Devendra @dev_shm

“Being wrong is part of being a scientist. We’re wrong all the time. One of the jokes that I use all the time, but it’s not a joke, it’s really true, is when we got to the point of trying to identify this gene, we had 20 possible genes it could be. I prioritised those genes. The gene that was responsible was the last gene, which means I could not have been more wrong in my prioritisation. It’s absolutely the most wrong thing I could have done. We got it eventually, so it was still there, but it was because there was nothing left. It’s not because I was smart or had any foresight.” In our official interview with medicine laureate Fred Ramsdell, he told us about the importance of handling failures and being persistent. Watch the full interview: nobelprize.org/prizes/medicin…

Physics laureate Anton Zeilinger followed his curiosity to India where he discussed the possibilities of parallels between eastern philosophy and quantum mechanics with the Dalai Lama. Watch our 2022 interview: bit.ly/3x2yTOi

Why did so many languages copy async/await from C#? Anders Hejlsberg(@ahejlsberg) - creator of TypeScript, C# & Turbo Pascal - on what they got right with the design: #1 - async/await was designed to solve a common problem in the event-loop model: "A lot of languages are built around cooperative multitasking in the sense that they have an event loop that sits and dispatches events. Then you handle the event and then you yield back to the event handler loop. And it all runs in a single thread cooperatively. The problem with that is if you then want to do some long running work: how do I stop in the middle of this piece of long running work and yield back to the event loop cooperatively? And then when my result is ready, I can come back and continue executing here." #2 - state machines are the solution, but hard to build: "Well, in order to do that in an inverted architecture like that, you have to build a state machine. State machines are notoriously hard for people to implement because you've got to move all of your state off of the stack into objects. And then you have this big case statement that envelopes your entire logic. It's a nightmare to figure out. But, the transformation from serially executing code into a state machine, its continuation-passing-style translation is actually one that you can do in a machine-based fashion." #3 - compilers are good at writing state machines: "You can have the compiler write the state machine if you introduce syntax that allows you to indicate where you want to yield. And that's what await is. Await is basically saying, I want to yield here, and I want to yield this promise, and then when the promise completes, I want you to come back here and continue executing. Then the compiler writes a state machine around it and it actually turns it into this big switch statement and moves all of the state that survives across the await into something that's heap allocated. So it can be brought back. And doing all of that work is something that compilers are great at. And so that was sort of the idea that we have this new style of programming where we're using promises or the equivalent of promises and the ability to yield and then we have callbacks. But trying to write your program in that style, that's also what JavaScript suffered from a lot. It's like all this callback style stuff. With Async and Await, you get the illusion that you're just writing normal sequential code and then the compiler does the painful transformation for you. That turns out to be really useful."

Ranked: The Countries With the Most High-Speed Rail 🚄 visualcapitalist.com/ranked-countri…

If you want something from someone, make it clear what. It's not imposing to ask explicitly for something; it's imposing to be vague and make the recipient work to figure out what you want.

If you think a $300K corporate salary is payment for 40 hours of weekly labor, I've got news for you... There is a persistent cynical narrative that large enterprises are bloated engines of inefficiency, filled with overpaid professionals who spend their days looking at slides and doing "nothing." I mean, it's a comforting myth for critics, but I think it fundamentally misunderstands modern knowledge work. That $300K salary (or $400K, or $500K) isn't a reward for linear effort but an option premium on high-leverage thinking. We are still haunted by the ghost of the assembly line, ie, the outdated idea that compensation must directly correlate with time spent + physical output. In the factory world, if you leave your station, production stops, but in the knowledge economy, value is almost totally decoupled from time. Folks... An enterprise paying a senior leader or specialist $25K a month is not buying 160 hours of typing, they are buying *insurance* against catastrophic errors and positioning themselves for asymmetric upside. I'll try to make it tangible with an example... Consider a complex matrix organization busy with a $40M product migration. In this environment, the value distribution of a worker's is heavily spiked. Most days look like nothing... alignment meetings, reading documentation, maintaining steady state. Yes, to an outsider, it looks like "doing nothing." But then a critical day arrives. A vendor fails, a timeline slips, a crossroads appears, whatever... If that $300K professional has the institutional memory and capability to make just 4 or 5 correct decisions during those critical moments, the ROI is staggering! A single right call can avert a $5M problem. Suddenly, that $300K salary doesn't look like bloat but, to me, seems like the cheapest asset on the p&l. These days we are bombarded by tech CEOs promising fully autonomous, AI-driven organizations and I keep saying these pitches miss the entire point of how complex enterprises actually move. Data computation can be outsourced to an LLM but going through the decision fabric of an enterprise cannot. You need people for: > Knowing *how* to build consensus across disconnected departments with competing incentives; > Understanding the unspoken history of why past projects failed, and how to position a new initiative so it doesn't trigger corporate antibodies; > When a multi-million-dollar decision goes sideways, an algorithm cannot stand before a board of directors or regulators and take ownership of the corrective action. An AI can give you a pristine strategic framework with nice and difficult sounding words, but it cannot navigate the human matrix required to execute it. The ability to be effective inside a complex enterprise is a rare AND expensive skillset precisely because it cannot be automated or easily replicated. My point is you aren't paying for the 9-to-5 "grind", but more for the readiness. Like an elite surgeon or an expert technician, you pay for the decades of accumulated knowledge that allow them to fix a crisis in 5 minutes, not the 5 minutes itself.... Leverage, not labor.

Books I regularly recommend to parents: 📕Absorbent Mind (Montessori) - she has the deepest reverse for the human condition focused on children. 📗 Positive Discipline series - great for instilling emotional intelligence and agency in young children. 📘 How to Talk so Children Listen and Listen so Children Talk (Faber) - fabulous practical communication tips. 📙 How Children Learn (Holt) - love his observations about helping young children to teach themselves. 📚 Teach Your Child to Read in 100 Easy Lessons (Engelmann) - the bible of teaching reading. 📖 Magical Child (Pearce) - raising genius kids through play. He gets woo-woo at the end (but given that people love the telepathy tapes, maybe he's onto something).

Paul Graham @paulg

a week ago

Someone asked me to recommend a good book on parenting. I would guess that most books about parenting are tedious. So my recommendation is to read autobiographies, the early parts of which are usually implicitly about parenting.

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If W> 2T, then it's rejected as per IPC A 610 under all 3 classes. W= Width of the component and T is thickness or height. PS: I tweeted this without checking any documents. I am pulling this from my memory from a decade ago.

Lukas Henkel @QVHenkel

a week ago

I've mounted the inductors in the reverse direction, with them standing on the narrow sides. I didn't even notice it looks like it's meant to be that way. 😅

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.@pmarca: "The person who writes down the thing has tremendous power." @david_perell

David Haber @dhaber

2 weeks ago

x.com/i/article/2064…

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We were built for bright days and dark nights. Among 86,772 adults, more light at night was linked to higher odds of depression, anxiety, PTSD, psychosis, bipolar disorder, and self-harm. Respecting our natural rhythms is one of the lowest hanging fruits for mental health.

Demonstrative of the muddled thinking of the anti-surrogacy crowd is the constantly repeated claim that surrogacy is like taking a puppy away from its mother. Surrogacy is like taking a puppy away from one mother, and giving it to another dog who accepts it as her puppy. This technique is called cross-fostering and it's been used for centuries for animal husbandry, conservation and research because it has minimal effects on the animal so long as its new parent cares for it.

@hthieblot Retire my parents, buy them a house, and make sure they have 0 money worries ever again

One thing Paul Graham said about YC interviews is that they’re not looking for founders who can “control the room” like polished salespeople. The real question YC is trying to answer is: “How do you know people actually want this?” That’s also why YC tends to filter out a lot of overly “street smart” founders. People who bluff, dodge questions, or try too hard to sound impressive are usually easier to detect than they think. Real understanding of users tends to sound much calmer and more specific.

Clinical psychologist @darbysaxbe breaks down how becoming a parent physically remakes the brain—and why "dad brain" is a very real, measurable neurological shift.🧠 Watch this take from our recent Super Salon on how fatherhood remakes a man, hosted by @TKPullinger.

Many founders start with a shiny new technology and go looking for a problem it can solve. The ones who build companies that last do the opposite. They start with a problem they understand deeply and reach for whatever tools, new and old, best solve it. This discipline matters more now than ever, because the leverage available to one person has never been higher. We're entering an era where 10 people can do what used to take 10,000. The more any one person can do, the more it matters what they choose to do with it. The obvious thing to do with your leverage is spend it on volume: ship more code, launch more features, send more outreach, generate more of everything. That confuses speed with velocity. Speed is pure motion. It's seductive because it's the easiest thing to measure and the easiest to mistake for progress. Velocity is motion with direction. It reveals itself over time, in whether your motion brought you closer to a goal worth reaching. A startup sprinting in 10 directions at once can feel enormously productive while going nowhere. To win the race, you have to run quickly and in the right direction. One of the biggest jobs of an early-stage founder is figuring out which direction that is. The best thing to spend your leverage on is ambition, on projects you would never have had the resources, expertise, or confidence to attempt before. But ambition needs a direction too. The right one is a problem that genuinely matters to you: one whose solution would mean something to a few people you know, and ideally to many. That’s where the best founders begin: with the problem itself, before any particular tool. The tools change by the week, but the problems worth solving change at human pace.

VC pitch horror stories are so fun. My best is when a partner tried to teach my cofounder some basic Chinese for 20 minutes before he let us start the pitch. Fun times!!!

Co-founder is marriage without the sex.

You cannot solve problems with compute that are created by problems of context.

Men and women calculate the number of people they've had sex with differently. Women are more likely to exclude someone from their body count e.g. if it was just once, or they regret it. Men are more likely to count anything sex related as a sexual partner, and do calculations like "I had sex with 3 women a year for 5 years, so 15" instead of keeping track properly. If everyone calculated accurately and there was adequate sampling the number for men and women would be the same, but they aren't because of women's omission, men's generous inclusion and, likely, not sampling prostitutes who end up in many men's counts.

For Aristotle, the banausos is not just physically deformed by his profession, but politically and ethically stunted: specialization makes him less a complete man than a TOOL of his occupation. Politics, book VII: "And any occupation, art, or science, which makes the body or soul or mind of the freeman less fit for the practice or exercise of virtue, is vulgar; wherefore we call those arts vulgar which tend to DEFORM the body, and likewise all paid employments, for they absorb and degrade the mind."

ThinkingWest @thinkingwest

3 weeks ago

Everyone’s missing the most insane thing about Federer’s physique

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