking, Hilbert’s 1928 problem asked whether there exists a general algorithm a mathematician can follow which would let them figure out whether any given mathematical statement is provable.
    Quantum computing for the very curious
  • Discovery fiction starts with the question “how would I have discovered this result?” And then you try to make up a story about how you might have come to discover it, following simple, almost-obvious steps.
    Using spaced repetition systems to see through a piece of mathematics
  • Now, the only way I’ve reliably found to get to this point is to get obsessed with some mathematical problem
    Using spaced repetition systems to see through a piece of mathematics
  • I can’t emphasize enough the value of finding multiple different ways of thinking about the “same” mathematical ideas
    Using spaced repetition systems to see through a piece of mathematics
  • I recommend regularly asking “am I getting value from this?” and every hour writing down what you just learned.
    Post 34: Learning how to learn — Neel Nanda
  • Eg, challenge yourself to write down the key ideas of a course in <10 minutes. This pressure often forces me to identify the truly important ideas.
    Post 34: Learning how to learn — Neel Nanda
  • Optimise for what will help you understand other things. Can you imagine this coming up again? What is the minimal set of ideas I’d need to remember to rederive everything else here? Ask someone who’s more experienced than you whether this is worth your time Notice when things feel arbitrary or unmotivated This is hard because sometimes this shows you haven’t grasped the high-level picture - mentors are useful for resolving this!
    Post 34: Learning how to learn — Neel Nanda
  • What is going on here? What problems are we trying to solve? Why do we care about this? How could I rederive/generate this idea from scratch if I needed to? Notice when a decision feels arbitrary and unmotivated, and try to figure out where it comes from Sit down, and try to write out the key points of a topic from memory. What are the biggest holes in your understanding? What’s missing? What is currently confusing me? What felt surprising?
    Post 34: Learning how to learn — Neel Nanda
  • If you feel you could easily find something more rewarding to read, switch over. It's worth deliberately practicing such switches, to avoid building a counter-productive habit of completionism in your reading. It's nearly always possible to read deeper into a paper, but that doesn't mean you can't easily be getting more value elsewhere. It's a failure mode to spend too long reading unimportant papers.
    Augmenting Long-term Memory
  • It's particularly helpful to extract Anki questions from the abstract, introduction, conclusion, figures, and figure captions. Typically I will extract anywhere from 5 to 20 Anki questions from the paper. It's usually a bad idea to extract fewer than 5 questions – doing so tends to leave the paper as a kind of isolated orphan in my memory. Later I find it difficult to feel much connection to those questions. Put another way: if a paper is so uninteresting that it's not possible to add 5 good questions about it, it's usually better to add no questions at all
    Augmenting Long-term Memory
  • I find Anki works much better when used in service to some personal creative project
    Augmenting Long-term Memory
  • the most common mistakes with spaced repetition are formulating poor questions and answers assuming it will help you learn, as opposed to maintain and preserve what one already learned⁠⁠54⁠. (It’s hard to learn from cards, but if you have learned something, it’s much easier to then devise a set of flashcards that will test your weak points.)
    Spaced Repetition for Efficient Learning · Gwern.net