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a quant at Two Sigma told me something at a bar i can't stop thinking about "retail looks at price. we look at the autocorrelation of price changes - completely different signal" i asked him to explain it like i was 12 he drew on a napkin: if today's...

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Livsun

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a quant at a prop firm showed me a 5x5 grid on a napkin said: > this is our entire edge. we don't predict price. we predict which box the market is in and where that box historically leads i didn't understand it for weeks. then it clicked never looked at a chart the same way since grid is called a Markov Chain transition matrix. the math is from 1906, it's in every probability textbook on earth and hedge funds use it because it asks a completely different question than retail traders ever ask retail: will this go up or down quant: what state is this market in, and where does this state typically go every market lives in one of maybe 5-6 states at any given moment tight range, volatility compression, trending with momentum, post-spike reversal, pre-breakout coil not random labels - clusters you identify from actual data using volatility, volume, and momentum readings stacked together once you have the states, you build the matrix: P(state 2 -> state 4) = 73% P(state 4 -> state 1) = 61% P(state 1 -> state 3) = 68% each cell is a historical probability. now when the market is in state 2, you're not guessing you're betting on 73% historical completion. you size it with Kelly. you take the trade when the math says to, not when it feels right i built this on BTC using 2 years of 4-hour data. identified 5 states one i labeled "volatility compression below 20-day mean for 6+ consecutive candles" transitioned to a directional move above 1.8 ATR in 71% of cases average reward/risk on those trades: 5.4 that's not prediction. that's reading a probability table the market keeps filling in for you every single day the part that should bother you: the data to build this is free. the framework is in any quant textbook python to implement it is maybe 200 lines what Renaissance Technologies has that you don't isn't secret data or proprietary signals it's this framework applied to higher-resolution data with more sophisticated state definitions you're not missing information you're asking the wrong question every single time you open a chart
0:26

a quant at a prop firm showed me a 5x5 grid on a napkin said: > this is our entire edge. we don't predict price. we predict which box the market is in and where that box historically leads i didn't understand it for weeks. then it clicked never looked at a chart the same way since grid is called a Markov Chain transition matrix. the math is from 1906, it's in every probability textbook on earth and hedge funds use it because it asks a completely different question than retail traders ever ask retail: will this go up or down quant: what state is this market in, and where does this state typically go every market lives in one of maybe 5-6 states at any given moment tight range, volatility compression, trending with momentum, post-spike reversal, pre-breakout coil not random labels - clusters you identify from actual data using volatility, volume, and momentum readings stacked together once you have the states, you build the matrix: P(state 2 -> state 4) = 73% P(state 4 -> state 1) = 61% P(state 1 -> state 3) = 68% each cell is a historical probability. now when the market is in state 2, you're not guessing you're betting on 73% historical completion. you size it with Kelly. you take the trade when the math says to, not when it feels right i built this on BTC using 2 years of 4-hour data. identified 5 states one i labeled "volatility compression below 20-day mean for 6+ consecutive candles" transitioned to a directional move above 1.8 ATR in 71% of cases average reward/risk on those trades: 5.4 that's not prediction. that's reading a probability table the market keeps filling in for you every single day the part that should bother you: the data to build this is free. the framework is in any quant textbook python to implement it is maybe 200 lines what Renaissance Technologies has that you don't isn't secret data or proprietary signals it's this framework applied to higher-resolution data with more sophisticated state definitions you're not missing information you're asking the wrong question every single time you open a chart

Livsun

187,776 Aufrufe • vor 1 Monat

100 billion dollars made without predicting a single price direction not a direction call, a macro bet, or a news trade in sight they asked a completely different question than every retail trader alive retail: "will this go up?" quant: "what state is the market in, and where does that state historically lead?" same data. completely different game markets aren't random - they cycle through states: trending, ranging, compressing, reversing each state has a fixed historical probability of transitioning to the next that's the whole edge. not a signal, not an indicator - just conditional probability you don't need to know what fed will do or what earnings will print you need to know which state you're in and what that state leads to 68% of the time framework has been public since 1906 Bookmark it before it gone data is free, implementation is 200 lines of python, paper costs nothing they built 100 billion off math sitting in statistics textbooks your whole life you were staring at candles while they ran probability tables
0:52

100 billion dollars made without predicting a single price direction not a direction call, a macro bet, or a news trade in sight they asked a completely different question than every retail trader alive retail: "will this go up?" quant: "what state is the market in, and where does that state historically lead?" same data. completely different game markets aren't random - they cycle through states: trending, ranging, compressing, reversing each state has a fixed historical probability of transitioning to the next that's the whole edge. not a signal, not an indicator - just conditional probability you don't need to know what fed will do or what earnings will print you need to know which state you're in and what that state leads to 68% of the time framework has been public since 1906 Bookmark it before it gone data is free, implementation is 200 lines of python, paper costs nothing they built 100 billion off math sitting in statistics textbooks your whole life you were staring at candles while they ran probability tables

Livsun

13,335 Aufrufe • vor 14 Tagen

a russian mathematician solved trading in 1906 wall street found the paper 70 years later, built billion-dollar funds around it, never mentioned it to retail andrei markov proved markets aren't random - they're state machines trending, ranging, reversing - each state has a fixed historical probability of shifting to the next build a transition matrix from real data: trending -> stays trending: 68% trending -> flips to range: 21% trending -> reverses: 11% now you're not predicting direction. you're entering on 68% historical completion identify your state, size with kelly, take the trade when math says yes that's the edge. the whole edge renaissance has run this since 1988. 37 years of 66% annual returns paper is free, data is free, implementation is 200 lines of python Bookmark and use in your own strategy they kept you staring at candles while they ran probability tables
2:30

a russian mathematician solved trading in 1906 wall street found the paper 70 years later, built billion-dollar funds around it, never mentioned it to retail andrei markov proved markets aren't random - they're state machines trending, ranging, reversing - each state has a fixed historical probability of shifting to the next build a transition matrix from real data: trending -> stays trending: 68% trending -> flips to range: 21% trending -> reverses: 11% now you're not predicting direction. you're entering on 68% historical completion identify your state, size with kelly, take the trade when math says yes that's the edge. the whole edge renaissance has run this since 1988. 37 years of 66% annual returns paper is free, data is free, implementation is 200 lines of python Bookmark and use in your own strategy they kept you staring at candles while they ran probability tables

Livsun

374,208 Aufrufe • vor 1 Monat

Quant on Polymarket turned $313 into $296,000 in one month - and it never predicted Bitcoin's direction once. 65% win rate on 15-minute Up/Down markets. The edge wasn't the forecast. It was the order book. Wallet proof: It's the one thing retail never sees and bots live on: full bid/ask depth on any BTC/ETH/SOL Up/Down market, at any second in its history, down to 300ms - Binance depth beside it, replayable tick-by-tick on real fills. I've been pulling it from PolyHistorical Here's why it matters. Bloomberg ran the numbers: the top 1% of wallets, mostly bots, took 80%+ of all profits. Retail lost $131M net. Same predictions - better data. What that data shows: pull the depth on a BTC 5-minute market and watch the last minute. Resting bids at T-60 sit around $1,210. At T-10, $240. At T-3, $90. 95% of the liquidity you think you can hit vanishes before resolution. A $500 buy at T-30 eats ~4.2¢ of slippage - half the edge, gone. One tested pattern: when depth leans 65/35 while price sits flat, it reverts within 60s 73% of the time. Median lag from depth to price: 11 seconds. 312 signals in 30 days. The depth wasn't lagging. It was waiting. That's the whole game here - not calling the candle, but seeing depth shift before price does. This wallet did exactly that. Every level, every 300ms, 13,000+ resolved markets, free to replay.
0:46

Quant on Polymarket turned $313 into $296,000 in one month - and it never predicted Bitcoin's direction once. 65% win rate on 15-minute Up/Down markets. The edge wasn't the forecast. It was the order book. Wallet proof: It's the one thing retail never sees and bots live on: full bid/ask depth on any BTC/ETH/SOL Up/Down market, at any second in its history, down to 300ms - Binance depth beside it, replayable tick-by-tick on real fills. I've been pulling it from PolyHistorical Here's why it matters. Bloomberg ran the numbers: the top 1% of wallets, mostly bots, took 80%+ of all profits. Retail lost $131M net. Same predictions - better data. What that data shows: pull the depth on a BTC 5-minute market and watch the last minute. Resting bids at T-60 sit around $1,210. At T-10, $240. At T-3, $90. 95% of the liquidity you think you can hit vanishes before resolution. A $500 buy at T-30 eats ~4.2¢ of slippage - half the edge, gone. One tested pattern: when depth leans 65/35 while price sits flat, it reverts within 60s 73% of the time. Median lag from depth to price: 11 seconds. 312 signals in 30 days. The depth wasn't lagging. It was waiting. That's the whole game here - not calling the candle, but seeing depth shift before price does. This wallet did exactly that. Every level, every 300ms, 13,000+ resolved markets, free to replay.

cvxv666

21,867 Aufrufe • vor 14 Tagen

quants don't predict markets. they stopped trying years ago retail is still asking "where is price going?" - quants switched to a different question entirely "given the current state, what's the probability distribution of outcomes" that's not a semantics game. it changes the math entirely stochastic processes model how a system evolves probabilistically - not picking a direction, mapping where each path leads and how likely it is ornstein-uhlenbeck does this for mean reversion: drift rate back to equilibrium, variance around that path same price data everybody has. different equation math is a century old, free in every applied probability textbook Bookmark and learn this before it gone you've been drawing trend lines while they ran probability distributions on same numbers it was never about data it was the question you were taught to ask
1:27

quants don't predict markets. they stopped trying years ago retail is still asking "where is price going?" - quants switched to a different question entirely "given the current state, what's the probability distribution of outcomes" that's not a semantics game. it changes the math entirely stochastic processes model how a system evolves probabilistically - not picking a direction, mapping where each path leads and how likely it is ornstein-uhlenbeck does this for mean reversion: drift rate back to equilibrium, variance around that path same price data everybody has. different equation math is a century old, free in every applied probability textbook Bookmark and learn this before it gone you've been drawing trend lines while they ran probability distributions on same numbers it was never about data it was the question you were taught to ask

Livsun

13,176 Aufrufe • vor 16 Tagen

🚨 Jensen Huang says everyone panicked about the AI data when MOST training data was never REAL to begin with. Ilya Sutskever told the industry pre-training was over. "Ilya said, 'We're out of data,' or something like that. 'Pre-training is over,' or something like that," Huang says. "The industry panicked, you know, that this is the end of AI." "And of course, of course that's obviously not true. We're gonna keep on scaling the amount of data that we have to train with." "A lot of that data is probably gonna be synthetic." That's where the panic came from — synthetic data sounds like cheating. "Most of the data that we are training, that we teach each other with, inform each other with, is synthetic." "It's synthetic because it didn't come out of nature." "You created it. I'm consuming it. I modify it, augment it, I regenerate it, somebody else consumes it." The textbook in your hand is synthetic. The post you're reading is synthetic. The lecture you took is synthetic. Nature didn't make any of it. Humans did. AI just learned to do the same thing — faster. "Training is now limited by compute," Huang says. "Data is now limited by compute." The data wall wasn't a wall. It was a mirror. If you're new here, follow @AiEvolutio for the latest on ChatGPT, Claude, and the AI tools shaping how we work and create. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast
1:29

🚨 Jensen Huang says everyone panicked about the AI data when MOST training data was never REAL to begin with. Ilya Sutskever told the industry pre-training was over. "Ilya said, 'We're out of data,' or something like that. 'Pre-training is over,' or something like that," Huang says. "The industry panicked, you know, that this is the end of AI." "And of course, of course that's obviously not true. We're gonna keep on scaling the amount of data that we have to train with." "A lot of that data is probably gonna be synthetic." That's where the panic came from — synthetic data sounds like cheating. "Most of the data that we are training, that we teach each other with, inform each other with, is synthetic." "It's synthetic because it didn't come out of nature." "You created it. I'm consuming it. I modify it, augment it, I regenerate it, somebody else consumes it." The textbook in your hand is synthetic. The post you're reading is synthetic. The lecture you took is synthetic. Nature didn't make any of it. Humans did. AI just learned to do the same thing — faster. "Training is now limited by compute," Huang says. "Data is now limited by compute." The data wall wasn't a wall. It was a mirror. If you're new here, follow @AiEvolutio for the latest on ChatGPT, Claude, and the AI tools shaping how we work and create. — Jensen Huang ( NVIDIA ), NVIDIA CEO, on Lex Fridman's ( Lex Fridman ) podcast

AI Evolution

15,565 Aufrufe • vor 26 Tagen

Congrats if you watched this video a few months ago, I think we were one of the first channels to spot this diminishing MVRV pattern on $BTC. The technicals and on chain data all indicated that we were starting to form a top. Price of #Bitcoin at the time was $111,000.
5:07

Congrats if you watched this video a few months ago, I think we were one of the first channels to spot this diminishing MVRV pattern on $BTC. The technicals and on chain data all indicated that we were starting to form a top. Price of #Bitcoin at the time was $111,000.

SmartMoneyCrypto

61,142 Aufrufe • vor 7 Monaten

I asked a Meta whistleblower if the company stopped child safety research, restricted data, altered results, and even deleted evidence of harm to kids. The answer each time was the same: Yes. That says it all.
0:31

I asked a Meta whistleblower if the company stopped child safety research, restricted data, altered results, and even deleted evidence of harm to kids. The answer each time was the same: Yes. That says it all.

Amy Klobuchar

35,516 Aufrufe • vor 9 Monaten

MIT has been teaching this publicly for 50 years. retail traders still draw trendlines andrei markov published the framework in 1906. hedge funds found it in the 70s built billion-dollar operations around it, never told retail it existed markets aren't random - they're state machines trending, ranging, reversing. each state has a fixed historical probability of shifting to the next you build a transition matrix from real price data: trending -> stays trending: 68% trending -> flips to range: 21% trending -> reverses: 11% now you're not predicting direction. you're entering on 68% historical completion that's not a signal, that's conditional probability compounding every single trade math is free, data is free, implementation is ~200 lines of python what's not free: knowing this framework exists while everyone around you draws support levels and hopes renaissance has run this since 1988. paper was always public edge was never secret. just never pointed out
52:24

MIT has been teaching this publicly for 50 years. retail traders still draw trendlines andrei markov published the framework in 1906. hedge funds found it in the 70s built billion-dollar operations around it, never told retail it existed markets aren't random - they're state machines trending, ranging, reversing. each state has a fixed historical probability of shifting to the next you build a transition matrix from real price data: trending -> stays trending: 68% trending -> flips to range: 21% trending -> reverses: 11% now you're not predicting direction. you're entering on 68% historical completion that's not a signal, that's conditional probability compounding every single trade math is free, data is free, implementation is ~200 lines of python what's not free: knowing this framework exists while everyone around you draws support levels and hopes renaissance has run this since 1988. paper was always public edge was never secret. just never pointed out

Livsun

13,963 Aufrufe • vor 21 Tagen

7 years of trading options. Lost over $30,000. Blown accounts I can't even count. There was a point I seriously considered quitting forever. I was making less than $ 30k at my 9-5. Struggling financially. Struggling mentally. Trading was supposed to be the way out. Instead it became the thing that was destroying me. I remember one point, it was 2am. I was staring at my brokerage screen after blowing $500 on a revenge trade. Kept refreshing hoping the number would change. It never did. Too embarrassed to tell anyone. Dodging family questions. Starting to wonder if maybe I just wasn't smart enough. Maybe these traders on social media had something I didn't. I tried everything. Every YouTube strategy. Every Discord. Spent thousands on courses. Scalping. Swing trading. Signals. Indicators. All of it. Every time - further in the hole. Then one January morning. Down $4,000 year to date. Sat on the edge of my bed, head in my hands. Told myself I was done. And then I realized something. I had been treating trading like gambling. Forcing trades. Oversizing. Chasing. Revenge trading. I scrapped everything. Started over with tiny positions and a checklist . One rule: if a trade doesn't meet every condition, I don't take it. Doesn't matter how good it looks. The edge was being boringly selective, not finding a better setup. That's when everything changed. 7 years later. I'm consistently profitable. I still have a full-time job (a better one now). The centerpiece of that checklist is something most retail traders have never heard of. It's called GEX - Gamma Exposure. Every time you buy an options contract, someone has to be on the other side of that trade. That someone is almost always a market maker - firms like Citadel, SIG, Wolverine. They don't want directional risk. They just want to collect the spread. So the moment they sell you that contract, they immediately go into the market and hedge their position by buying or selling the underlying shares. That hedging is not optional. They have to do it. Continuously. All day long. As price moves. At certain price levels there is a massive concentration of forced buying or forced selling from those dealers. Price reacts to those levels because dealers are mechanically obligated to transact there. That's a GEX level. Not a line you drew on a chart. Not a pattern you spotted. A level backed by real institutional positioning data. I pull the GEX map every single morning using ITMatrix HQ before I open a single chart. It shows me exactly where the major levels are, what kind of environment I'm trading in, and where the clean air is between levels. So instead of guessing where price might react - I know where it has to. Because it almost always behaves the exact same way! But GEX is only one piece of it. The checklist has four components total. And all four have to be green before I place a single trade. Miss one - I wait. That's what makes it an A+ setup. I used it to turn $1,000 into $21,000, and I consistently collect around 5k every month from trading alone! If all this sounds complicated, watch the video below. The checklist is FREE btw - I recently turned it into a web app find it in the comments below ↓
23:11

7 years of trading options. Lost over $30,000. Blown accounts I can't even count. There was a point I seriously considered quitting forever. I was making less than $ 30k at my 9-5. Struggling financially. Struggling mentally. Trading was supposed to be the way out. Instead it became the thing that was destroying me. I remember one point, it was 2am. I was staring at my brokerage screen after blowing $500 on a revenge trade. Kept refreshing hoping the number would change. It never did. Too embarrassed to tell anyone. Dodging family questions. Starting to wonder if maybe I just wasn't smart enough. Maybe these traders on social media had something I didn't. I tried everything. Every YouTube strategy. Every Discord. Spent thousands on courses. Scalping. Swing trading. Signals. Indicators. All of it. Every time - further in the hole. Then one January morning. Down $4,000 year to date. Sat on the edge of my bed, head in my hands. Told myself I was done. And then I realized something. I had been treating trading like gambling. Forcing trades. Oversizing. Chasing. Revenge trading. I scrapped everything. Started over with tiny positions and a checklist . One rule: if a trade doesn't meet every condition, I don't take it. Doesn't matter how good it looks. The edge was being boringly selective, not finding a better setup. That's when everything changed. 7 years later. I'm consistently profitable. I still have a full-time job (a better one now). The centerpiece of that checklist is something most retail traders have never heard of. It's called GEX - Gamma Exposure. Every time you buy an options contract, someone has to be on the other side of that trade. That someone is almost always a market maker - firms like Citadel, SIG, Wolverine. They don't want directional risk. They just want to collect the spread. So the moment they sell you that contract, they immediately go into the market and hedge their position by buying or selling the underlying shares. That hedging is not optional. They have to do it. Continuously. All day long. As price moves. At certain price levels there is a massive concentration of forced buying or forced selling from those dealers. Price reacts to those levels because dealers are mechanically obligated to transact there. That's a GEX level. Not a line you drew on a chart. Not a pattern you spotted. A level backed by real institutional positioning data. I pull the GEX map every single morning using ITMatrix HQ before I open a single chart. It shows me exactly where the major levels are, what kind of environment I'm trading in, and where the clean air is between levels. So instead of guessing where price might react - I know where it has to. Because it almost always behaves the exact same way! But GEX is only one piece of it. The checklist has four components total. And all four have to be green before I place a single trade. Miss one - I wait. That's what makes it an A+ setup. I used it to turn $1,000 into $21,000, and I consistently collect around 5k every month from trading alone! If all this sounds complicated, watch the video below. The checklist is FREE btw - I recently turned it into a web app find it in the comments below ↓

Nick Ireland

20,376 Aufrufe • vor 1 Monat

John: There is a lot of opposition to building in America, broadly. That's just the nature of our society. I was thinking about, what do Americans want to build? Because it's easy to look at the data center stuff and be like, "Well, everyone's against building data centers." I was reflecting on the whole reindustrialization meme this weekend. And I was thinking about the actual knock-on effects of reindustrialization — most people don't want a car factory in their town. I actually think people don't really want change. They don't want things built. Data centers are probably at the bottom of the list. They're the least popular. But people don't want stuff built, generally. There are very few things that people are like, "Yeah, I'd be down for that to be built." People like the status quo. They're happy with things as they are. And they don't like change. People block home construction all the time. Also, permitting and expansion of existing homes. I'm not saying that they're as unpopular as data centers. Data centers are at the bottom. But new housing in communities is like razor's edge. I do think there's an element of like, Americans don't want to build anything.
2:48

John: There is a lot of opposition to building in America, broadly. That's just the nature of our society. I was thinking about, what do Americans want to build? Because it's easy to look at the data center stuff and be like, "Well, everyone's against building data centers." I was reflecting on the whole reindustrialization meme this weekend. And I was thinking about the actual knock-on effects of reindustrialization — most people don't want a car factory in their town. I actually think people don't really want change. They don't want things built. Data centers are probably at the bottom of the list. They're the least popular. But people don't want stuff built, generally. There are very few things that people are like, "Yeah, I'd be down for that to be built." People like the status quo. They're happy with things as they are. And they don't like change. People block home construction all the time. Also, permitting and expansion of existing homes. I'm not saying that they're as unpopular as data centers. Data centers are at the bottom. But new housing in communities is like razor's edge. I do think there's an element of like, Americans don't want to build anything.

TBPN

106,441 Aufrufe • vor 1 Monat

quant funds spend millions hiring people who know a formula you learned in 10th grade and never applied to a price chart y = mx + b. that's it linear regression - same math from high school most traders learned, ignored, and forgot existed what quants actually figured out: asset prices don't move randomly, they drift and revert with measurable slope regression separates signal from noise. slope tracks trend, residuals measure the deviation when deviation gets large enough, that's the trade - prices tend to snap back to the line quants call it "mean reversion." retail calls it "a dip" actual workflow: > pull 5 years of daily returns > run OLS, extract beta and residuals > z-score the residuals > entries at -2 standard deviations, exits at 0 retail draws trend lines by hand and calls it analysis Bookmark this ^ data is public, math is free, approach has been in papers since the 1980s 99% of traders have never built one signal this way it was never an information gap - always been a methodology gap, and that's the kind that compounds
1:01

quant funds spend millions hiring people who know a formula you learned in 10th grade and never applied to a price chart y = mx + b. that's it linear regression - same math from high school most traders learned, ignored, and forgot existed what quants actually figured out: asset prices don't move randomly, they drift and revert with measurable slope regression separates signal from noise. slope tracks trend, residuals measure the deviation when deviation gets large enough, that's the trade - prices tend to snap back to the line quants call it "mean reversion." retail calls it "a dip" actual workflow: > pull 5 years of daily returns > run OLS, extract beta and residuals > z-score the residuals > entries at -2 standard deviations, exits at 0 retail draws trend lines by hand and calls it analysis Bookmark this ^ data is public, math is free, approach has been in papers since the 1980s 99% of traders have never built one signal this way it was never an information gap - always been a methodology gap, and that's the kind that compounds

Livsun

28,609 Aufrufe • vor 13 Tagen

There was a time you couldn't own a piece of something like SpaceX. Today it lists on Nasdaq. Same day? It's on Solana through Backpack 🎒. Not a token tracking the price. The real share. One-to-one. Redeem it. Move it to a brokerage. Bring it back. Own something for real this time.
0:37

There was a time you couldn't own a piece of something like SpaceX. Today it lists on Nasdaq. Same day? It's on Solana through Backpack 🎒. Not a token tracking the price. The real share. One-to-one. Redeem it. Move it to a brokerage. Bring it back. Own something for real this time.

nikkideyy

18,342 Aufrufe • vor 14 Tagen

A visual modeling of the Earth from the beginning of time to the present day. A ma is a unit of time corresponding to 1 million years. The plate tectonics reconstruction is based on paleomagnetic data, although it may be imprecise. The temperature, atmospheric composition, and length of day that might have existed at that time are also shown.
1:00

A visual modeling of the Earth from the beginning of time to the present day. A ma is a unit of time corresponding to 1 million years. The plate tectonics reconstruction is based on paleomagnetic data, although it may be imprecise. The temperature, atmospheric composition, and length of day that might have existed at that time are also shown.

Black Hole

18,682 Aufrufe • vor 1 Monat

"It takes time to process. It was one of the hardest years of my life, with everything that happened to me. I had to overcome a lot of odds, working my butt off every single day. My wife went through it with me. There wasn't a lot of time off. When I look back at all the people that helped me out and believed in me, I'm really grateful for my family, friends, and everyone in that locker room." CMC on Kyle Shanahan saying his season was one of the most impressive by a player of all time 🥺
1:00

"It takes time to process. It was one of the hardest years of my life, with everything that happened to me. I had to overcome a lot of odds, working my butt off every single day. My wife went through it with me. There wasn't a lot of time off. When I look back at all the people that helped me out and believed in me, I'm really grateful for my family, friends, and everyone in that locker room." CMC on Kyle Shanahan saying his season was one of the most impressive by a player of all time 🥺

95.7 The Game

220,224 Aufrufe • vor 5 Monaten

🗣️ 'It's what Ray would have wanted! That's the most important thing.' 🗣️ 'It's something that's on your mind all the time. It was a person that I talked to all the time about hurling, I rang him every day, maybe 3 or 4 times a day!' Pat Ryan reflects on the week of his brother's passing last year, going to the Kilkenny game, and how hurling helped him and his family over that time.
3:44

🗣️ 'It's what Ray would have wanted! That's the most important thing.' 🗣️ 'It's something that's on your mind all the time. It was a person that I talked to all the time about hurling, I rang him every day, maybe 3 or 4 times a day!' Pat Ryan reflects on the week of his brother's passing last year, going to the Kilkenny game, and how hurling helped him and his family over that time.

Off The Ball

24,953 Aufrufe • vor 1 Monat

The dirty little secret of Roblox is that it's actually an infrastructure company. David Baszucki on what's really running behind the scenes when 20M people play a game at the same time: "That's 20,000,000 people all around the world. They're playing on a phone, a tablet, a computer, iOS, Android, PC, Mac, Xbox, PlayStation, Meta Quest. They are running translated versions of that experience. They are hitting very quickly on Roblox bandwidth. They are connecting to data centers in Poland or in Singapore or in Brazil." "Running that is very complex. Running a 3D simulation cheaply is very complicated." "We have core data centers, edge data centers, and we're running a lot of our own CPUs and GPUs all around that." Where did it all start? "The very beginning of Roblox was running on one giant server. It was right over there in my office."
1:25

The dirty little secret of Roblox is that it's actually an infrastructure company. David Baszucki on what's really running behind the scenes when 20M people play a game at the same time: "That's 20,000,000 people all around the world. They're playing on a phone, a tablet, a computer, iOS, Android, PC, Mac, Xbox, PlayStation, Meta Quest. They are running translated versions of that experience. They are hitting very quickly on Roblox bandwidth. They are connecting to data centers in Poland or in Singapore or in Brazil." "Running that is very complex. Running a 3D simulation cheaply is very complicated." "We have core data centers, edge data centers, and we're running a lot of our own CPUs and GPUs all around that." Where did it all start? "The very beginning of Roblox was running on one giant server. It was right over there in my office."

David Senra

37,251 Aufrufe • vor 1 Monat

When a million people told Facebook they hated News Feed, the data told a very different story. Julie Zhuo (Co-founder, Sundial; former Facebook VP of Design) on decision-making at Meta: “In order to build something new, you do need that spark of inspiration, and it usually comes from intuition.” From there, test the hypothesis fast and follow the data. “News Feed faced huge protests, over a million joined ‘I effing hate Facebook News Feed’, but the numbers showed people spending a lot of time on it. It was obvious it was working despite the backlash.”
2:52

When a million people told Facebook they hated News Feed, the data told a very different story. Julie Zhuo (Co-founder, Sundial; former Facebook VP of Design) on decision-making at Meta: “In order to build something new, you do need that spark of inspiration, and it usually comes from intuition.” From there, test the hypothesis fast and follow the data. “News Feed faced huge protests, over a million joined ‘I effing hate Facebook News Feed’, but the numbers showed people spending a lot of time on it. It was obvious it was working despite the backlash.”

TBPN

16,488 Aufrufe • vor 10 Monaten

a quant who started as a technical trader explained what changed everything for him he stopped trying to predict where price goes he started measuring the probability of each market state and betting only when the math was asymmetric that shift took him from drawing trendlines to writing models at 22 the realization was simple but brutal: technical analysis gives you a narrative quantitative analysis gives you a number one feels right the other is testable, repeatable, and either works or doesn't across 10,000 trades the setup on his desk tells the whole story no TradingView. no candlestick charts. just code, data, and a terminal he didn't go to MIT he didn't intern at Goldman he learned Python, statistics, and probability theory on his own and built something that actually worked > the math: free in any stats textbook > the data: free on Yahoo Finance, FRED, exchange APIs > the code: Python, 200 lines, running on a laptop > the barrier: not intelligence. just knowing this path exists most people spend years staring at indicators from the 1970s wondering why they can't find consistency the answer was never a better indicator it was a completely different framework one that treats trading as a math problem, not a prediction game full breakdown in the video below
4:36

a quant who started as a technical trader explained what changed everything for him he stopped trying to predict where price goes he started measuring the probability of each market state and betting only when the math was asymmetric that shift took him from drawing trendlines to writing models at 22 the realization was simple but brutal: technical analysis gives you a narrative quantitative analysis gives you a number one feels right the other is testable, repeatable, and either works or doesn't across 10,000 trades the setup on his desk tells the whole story no TradingView. no candlestick charts. just code, data, and a terminal he didn't go to MIT he didn't intern at Goldman he learned Python, statistics, and probability theory on his own and built something that actually worked > the math: free in any stats textbook > the data: free on Yahoo Finance, FRED, exchange APIs > the code: Python, 200 lines, running on a laptop > the barrier: not intelligence. just knowing this path exists most people spend years staring at indicators from the 1970s wondering why they can't find consistency the answer was never a better indicator it was a completely different framework one that treats trading as a math problem, not a prediction game full breakdown in the video below

delost

111,068 Aufrufe • vor 12 Tagen