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The most important tool in Probability and Statistics - Markov Chain Monte Carlo (MCMC) Method Fresh out of undergraduate Probability and Stats courses, it’s easy to feel invincible. You’ve tamed Gaussians, gammas, betas, all those neat closed-form toy distributions. Then research hits and you meet the harsher truth. Real... posteriors and energy landscapes are jagged, asymmetric, multimodal, and too high-dimensional to integrate or sample from directly. You can’t compute the normalising constant. You can’t do the integrals by hand. And i.i.d. samples are basically science fiction. Markov Chain Monte Carlo is the hack we invented to survive that reality. Instead of drawing perfect samples, you send a carefully designed random walk wandering through the landscape, then use its long-run positions as your window into the target distribution. Here’s the problem. Standard trace plots and diagnostics can still cheerfully lie to you. High-dimensional geometry can make a chain that looks healthy while it’s effectively frozen. Multimodal targets, bad tuning, and hidden correlations can quietly wreck your posterior summaries. This series is about those blind spots. We’ll use visuals like this one to show how MCMC actually moves, where the guarantees get slippery, and how to think clearly about convergence and diagnostics in serious Bayesian, physics, and ML work. #BayesianInference #MCMC #MonteCarloMethods #ProbabilityLandscape #StatisticsEducation #ComputationalScienceshow more

Mathelirium

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32,296 просмотров • 7 месяцев назад •via X (Twitter)

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$In 1906, the world-renowned Russian mathematician Andrey A. Markov asked a heretic question of that time: if randomness has memory, do averages still behave or does probability theory collapse? His answer was a new kind of dependence where the next step only remembers the present, P(X_{n+1}=j | X_n=i, X_{n-1}, …) = P_ij, and yet the law of large numbers survives. The path stays noisy, while long-run state frequencies converge to a fixed profile pi = pi P. Markov’s idea is now the workhorse behind estimates by random-walks. MCMC (Markov Chain Monte Carlo) builds a chain whose stationary distribution is the target (posteriors, partition functions, constrained geometries), then uses time-averages as estimates. The same Markov structure shows up in hidden Markov models for time series, in biophysics as channels switching between states, and in control/RL as Markov decision processes. #ProbabilityTheory #Markov #MCMC$

In 1906, the world-renowned Russian mathematician Andrey A. Markov asked a heretic question of that time: if randomness has memory, do averages still behave or does probability theory collapse? His answer was a new kind of dependence where the next step only remembers the present, P(X_{n+1}=j | X_n=i, X_{n-1}, …) = P_ij, and yet the law of large numbers survives. The path stays noisy, while long-run state frequencies converge to a fixed profile pi = pi P. Markov’s idea is now the workhorse behind estimates by random-walks. MCMC (Markov Chain Monte Carlo) builds a chain whose stationary distribution is the target (posteriors, partition functions, constrained geometries), then uses time-averages as estimates. The same Markov structure shows up in hidden Markov models for time series, in biophysics as channels switching between states, and in control/RL as Markov decision processes. #ProbabilityTheory #Markov #MCMC

Mathelirium

288,553 просмотров • 9 месяцев назад

I asked Garry Tan how to use meta prompting to get better at AI: "My partners at YC Jared Friedman and Pete Koomen showed me how to do this. You can take almost anything that you do all the time and just drop it into a context window. And then say, “Here’s a bunch of inputs and outputs." And maybe you also add a bunch of notes. And then you tell it, “Write me a prompt that can act as an agent that takes this input and makes this output over here.” You can do this for almost any type of knowledge work. And you can even introspect. "What are things you notice that I did to convert this from the input to the output?”. And then you can just start using the prompt. Initially, it’s going to suck. Because it’s just not that smart yet. But what’s funny is now, I also use it to Iterate my writing. You can be very direct, "I would never say that", "Don’t say it like this", or "Oh, you used the long word there, use the short word". Just speak to it conversationally. And then when you're happy with the output, you can use that new output to make a new prompt. "Based on this conversation, give me a better initial prompt that incorporates all the things we talked about." And you can do this with literally everything. And in theory, there’s so much it applies to that people do day-to-day. You could use it for tweets. You could use it for editing podcasts. You can use it for pretty much everything. I have a folder of prompts that I use all the time. My YouTube prompt is on v27 or something. I'll go through this process with all the different max models. I'll use GPT 5.2 Pro. I’ll use Grok. I'll use Claude. Then, I’ll take all the outputs from all the models and put them into Claude and say "Here’s my prompt, here’s the output from four LLMs, including yourself. Rate each response and tell me what the pros and cons of each approach are." And I usually say "give it to me in numbered form". And then you can agree with one, disagree with two, tell it three is this or that. And then after that, you say given all of this, synthesize it."

I asked Garry Tan how to use meta prompting to get better at AI: "My partners at YC Jared Friedman and Pete Koomen showed me how to do this. You can take almost anything that you do all the time and just drop it into a context window. And then say, “Here’s a bunch of inputs and outputs." And maybe you also add a bunch of notes. And then you tell it, “Write me a prompt that can act as an agent that takes this input and makes this output over here.” You can do this for almost any type of knowledge work. And you can even introspect. "What are things you notice that I did to convert this from the input to the output?”. And then you can just start using the prompt. Initially, it’s going to suck. Because it’s just not that smart yet. But what’s funny is now, I also use it to Iterate my writing. You can be very direct, "I would never say that", "Don’t say it like this", or "Oh, you used the long word there, use the short word". Just speak to it conversationally. And then when you're happy with the output, you can use that new output to make a new prompt. "Based on this conversation, give me a better initial prompt that incorporates all the things we talked about." And you can do this with literally everything. And in theory, there’s so much it applies to that people do day-to-day. You could use it for tweets. You could use it for editing podcasts. You can use it for pretty much everything. I have a folder of prompts that I use all the time. My YouTube prompt is on v27 or something. I'll go through this process with all the different max models. I'll use GPT 5.2 Pro. I’ll use Grok. I'll use Claude. Then, I’ll take all the outputs from all the models and put them into Claude and say "Here’s my prompt, here’s the output from four LLMs, including yourself. Rate each response and tell me what the pros and cons of each approach are." And I usually say "give it to me in numbered form". And then you can agree with one, disagree with two, tell it three is this or that. And then after that, you say given all of this, synthesize it."

The Peel

51,632 просмотров • 6 месяцев назад

Markov Proved that Randomness With Memory Can Still Settle Into Law Markov’s 1906 result was a major turning point in Probability Theory. He showed that even when successive events are dependent, long-run averages can still stabilize. That broke the old habit of tying the Law of Large Numbers only to independence, and opened the door to a much broader Mathematics of Stochastic Systems. From there, the whole subject of Markov Chains grew into one of the central languages of modern probability. It feeds directly into Ergodic Theory, Statistical Physics, Queueing Systems, Population Models, Monte Carlo methods, Hidden Markov models, Speech Recognition, Finance, Genetics, and even web search. The idea is simple and deep at once. It shows that local randomness can still produce global regularity. The paper: А. А. Марков (1906). Распространение закона больших чисел на величины, зависящие друг от друга (Extension of The Law of Large Numbers to Dependent Quantities).

Markov Proved that Randomness With Memory Can Still Settle Into Law Markov’s 1906 result was a major turning point in Probability Theory. He showed that even when successive events are dependent, long-run averages can still stabilize. That broke the old habit of tying the Law of Large Numbers only to independence, and opened the door to a much broader Mathematics of Stochastic Systems. From there, the whole subject of Markov Chains grew into one of the central languages of modern probability. It feeds directly into Ergodic Theory, Statistical Physics, Queueing Systems, Population Models, Monte Carlo methods, Hidden Markov models, Speech Recognition, Finance, Genetics, and even web search. The idea is simple and deep at once. It shows that local randomness can still produce global regularity. The paper: А. А. Марков (1906). Распространение закона больших чисел на величины, зависящие друг от друга (Extension of The Law of Large Numbers to Dependent Quantities).

Mathelirium

15,338 просмотров • 5 месяцев назад

-> If you’re looking for a job -> right now, there are three -> Claude certifications that -> you should do this week -> and then put them on your -> LinkedIn, they are all -> completely free, and they -> come from Anthropic, -> which is the company -> that's behind Claude. -> And jobs that need AI skills -> pay 56% more than jobs -> that don’t, So, I think -> spending a few hours this -> week to knock out these -> three courses and then -> add them to your LinkedIn -> will really go a long way -> The first one is called -> Claude 101, and this -> essentially just goes over -> what Claude is and when -> you should use chat versus -> co-work versus code, how -> projects and skills work, -> and how to connect all -> of your tools and apps -> like Gmail, Notion, Slack, -> and other tools that you use -> And the second course -> is called AI Fluency -> Framework and Foundations -> Inside this one, there are -> 13 lessons on how to -> actually work with AI. -> It goes over things like -> effective prompting, critical -> thinking on the outputs, -> and it has a vocabulary -> sheet that you’ll want -> to read and save for later. -> And the third one is -> Intro to Claude Cowork -> Claude Cowork is where -> you can actually get stuff -> done with Claude. -> So, this course covers -> projects, skills, plug-ins, -> scheduling tasks, handling -> files, and then also how -> to pick the right model -> for the job, and then when -> you finish these courses, -> just go to your LinkedIn -> and go to your profile -> Click "Add section," and -> then go to "Licenses -> and certifications" and -> add all three of these. -> And then when you land -> the interview, you should -> talk about your AI fluency -> often as you possibly can -> I feel pretty confident that -> you’ll truly be able to -> differentiate yourself -> from other candidates -> if you do this

BeingInvested

13,130 просмотров • 3 месяцев назад

SELF LANGUAGE AND HEALTH How we talk about ourselves matters The power of placebo, and its opposite nocebo - means that what we believe, and how we reinforce that with our language can literally make us sick or healthy For this reason, learn to see your symptoms as a healing process, rather than the sickness itself to be avoided Be HAPPY that your body is healing and cleansing you, and your recovery will be improved because of this Once you learn the truth, that you can’t catch a cold; that it’s not a bad thing to clear out garbage (although it may feel rough), then sickness becomes much easier to handle

SELF LANGUAGE AND HEALTH How we talk about ourselves matters The power of placebo, and its opposite nocebo - means that what we believe, and how we reinforce that with our language can literally make us sick or healthy For this reason, learn to see your symptoms as a healing process, rather than the sickness itself to be avoided Be HAPPY that your body is healing and cleansing you, and your recovery will be improved because of this Once you learn the truth, that you can’t catch a cold; that it’s not a bad thing to clear out garbage (although it may feel rough), then sickness becomes much easier to handle

⚡️🌞 Sol Brah 🌞🐬

15,159 просмотров • 1 год назад

Here's how Elon Musk found out Bill Gates has no basic physics. Gates showed up at Tesla Austin certain a long-range Semi could never work. Energy density? Efficiency? He didn't have a single number. Elon Musk: "You’d think that someone like Bill Gates, who clearly started a technology company that’s one of the biggest companies in the world—Microsoft—you’d think he’d be really quite strong in the sciences. But actually, at least from my direct conversations with him, he is not strong in the sciences. This was really surprising. He came to visit me at the Tesla Gigafactory in Austin and was telling me that it’s impossible to have a long-range semi-truck. And I was like, “Well, but we literally have them. And you can drive them. And Pepsi is literally using them right now. And you can drive them yourself or send someone. Obviously, Bill Gates is not going to drive it himself, but you can send a trusted person to drive the truck and verify that it can do the things that we say it’s doing.” And he’s like, “No, no, it doesn’t work. It doesn’t work.” And I’m like, “Okay.” I’m kind of stuck there. Then I was like, “Well, so it must be that you disagree with the watt-hours per kilogram of the battery pack. You must think that perhaps we can’t achieve the energy density of the battery pack, or that the watt-hours per mile of the truck is too high, and that when you combine those two numbers, the range is low. “And so, which one of those numbers do you think we have wrong, and what numbers do you think are correct?” And he didn’t know any of the numbers. And I’m like, “Well then, doesn’t it seem that it’s perhaps premature to conclude that a long-range semi cannot work if you do not know the energy density of the battery pack or the energy efficiency of the truck chassis?”

Here's how Elon Musk found out Bill Gates has no basic physics. Gates showed up at Tesla Austin certain a long-range Semi could never work. Energy density? Efficiency? He didn't have a single number. Elon Musk: "You’d think that someone like Bill Gates, who clearly started a technology company that’s one of the biggest companies in the world—Microsoft—you’d think he’d be really quite strong in the sciences. But actually, at least from my direct conversations with him, he is not strong in the sciences. This was really surprising. He came to visit me at the Tesla Gigafactory in Austin and was telling me that it’s impossible to have a long-range semi-truck. And I was like, “Well, but we literally have them. And you can drive them. And Pepsi is literally using them right now. And you can drive them yourself or send someone. Obviously, Bill Gates is not going to drive it himself, but you can send a trusted person to drive the truck and verify that it can do the things that we say it’s doing.” And he’s like, “No, no, it doesn’t work. It doesn’t work.” And I’m like, “Okay.” I’m kind of stuck there. Then I was like, “Well, so it must be that you disagree with the watt-hours per kilogram of the battery pack. You must think that perhaps we can’t achieve the energy density of the battery pack, or that the watt-hours per mile of the truck is too high, and that when you combine those two numbers, the range is low. “And so, which one of those numbers do you think we have wrong, and what numbers do you think are correct?” And he didn’t know any of the numbers. And I’m like, “Well then, doesn’t it seem that it’s perhaps premature to conclude that a long-range semi cannot work if you do not know the energy density of the battery pack or the energy efficiency of the truck chassis?”

Doge Tipping

158,727 просмотров • 20 дней назад

YOUR WORLD IS NOT THEIR WORLD Your perspective is the lens through which you see the world And you have always control over this perspective Thus, you can create and destroy worlds in an instant - this is your power! Energy moves and flows, it is never destroyed. The levels of energy we encounter can be low, negative or high, and positive. We are a human node in a network of energy and we can be a positive transmitter or a negative one. It always reminds me of the situation of ‘a recession’ If a recession occurs, everyone freaks out and the widespread beliefs of ‘we’ll make less money, it’s harder to get a job’ become accepted by others But during The Great Depression, MANY millionaires were made. This example shows that you should always have the internal perspective that things can go well for you. Because when we filter energy and ‘the world’ through our chosen, positively intensifying one, we help those around us by magnifying the good and reflecting it back to them. And that’s a powerful thing!

YOUR WORLD IS NOT THEIR WORLD Your perspective is the lens through which you see the world And you have always control over this perspective Thus, you can create and destroy worlds in an instant - this is your power! Energy moves and flows, it is never destroyed. The levels of energy we encounter can be low, negative or high, and positive. We are a human node in a network of energy and we can be a positive transmitter or a negative one. It always reminds me of the situation of ‘a recession’ If a recession occurs, everyone freaks out and the widespread beliefs of ‘we’ll make less money, it’s harder to get a job’ become accepted by others But during The Great Depression, MANY millionaires were made. This example shows that you should always have the internal perspective that things can go well for you. Because when we filter energy and ‘the world’ through our chosen, positively intensifying one, we help those around us by magnifying the good and reflecting it back to them. And that’s a powerful thing!

⚡️🌞 Sol Brah 🌞🐬

35,837 просмотров • 2 лет назад

Naval Ravikant’s checklist for starting a company “The most important thing is there are no formulas. At the end of the day, you have to do what you love, and you have to do it even though people tell you it’ll never work. But that being said, if there was a formula [for starting a company], I would put it something like this.” Naval started seven companies before AngelList and this is the checklist he recommends running through before starting a startup: 1. Pick a great cofounder. This is most important: “You can do a company on your own, but it’s like you can raise a child on your own, but you probably shouldn’t. You need someone who’s going to be there with you.” This has it’s own checklist. Your cofounder should be: a. Very high intelligence (”hopefully they make you feel dumb, or they’re not smart enough”) b. Very high energy (”They should be extremely hardworking. A founder is someone who never has to be motivated. You should not have to be telling them to do their job.”) c. Very high integrity. (”a smart, hardworking crook who’s going to cheat you is the worst kind of person to be paired up with.”) 2. Pick a very large market. “Notice I don’t talk about the idea. I think ideas are almost irrelevant… The more important thing is that you pick a large space that you’re knowledgeable and passionate about. And then you will figure out what the right thing to do within that space is.” You want to be able to say to investors: “This is a space where there’s a huge market. I’m really knowledgeable and passionate about it. Here’s the great person that I have doing it with me. And here’s the minimum viable product that we have built. That will show that we can test in the marketplace… You iterate until you get to product/market fit… And then you go and you raise money from people you trust. And you use that money to scale.”

Naval Ravikant’s checklist for starting a company “The most important thing is there are no formulas. At the end of the day, you have to do what you love, and you have to do it even though people tell you it’ll never work. But that being said, if there was a formula [for starting a company], I would put it something like this.” Naval started seven companies before AngelList and this is the checklist he recommends running through before starting a startup: 1. Pick a great cofounder. This is most important: “You can do a company on your own, but it’s like you can raise a child on your own, but you probably shouldn’t. You need someone who’s going to be there with you.” This has it’s own checklist. Your cofounder should be: a. Very high intelligence (”hopefully they make you feel dumb, or they’re not smart enough”) b. Very high energy (”They should be extremely hardworking. A founder is someone who never has to be motivated. You should not have to be telling them to do their job.”) c. Very high integrity. (”a smart, hardworking crook who’s going to cheat you is the worst kind of person to be paired up with.”) 2. Pick a very large market. “Notice I don’t talk about the idea. I think ideas are almost irrelevant… The more important thing is that you pick a large space that you’re knowledgeable and passionate about. And then you will figure out what the right thing to do within that space is.” You want to be able to say to investors: “This is a space where there’s a huge market. I’m really knowledgeable and passionate about it. Here’s the great person that I have doing it with me. And here’s the minimum viable product that we have built. That will show that we can test in the marketplace… You iterate until you get to product/market fit… And then you go and you raise money from people you trust. And you use that money to scale.”

Startup Archive

36,050 просмотров • 1 год назад

This is one of my favorite movie endings... It has a powerful lesson: "At some point, everything is going to go south on you...and you're gonna say 'this is it, this is how I end.' Now you can either accept that, or you can get to work. That's all it is, you just begin. You do the math. You solve one problem. Then you solve the next one. And the next. And if you solve enough problems, you get to come home." This is the beautiful thing about life: No matter where you are today—no matter how deep in the darkness—you are always just one good decision away from being in a better place tomorrow. You can always focus on that one decision—that one problem—in front of you. Don't worry about the hundreds or thousands of decisions that you still have to make to get to where you want to be—just focus on the next decision. Just begin. Solve one problem. Then solve the next one. And the next. "Life is really simple, but we insist on making it complicated." - Confucius

This is one of my favorite movie endings... It has a powerful lesson: "At some point, everything is going to go south on you...and you're gonna say 'this is it, this is how I end.' Now you can either accept that, or you can get to work. That's all it is, you just begin. You do the math. You solve one problem. Then you solve the next one. And the next. And if you solve enough problems, you get to come home." This is the beautiful thing about life: No matter where you are today—no matter how deep in the darkness—you are always just one good decision away from being in a better place tomorrow. You can always focus on that one decision—that one problem—in front of you. Don't worry about the hundreds or thousands of decisions that you still have to make to get to where you want to be—just focus on the next decision. Just begin. Solve one problem. Then solve the next one. And the next. "Life is really simple, but we insist on making it complicated." - Confucius

Sahil Bloom

213,822 просмотров • 2 лет назад

2 Minutes before the launch of the Public sale !!! Remember: FCFS Here is a little tutorial to guide you: Remember the only website you have to use to participate to the public sale today is : How will it work ? 1⃣Go to : And click on "Invest in Elys Network" 2⃣You will then see the different whitelists : 30% / 15% / public sale choose the one available to you, if you are whitelisted for the 30% you'll be able to take the 30% deal. 3⃣Once this is done, put in the amount you want to invest, make sure you've checked all the information, accept all the conditions and click Confirm Investment. 4⃣Now you will see a new page on which you will asked to submit your cosmos wallet. Do the process, create your 2FA and then copy / Pasta your cosmos address (make sure that your address is starting with Cosmos and take the time to verify it) you can find your address on keplr. 5⃣After that you will have to do your investment for that click on "Complete paiement" make sure that the chain you choose is the one you want to use (click on edit if it's not the case) and Copy the address below. 6⃣Go on your Metamask / Rabby / Phantom wallet and use the send function to send your paiement to republic. You can find also a little tutorial for Rabby and Metamask at the end of the video In every step of the process make sure that : ◾️ You are using the right cosmos address, the one you want to use on mainnet. ◾️ You are using the right address to send the funds to Republic Here is a little video to guide you if you need help. Also if you need more guidance please come to us on discord or here on X and we will help you !

2 Minutes before the launch of the Public sale !!! Remember: FCFS Here is a little tutorial to guide you: Remember the only website you have to use to participate to the public sale today is : How will it work ? 1⃣Go to : And click on "Invest in Elys Network" 2⃣You will then see the different whitelists : 30% / 15% / public sale choose the one available to you, if you are whitelisted for the 30% you'll be able to take the 30% deal. 3⃣Once this is done, put in the amount you want to invest, make sure you've checked all the information, accept all the conditions and click Confirm Investment. 4⃣Now you will see a new page on which you will asked to submit your cosmos wallet. Do the process, create your 2FA and then copy / Pasta your cosmos address (make sure that your address is starting with Cosmos and take the time to verify it) you can find your address on keplr. 5⃣After that you will have to do your investment for that click on "Complete paiement" make sure that the chain you choose is the one you want to use (click on edit if it's not the case) and Copy the address below. 6⃣Go on your Metamask / Rabby / Phantom wallet and use the send function to send your paiement to republic. You can find also a little tutorial for Rabby and Metamask at the end of the video In every step of the process make sure that : ◾️ You are using the right cosmos address, the one you want to use on mainnet. ◾️ You are using the right address to send the funds to Republic Here is a little video to guide you if you need help. Also if you need more guidance please come to us on discord or here on X and we will help you !

Elys Network

25,378 просмотров • 1 год назад

Vitalik Buterin on why consortium blockchains have mostly failed “The original vision of consortium blockchains — the idea that you have 5 banks or major companies that come together and create their own chain — has been mostly a failure. I think the reason why is it ends up inheriting most of the disadvantages of centralization and most of the disadvantages of decentralization at the same time.” “The first five banks join, and they all feel like ‘Yay, we’re building a system together. We can all be part of it.’ But then once bank #6 and bank #7 and bank #29 come in, they’re joining a system where there’s already an established power structure, established participants, and basically to them it still feels like they’re joining some kind of centralized thing that’s controlled by a cartel.” “You don’t actually gain the benefits of true openness that people are looking for. You don’t have Etherscan. You don’t have a connection to an open, public network. At the same time, if you build on one of those systems, you have to figure out how to program distributed systems; you lose privacy — you might think you still have some, but the reality is you’re putting your data on a network where the only people that get to see it are you and all your closest competitors. From a privacy perspective, it actually doesn’t make much sense.” “The compromise between centralization and decentralization that actually makes a lot more sense is: you have an application and today that application is a server. You can keep your server, but instead, we’re going to add scaffolding on top to give users extra security guarantees. You put Merkle roots on chain. You put proofs on chain. And you give your users assurance that whatever is happening inside of your system is actually following the rules. So you have high scale, high performance, and you optimize for a minimal delta for existing centralized infrastructure deployment. Keep your existing infrastructure the way it is, and you just add a side car that makes the roots and the proofs.” Source: Arbitrum

Vitalik Buterin on why consortium blockchains have mostly failed “The original vision of consortium blockchains — the idea that you have 5 banks or major companies that come together and create their own chain — has been mostly a failure. I think the reason why is it ends up inheriting most of the disadvantages of centralization and most of the disadvantages of decentralization at the same time.” “The first five banks join, and they all feel like ‘Yay, we’re building a system together. We can all be part of it.’ But then once bank #6 and bank #7 and bank #29 come in, they’re joining a system where there’s already an established power structure, established participants, and basically to them it still feels like they’re joining some kind of centralized thing that’s controlled by a cartel.” “You don’t actually gain the benefits of true openness that people are looking for. You don’t have Etherscan. You don’t have a connection to an open, public network. At the same time, if you build on one of those systems, you have to figure out how to program distributed systems; you lose privacy — you might think you still have some, but the reality is you’re putting your data on a network where the only people that get to see it are you and all your closest competitors. From a privacy perspective, it actually doesn’t make much sense.” “The compromise between centralization and decentralization that actually makes a lot more sense is: you have an application and today that application is a server. You can keep your server, but instead, we’re going to add scaffolding on top to give users extra security guarantees. You put Merkle roots on chain. You put proofs on chain. And you give your users assurance that whatever is happening inside of your system is actually following the rules. So you have high scale, high performance, and you optimize for a minimal delta for existing centralized infrastructure deployment. Keep your existing infrastructure the way it is, and you just add a side car that makes the roots and the proofs.” Source: Arbitrum

Etherealize

131,518 просмотров • 3 месяцев назад

Why did so many languages copy async/await from C#? Anders Hejlsberg(Anders Hejlsberg) - 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."

Why did so many languages copy async/await from C#? Anders Hejlsberg(Anders Hejlsberg) - 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."

The Pragmatic Engineer

13,258 просмотров • 3 месяцев назад

This is one way they're going to fill those ICE warehouses IMO: "With PCR [they] can declare you a carrier of any possible virus...[and] certain viruses are... written into law as quarantineable.... [So they can] violate your constitutional rights and imprison you without due cause." This clip of retired pharma R&D executive Sasha Latypova (sashalatypova.substack.com "Due Diligence and Art") is taken from an interview with Shannon Joy (Shannon Joy) posted to Rumble on February 10, 2026. ----------------Partial transcription of clip--------------- "With PCR, we can declare you a carrier of any possible virus. Any possible virus on the planet existing now, imaginary, non-imaginary, the one we just drew in a cartoon. We can diagnose you with that virus with the PCR, and then depends on how. "And also the US law is set out such a way that certain viruses are actually written into law as quarantineable. And quarantineable means the government can violate your constitutional rights and imprison you without due cause. And this is why they build those centers in the marketplace mall, by the way. "So this, the detention center. There are several viruses, including influenza and Covid and a few others that are written into the US Law that gives CDC and the military unlimited power to. To detain you, take you off a cruise ship like, just like they did with those, Grand Princes and, the other. Yeah, International Princess. I forget those two. And, send you to the military base where you will be treated against your will and killed there and then declared you dead from COVID or disease acts or whatever next virus we're going to have on the menu. "And so that's why. That's why these, these are, you know, these are not just to harvest people's bodies. That's. That's a given. Yeah, they've been doing that, that for ages. Now this is also designed to imprison anyone by declaring them a carrier of a, of an emergency threat virus. And so imprison any dissident, anybody the state wants to get rid of is a perfectly easy way to do... And also broadly establish control measures. "So if they want to roll out CBDC programmable money, this is a way to do it, by tying it to your health records. They already tying everything to the. To the health records. They're already centrally collecting all the health data through the electronic medical records, which. Which, you know, technically the practice of medicine, including these electronic medical records, supposed to be a purview of the state regulation, not federal regulation. But... we have blown past that a long time ago. "And now all these records, health records, have been centrally sucked into federal databases, which are then turned over to Palantir to target you, to the sum up, to AI, to set up some AI to surveil you. So now they can force you, especially with people with children, they can threaten them, and you've been participating in those, in those cases many times where they can threaten the parent if they deny some sort of a health intervention. "And, you know, and parents will comply just because they're afraid for their children. But guess what? They can also test your child for some novel virus. Find it, and then you. And then you become it. Then you become the sentinel case. Then you become that case that they need to demonstrate there is a pandemic... Lock down the whole community, do whatever they wish there. It becomes an unlimited scenario for totalitarian dystopia."

This is one way they're going to fill those ICE warehouses IMO: "With PCR [they] can declare you a carrier of any possible virus...[and] certain viruses are... written into law as quarantineable.... [So they can] violate your constitutional rights and imprison you without due cause." This clip of retired pharma R&D executive Sasha Latypova (sashalatypova.substack.com "Due Diligence and Art") is taken from an interview with Shannon Joy (Shannon Joy) posted to Rumble on February 10, 2026. ----------------Partial transcription of clip--------------- "With PCR, we can declare you a carrier of any possible virus. Any possible virus on the planet existing now, imaginary, non-imaginary, the one we just drew in a cartoon. We can diagnose you with that virus with the PCR, and then depends on how. "And also the US law is set out such a way that certain viruses are actually written into law as quarantineable. And quarantineable means the government can violate your constitutional rights and imprison you without due cause. And this is why they build those centers in the marketplace mall, by the way. "So this, the detention center. There are several viruses, including influenza and Covid and a few others that are written into the US Law that gives CDC and the military unlimited power to. To detain you, take you off a cruise ship like, just like they did with those, Grand Princes and, the other. Yeah, International Princess. I forget those two. And, send you to the military base where you will be treated against your will and killed there and then declared you dead from COVID or disease acts or whatever next virus we're going to have on the menu. "And so that's why. That's why these, these are, you know, these are not just to harvest people's bodies. That's. That's a given. Yeah, they've been doing that, that for ages. Now this is also designed to imprison anyone by declaring them a carrier of a, of an emergency threat virus. And so imprison any dissident, anybody the state wants to get rid of is a perfectly easy way to do... And also broadly establish control measures. "So if they want to roll out CBDC programmable money, this is a way to do it, by tying it to your health records. They already tying everything to the. To the health records. They're already centrally collecting all the health data through the electronic medical records, which. Which, you know, technically the practice of medicine, including these electronic medical records, supposed to be a purview of the state regulation, not federal regulation. But... we have blown past that a long time ago. "And now all these records, health records, have been centrally sucked into federal databases, which are then turned over to Palantir to target you, to the sum up, to AI, to set up some AI to surveil you. So now they can force you, especially with people with children, they can threaten them, and you've been participating in those, in those cases many times where they can threaten the parent if they deny some sort of a health intervention. "And, you know, and parents will comply just because they're afraid for their children. But guess what? They can also test your child for some novel virus. Find it, and then you. And then you become it. Then you become the sentinel case. Then you become that case that they need to demonstrate there is a pandemic... Lock down the whole community, do whatever they wish there. It becomes an unlimited scenario for totalitarian dystopia."

Sense Receptor

14,513 просмотров • 7 месяцев назад

I was watching a lecture on YouTube by David Tse from Stanford (see link below), and he quoted his advisor Bob Gallager: "Good theory should prune rather than grow the knowledge tree." To demonstrate what Gallager meant, we takes one idea… "how do you move mass from one shape to another as cheaply as possible?" and watch 200 years of mathematics cut that idea down to its clean geometric core. Monge (1781, "Mémoire sur la théorie des déblais et des remblais") A mound on the left, a trench on the right, and every grain of earth has to choose one destination and stick to it. In the animation that’s strict one-to-one matching: each point marches to a single partner, no splitting, no sharing. It’s beautiful but rigid and hard to work with. Kantorovich (1942, "On the Translocation of Masses"; 1948, "On a Problem of Monge") Kantorovich relaxes the rules. Instead of forcing each point to pick exactly one target, he allows mass to split: part of it can go here, part of it can go there. On screen you see packets of mass spraying from one source cell to several targets along smooth arcs. The problem becomes a clean convex optimisation problem. Brenier (1991, "Polar factorization and monotone rearrangement of vector-valued functions"); McCann (1995, "Existence and uniqueness of monotone measure-preserving maps"; 1997, "A convexity principle for interacting gases") Bernier then shows that, in the most natural cost setting, the best way to move mass always comes from a hidden height function whose slopes tell you where to send things. McCann shows that many natural energy functionals behave nicely along the paths generated this way. In the animation you see contour lines of that hidden landscape, with particles gliding along the most economical path between the two shapes. Jordan-Kinderlehrer-Otto (1998, "The variational formulation of the Fokker-Planck equation") JKO change the question from "what is the best single shuffle?" to "how does a whole cloud evolve in time?". They show that a familiar diffusion-with-drift equation can be reinterpreted as steepest descent of a free energy in the space of probability distributions. In the scene, a blob both smooths out and gets pulled toward the embankment while a free-energy counter steadily drops. Ambrosio-Gagli-Savaré (2005, "Gradient flows in metric spaces and in the spaces of probability measures") Ambrosio-Gigli-Savaré take that idea and generalise it far beyond this one setting. They build a theory of gradient flows on abstract metric spaces: you only need a notion of distance and an energy, and you can talk about curves of maximal slope. Wasserstein spaces become one important example among many. In the final scene the probability field evolves in the top panel while its energy traces a clean descending curve below.

I was watching a lecture on YouTube by David Tse from Stanford (see link below), and he quoted his advisor Bob Gallager: "Good theory should prune rather than grow the knowledge tree." To demonstrate what Gallager meant, we takes one idea… "how do you move mass from one shape to another as cheaply as possible?" and watch 200 years of mathematics cut that idea down to its clean geometric core. Monge (1781, "Mémoire sur la théorie des déblais et des remblais") A mound on the left, a trench on the right, and every grain of earth has to choose one destination and stick to it. In the animation that’s strict one-to-one matching: each point marches to a single partner, no splitting, no sharing. It’s beautiful but rigid and hard to work with. Kantorovich (1942, "On the Translocation of Masses"; 1948, "On a Problem of Monge") Kantorovich relaxes the rules. Instead of forcing each point to pick exactly one target, he allows mass to split: part of it can go here, part of it can go there. On screen you see packets of mass spraying from one source cell to several targets along smooth arcs. The problem becomes a clean convex optimisation problem. Brenier (1991, "Polar factorization and monotone rearrangement of vector-valued functions"); McCann (1995, "Existence and uniqueness of monotone measure-preserving maps"; 1997, "A convexity principle for interacting gases") Bernier then shows that, in the most natural cost setting, the best way to move mass always comes from a hidden height function whose slopes tell you where to send things. McCann shows that many natural energy functionals behave nicely along the paths generated this way. In the animation you see contour lines of that hidden landscape, with particles gliding along the most economical path between the two shapes. Jordan-Kinderlehrer-Otto (1998, "The variational formulation of the Fokker-Planck equation") JKO change the question from "what is the best single shuffle?" to "how does a whole cloud evolve in time?". They show that a familiar diffusion-with-drift equation can be reinterpreted as steepest descent of a free energy in the space of probability distributions. In the scene, a blob both smooths out and gets pulled toward the embankment while a free-energy counter steadily drops. Ambrosio-Gagli-Savaré (2005, "Gradient flows in metric spaces and in the spaces of probability measures") Ambrosio-Gigli-Savaré take that idea and generalise it far beyond this one setting. They build a theory of gradient flows on abstract metric spaces: you only need a notion of distance and an energy, and you can talk about curves of maximal slope. Wasserstein spaces become one important example among many. In the final scene the probability field evolves in the top panel while its energy traces a clean descending curve below.

Mathelirium

65,705 просмотров • 9 месяцев назад

.Naval: Epistemology, which is a fancy word for the theory of how knowledge grows or how knowledge growth occurs. And we've all been told since we're young that there's a scientific method and that scientists sort of do this stuff in white lab coats and we're supposed to accept it because of this thing called the scientific method. And then they give us true beliefs that we can then say, well the science is settled and we take that we move on. And we all only have a very, very vague understanding of how this works. And people say, well maybe you go out in the real world, you look at what's happening, you make all these observations, and then based on that you form a theory, you test the theory against more observations, and the more observations you get the closer you get to the truth. And once you have enough observation it's true and then you call it a scientific theory or a law and it's settled and you move on. And this is the popular conception of how science works. And as Popper pointed out and as you take even further, this is completely wrong. And so I'd love for you to get into that, which is what is knowledge? How does it grow? What is the real scientific method? And how do we figure things out? David Deutsch: I love the way you just stated the prevailing view there and laced every aspect of it with the contempt that it deserves. So you just went through touching every base. It's amazing that this series of misconceptions is still common sense. I mean, that it was common sense at a time when we didn't really have science or when science was just starting up, when the main issue in science was freeing itself from dogmatism, freeing itself from religion, freeing itself from authority, and so on. There it was understandable that people would look for an alternative source of authority and they would think, oh, it's sense impressions. We can see the world and you know, these religious people, they can't even see God and so on. And so we are confined to what we can see. That's where we get our ideas from. And as you say, that is completely false. Sense impressions, like all observation, even the most careful scientific observation is all theory laden. And theories are inherently fallible. I mean, we actually want to replace our best theories. Everybody who does a PhD is technically anyway, working to overturn something in the existing body of knowledge. You're not turned away at the door if you say, I don't believe this stuff, I'm going to produce something better. Whereas for most of human history, that was exactly what you were forbidden to do. The idea was that we already had all the important knowledge. If you want to discover something new, what you had to make sure of was that it didn't contradict the existing knowledge. Now, you have to make sure that it does contradict existing knowledge. So more or less. Naval: Yeah, it's this tradition of criticism that you've talked about in the West, that the Enlightenment really ushered in the Enlightenment era. David Deutsch: It has been institutionalized. So in many ways, our institutions are wiser than we are. So the institutions of science, for instance, have this built in, even if scientists actually don't always act that way. In fact, they often don't act that way, and act in a dogmatic way and try to preserve the status quo and are resistant to new ideas and so on. But the institutions, the way the procedures of science work, makes the right thing happen in the end anyway, regardless of what the people are trying to do. Naval: So you're saying the knowledge of the true scientific method is embedded in the institutions of science in the PhD process? David Deutsch: Well, the best scientific method that we know of, and one shouldn't really think of it as a method, you know, there's this wonderful lecture by Popper when he first was made a professor at the London School of Economics. He was made a professor of scientific method, and his first six lectures, I wish the rest of them were, the first six lectures are on the internet somewhere. And he starts the first one by saying, I am the first professor of scientific method in the British Empire. The British Empire still existed at the time, more or less. And so the first thing I want to say to you is that there is no such thing as the scientific method. And then he goes on from there. So this subject does not exist. So if any of you have come here to learn the handle that you have to turn in order to make scientific knowledge come out the other end, you're going to be disappointed.

.Naval: Epistemology, which is a fancy word for the theory of how knowledge grows or how knowledge growth occurs. And we've all been told since we're young that there's a scientific method and that scientists sort of do this stuff in white lab coats and we're supposed to accept it because of this thing called the scientific method. And then they give us true beliefs that we can then say, well the science is settled and we take that we move on. And we all only have a very, very vague understanding of how this works. And people say, well maybe you go out in the real world, you look at what's happening, you make all these observations, and then based on that you form a theory, you test the theory against more observations, and the more observations you get the closer you get to the truth. And once you have enough observation it's true and then you call it a scientific theory or a law and it's settled and you move on. And this is the popular conception of how science works. And as Popper pointed out and as you take even further, this is completely wrong. And so I'd love for you to get into that, which is what is knowledge? How does it grow? What is the real scientific method? And how do we figure things out? David Deutsch: I love the way you just stated the prevailing view there and laced every aspect of it with the contempt that it deserves. So you just went through touching every base. It's amazing that this series of misconceptions is still common sense. I mean, that it was common sense at a time when we didn't really have science or when science was just starting up, when the main issue in science was freeing itself from dogmatism, freeing itself from religion, freeing itself from authority, and so on. There it was understandable that people would look for an alternative source of authority and they would think, oh, it's sense impressions. We can see the world and you know, these religious people, they can't even see God and so on. And so we are confined to what we can see. That's where we get our ideas from. And as you say, that is completely false. Sense impressions, like all observation, even the most careful scientific observation is all theory laden. And theories are inherently fallible. I mean, we actually want to replace our best theories. Everybody who does a PhD is technically anyway, working to overturn something in the existing body of knowledge. You're not turned away at the door if you say, I don't believe this stuff, I'm going to produce something better. Whereas for most of human history, that was exactly what you were forbidden to do. The idea was that we already had all the important knowledge. If you want to discover something new, what you had to make sure of was that it didn't contradict the existing knowledge. Now, you have to make sure that it does contradict existing knowledge. So more or less. Naval: Yeah, it's this tradition of criticism that you've talked about in the West, that the Enlightenment really ushered in the Enlightenment era. David Deutsch: It has been institutionalized. So in many ways, our institutions are wiser than we are. So the institutions of science, for instance, have this built in, even if scientists actually don't always act that way. In fact, they often don't act that way, and act in a dogmatic way and try to preserve the status quo and are resistant to new ideas and so on. But the institutions, the way the procedures of science work, makes the right thing happen in the end anyway, regardless of what the people are trying to do. Naval: So you're saying the knowledge of the true scientific method is embedded in the institutions of science in the PhD process? David Deutsch: Well, the best scientific method that we know of, and one shouldn't really think of it as a method, you know, there's this wonderful lecture by Popper when he first was made a professor at the London School of Economics. He was made a professor of scientific method, and his first six lectures, I wish the rest of them were, the first six lectures are on the internet somewhere. And he starts the first one by saying, I am the first professor of scientific method in the British Empire. The British Empire still existed at the time, more or less. And so the first thing I want to say to you is that there is no such thing as the scientific method. And then he goes on from there. So this subject does not exist. So if any of you have come here to learn the handle that you have to turn in order to make scientific knowledge come out the other end, you're going to be disappointed.

Deutsch Explains

116,352 просмотров • 1 год назад

Mati Staniszewski on why ElevenLabs is betting on a cascaded approach for voice agents: “Our approach, as you think about voice agents, conversational agents, is effectively a cascaded approach. You use transcription or speech-to-text, an LLM, text-to-speech, and orchestrate all of that together. Then you have speech-to-speech, which goes directly from speech, and there’s a speech response on the other side. Today, we are optimizing heavily on a cascaded approach. As we work with a lot of the businesses and enterprises, they will need that visibility into what happens. They will want to execute certain tasks on top of that. They want good visibility into each of the steps and great accuracy of all the models. But beyond that, they can abstract away what’s the LLM layer, what’s the intelligence layer, and the integrations are easier in that system. That’s where we are betting a lot of the research work on how you can make that great, and we think we can make that great.” John Collison @matiii ElevenLabs

Mati Staniszewski on why ElevenLabs is betting on a cascaded approach for voice agents: “Our approach, as you think about voice agents, conversational agents, is effectively a cascaded approach. You use transcription or speech-to-text, an LLM, text-to-speech, and orchestrate all of that together. Then you have speech-to-speech, which goes directly from speech, and there’s a speech response on the other side. Today, we are optimizing heavily on a cascaded approach. As we work with a lot of the businesses and enterprises, they will need that visibility into what happens. They will want to execute certain tasks on top of that. They want good visibility into each of the steps and great accuracy of all the models. But beyond that, they can abstract away what’s the LLM layer, what’s the intelligence layer, and the integrations are easier in that system. That’s where we are betting a lot of the research work on how you can make that great, and we think we can make that great.” John Collison @matiii ElevenLabs

Stripe

18,535 просмотров • 5 месяцев назад

Mike Dunleavy Jr. says the Warriors are not in a situation to fix everything in free agency but they’re looking to put together a good team going into training camp: “I think there’s where you want to be in September when training camp starts, and there’s where you want to be in the spring as you try and compete for the postseason and get in the postseason. We have a couple transaction cycles here in the summer and then once again in February where we feel like we can build and maximize our team. And so I think the biggest thing is to put together a good team going into camp. And as I mentioned before, a lot of the improvement for us is going to have to come from within our habits, taking care of the ball, doing the little things. Get that knocked out, you get on your way to having a good season. We need to stay healthy and then get those guys (Jimmy & Moses) back, and then we’ll see at the trade deadline and we’ll evaluate everything. But this is not a fix-everything over the next couple weeks in free agency. We’re not in that situation based on some stuff we have going on, but we can get a lot better. We can have a good start to the season, and we can be in really good shape to make a run. But we got to get off to a good start.” (via NBC Sports Bay Area & CA with Bonta Hill and Monte Poole)

Mike Dunleavy Jr. says the Warriors are not in a situation to fix everything in free agency but they’re looking to put together a good team going into training camp: “I think there’s where you want to be in September when training camp starts, and there’s where you want to be in the spring as you try and compete for the postseason and get in the postseason. We have a couple transaction cycles here in the summer and then once again in February where we feel like we can build and maximize our team. And so I think the biggest thing is to put together a good team going into camp. And as I mentioned before, a lot of the improvement for us is going to have to come from within our habits, taking care of the ball, doing the little things. Get that knocked out, you get on your way to having a good season. We need to stay healthy and then get those guys (Jimmy & Moses) back, and then we’ll see at the trade deadline and we’ll evaluate everything. But this is not a fix-everything over the next couple weeks in free agency. We’re not in that situation based on some stuff we have going on, but we can get a lot better. We can have a good start to the season, and we can be in really good shape to make a run. But we got to get off to a good start.” (via NBC Sports Bay Area & CA with Bonta Hill and Monte Poole)

aly ✶

54,924 просмотров • 2 месяцев назад

We're Basically Being Asked To Believe That The Palestinians Are Genociding Themselves One of the dumbest things we are asked to believe about Israel’s genocide in Gaza is that all these civilians are being butchered because the Palestinians are evil and not the Israelis. That it’s the victims doing evil things and not the perpetrators. That’s all this gibberish about “human shields” and “self-defense” is meant to do, you know. To make it look like the victims of siege warfare and carpet bombing are the ones responsible for all the death and destruction we are seeing and not the people who are actually doing it. Can you think of anything more insulting to your intelligence? So self-evidently counter to common sense? They’re seriously asking you to believe that the people who are being starved, shot and bombed to death are the perpetrators of their own genocide, and that the side which has attacked every hospital in Gaza are just the innocent bystanders responding to unprovoked acts of aggression in the most ethical and responsible way they can manage. Off the top of my head I really can’t think of anything more absurd. Reading by Tim Foley.

We're Basically Being Asked To Believe That The Palestinians Are Genociding Themselves One of the dumbest things we are asked to believe about Israel’s genocide in Gaza is that all these civilians are being butchered because the Palestinians are evil and not the Israelis. That it’s the victims doing evil things and not the perpetrators. That’s all this gibberish about “human shields” and “self-defense” is meant to do, you know. To make it look like the victims of siege warfare and carpet bombing are the ones responsible for all the death and destruction we are seeing and not the people who are actually doing it. Can you think of anything more insulting to your intelligence? So self-evidently counter to common sense? They’re seriously asking you to believe that the people who are being starved, shot and bombed to death are the perpetrators of their own genocide, and that the side which has attacked every hospital in Gaza are just the innocent bystanders responding to unprovoked acts of aggression in the most ethical and responsible way they can manage. Off the top of my head I really can’t think of anything more absurd. Reading by Tim Foley.

Caitlin Johnstone

113,731 просмотров • 1 год назад

Your worst thoughts are not your enemies. They are just bad chemistry. And chemistry can be changed. Your body and nervous system can be brought into a balance from which you can tap into endless inspiration. You can set yourself up to get rid of those negative thoughts and replace them with moments of inspiration. How? By utilizing nature to change your body’s chemistry. Dip your hands in icy water. Take a cold shower. Stand barefoot in the winter air for a few minutes. The cold strips away distractions and quiets the mental noise. This is not comfortable nor easy. But in that sharp experience, something shifts. The daily routine and worries seem less relevant. The cold forces your presence to this intense moment. Clarity. Fresh and undeniable. The cold doesn't judge you. It doesn't care about your status, your achievements, your failures. You show up as you are to meet it. Nothing else matters in that moment. And in that meeting, your neurology changes. The cold is really it. Together with the breathing. I will guide you. -Wim

Your worst thoughts are not your enemies. They are just bad chemistry. And chemistry can be changed. Your body and nervous system can be brought into a balance from which you can tap into endless inspiration. You can set yourself up to get rid of those negative thoughts and replace them with moments of inspiration. How? By utilizing nature to change your body’s chemistry. Dip your hands in icy water. Take a cold shower. Stand barefoot in the winter air for a few minutes. The cold strips away distractions and quiets the mental noise. This is not comfortable nor easy. But in that sharp experience, something shifts. The daily routine and worries seem less relevant. The cold forces your presence to this intense moment. Clarity. Fresh and undeniable. The cold doesn't judge you. It doesn't care about your status, your achievements, your failures. You show up as you are to meet it. Nothing else matters in that moment. And in that meeting, your neurology changes. The cold is really it. Together with the breathing. I will guide you. -Wim

Wim Hof

14,307 просмотров • 4 месяцев назад