POPULARITY
2 episodes with hahahah
2 episodes with hahahah
2 episodes with hahahah
4 episodes with hahahah
2 episodes with hahahah
2 episodes with hahahah
2 episodes with hahahah
2 episodes with hahahah
2 episodes with hahahah
All three of us are back to cast actors for some of our favorite books! We talk about For the Plot, For the Show, For the Fans, Pucking Around, The Nanny is Off Limits, some others and of course... Twilight. Hahahah. This was a blast, tune in.
This episode has me creasing HAHAHAH. Enjoy xx Sammy's Socials: https://www.instagram.com/ssaaamm__/ Jadyn's Socials: https://www.instagram.com/jadynlam/ Remember if you enjoyed the episode, please don't forget to follow Life With Lam and leave a review. Contact me via these handles if you want to collaborate or be a part of the family! Instagram - https://www.instagram.com/lifewithlampodcast/ Email - lifewithlampodcast@gmail.com
Olá, divos e divas! Nós somos cheios de procedimentos estéticos HAHAHAH e vocês? Esse assunto é um tabu entre muitas pessoas. Muitos concordam com procedimentos e fazem mesmo, outros são contra e alguns apoiam mas dizem que não fariam. Cada um tem sua opinião, mas a verdade é que esse é um assunto que sempre movimenta a internet: harmonizações que deram errado, famosos que são criticados por fazerem alterações no corpo e alguns que escondem que fizeram procedimentos. Vamos hablar!
Jogo pegado e com um a mais em campo não conseguimos fazer um gol. Tonhão, seja mais ousado! Time ficou no 0x0 na estreia no Brasileiro. Teriam gasto os gols na goleada da Sul Americana? Lá foi 4x0 e poderia ter sido mais! Romero MAIOR ARTILHEIRO DA NEO QUÍMICA ARENA! Fausto se encontrou? E as BRABAS só ganham! Hahahah!
SPECIAL INTEREST ALERT!! Hello my loves, join me for a weekly catchup and sit back and relax while I tell you everything I know about the titanic HAHAHAH. No seriously I'm obsessed with the titanic and I wanted to talk about it on the anniversary. RIP. Enjoy this episode love ya
Beim Radio bezeichnet man eine interne Programm-Kritik als Aircheck. Außer an Ostern, da wird das ganze dann zum EIER-Check. Hahahah! Wegen Eiern und Ostern, versteht ihr?! FEIerlich. Auf jeden Fall aircheckt Tommy heute Kathrins Frühsendung. Die nimmt das gelassen hin – so, wie sie es von SensEI Norbert gelernt hat... EInfach EInzigartig diese Folge! Hier der Link zu unserem WhatsApp Channel: https://whatsapp.com/channel/0029VaBSCV98kyyQceNs4A1I Und hier zu unserem Instagram: https://www.instagram.com/ab17podcast/ Du möchtest mehr über unsere Werbepartner erfahren? [**Hier findest du alle Infos & Rabatte!**](https://linktr.ee/ab17_studiobummens)
This episode originally broadcast on January 25, 2024. The original podcast post is here: https://pixelatedgeek.com/2024/01/binary-system-podcast-395-doctor-who-taken-nice-house-on-the-lake-and-the-hugos/ You're not going to believe this, but we said we were going to watch the third David Tennant Doctor Who episode this week AND WE DID. Next thing you know we'll be watching movies the weekend they come out. (Hahahah, kidding, obviously.) Anyway, our hearts are still intact after the episode, which was for the most part goofy with a few terrifying images thrown in. It also gave new meaning to the words “self care,” which is just delightful. After that Elizabeth talks about how she's randomly watching 2008's Taken (which is still a fun watch even if it does lean into the patriarchy) and Kathryn discusses The Nice House on the Lake and how we DARN WELL BETTER get a third volume soon. Finally, we go over what we know about the Hugo Awards debacle, which is to say: not much. Several people were disqualified for reasons that can be summed up as “because I said so,” and while there's a lot of speculation that it was anything from Chinese government censorship to a massive screw up with the math, there's still no good explanation. If something changes we'll add a note to this description. I mean, Neil Gaiman's pissed off so you know it's not good. This week's outro is a clip from 6026 Zenophanes by Midnight Commando. Looking for a present for that hard-to-shop-for person? Want to buy them (or yourself) a square foot of a castle in Scotland? Look no further! You can support the restoration of Dunan's castle, legally call yourself Lady or Laird, AND if you use this link to get there, you can support this podcast too! ScottishLaird.co.uk. For updates, fan art, and other randomness, come follow us on Facebook, Tumblr, Twitter, and Instagram!
You're not going to believe this, but we said we were going to watch the third David Tennant Doctor Who episode this week AND WE DID. Next thing you know we'll be watching movies the weekend they come out. (Hahahah, kidding, obviously.) Anyway, our hearts are still intact after the episode, which was for the... The post Binary System Podcast #395 – Doctor Who, Taken, Nice House on the Lake, and the Hugos first appeared on Pixelated Geek.
Hahahah let's talk.
Hey y'all!!! It's been a minute!! Please listen to this short rant/review about the recent movie drop on netflix called Love at First Sight! Hahahah!! I def recommend!!
Welcome to the Silver Bullet Saga, the podcast that delves deep into the world of college football, uncovering the untold stories that make the sport both thrilling and controversial. In our latest episode, hosts Ryan Vonderhaar and Adam Vonderhaar tackle the shocking Michigan Football sign-stealing scandal that has sent shockwaves through the college sports community. As details emerge about the alleged espionage tactics employed by the Wolverines, the hosts dissect the implications for the team, the players, and the integrity of the game itself. But that's not all - the "Silver Bullet Saga" team also explores the suspension of none other than the renowned head coach, Jim Harbaugh. With a storied career and a reputation for success, Harbaugh's sudden sidelining raises questions about the responsibility of leadership and the lengths some may go to gain a competitive edge. Join Ryan and Adam as they unravel the layers of this gripping saga, providing insightful commentary, expert opinions, and a behind-the-scenes look at the scandal that's rocking the Michigan Football program to its core. We also preview the Buckeyes vs Michigan State game in the Shoe tomorrow night. Follow us on twitter: @OhioState_SBS
DER ER MINISODE!! DER ER MINISODE..Så er vi fandme klar. Paradise Hotel er tilbage efter 2 afstikkere - bare til Paradise med de to woke sæsoner alle hadede. Gamle deltagere er tilbage fra det gamle hotel. Rikke er tilbage fra det gamle hotel og de indtager nu Olivia Salos nye hotel i sådan en grad man nærmest ikke ved hvem der ellers er med udover Sarah Dohn og Anne Plejdrup. Det er efffing girlpower. Men samtidig er det nok en anelse problematisk, at man gør Silles forhistorie på Paradise, hvor hun jo rent faktisk udøver vold mod David, hun tabte til, til hendes herohistorie. Det taler vi selvfølgelig også om. Og hvorfor er Patrick egentlig med i startcastet - når han i historiebøgerne ikke riiiiiiigtigt har været i nærheden af en troskabstestsglaskugle?Jeg er mødtes med legenden af Paradise Hotel - Den gamle Skole - Philip May. Vi taler om de tre første afsnit af den nye sæson. Det er fantastisk endelig at mødes med Philip igen. Men som I nok kan høre, så er Philip hjemme hos sig selv, og jeg sidder hos mig. Det er derfor man kan høre Philip traske op og ned af sit stuegulv under nærmest hele podcasten. Hahahah.. Men vi optager over internettet - og Philip May taler fra en telefon, derfor lyden. Håber I kan holde det ud. Jeg er glad for at Philip May er tilbage. Elsker ham virkelig. Og det ved jeg også I gør, så tag lige godt imod den her episode - og vi laver i hvert fald et afsnit mere under den her sæson. #fridabnotmybachelorette Hosted on Acast. See acast.com/privacy for more information.
GUYS I'M IN A MAGAZINE!!! First and foremost thank you to the beautiful & talented Tanya Yarian for writing such a beautiful piece showcasing my podcast and to the Currents Magazine for all your hard work!! I truly am SO HONORED AND GRATEFUL!!! be warned there are a lot of happy tears in this episode HAHAHAH but I love you all and THANK YOU for the never ending SUPPORT!!!!
Hahahah is my life falling apart orrrrr do most people who just hit 30 feel like this? Errrggggghh --- Support this podcast: https://podcasters.spotify.com/pod/show/terrortimeagain/support
In this episode about Black Men in History, we pay homage to the finest black men who have made a lasting impact on American society. From civil rights leaders, to entrepreneurs --- JK! Hahahah this would be an amazing episode though wouldn't it? Tune in to see what Joy really did, what she really means by fine, the painstaking, bleeding work she did to sort through the crème de la crème of black men in U.S. history. Mmm. Follow the show and DM me your requests for bonus episodes! www.DatingUnsettled.com YouTube: JoyOfodu IG: @datingunsettled TikTok: datingunsettled Twitter: @datingunsettled Connect with Joy www.joyofodu.com IG: @joyofodu TikTok: joyofodu Twitter: @joyofodu
HAHAHAH! EDDIE YOU HERO! | Arsenal 3-2 Manchester United Match Reaction Show!Tom presents a daily show on The Gooner Talk covering all the latest Arsenal news, Arsenal transfer news, match reaction, press conferences and much more plus a Q&A session taking questions from the LIVE chat. Get all your Arsenal news now and every day. Links to Fantasy code, Twitter, Instagram, audio-only platforms, The Arsenal Way and our channel membership scheme including entry to the Discord community: https://linktr.ee/TheGoonerTalk Become a member at https://plus.acast.com/s/the-gooner-talk. Hosted on Acast. See acast.com/privacy for more information.
WELCOME TO SEASON 3!!!This season has so much in store...fun guests, LUD topics, and a committed Dani & Alexa? hmmmm IDK listen to find out.In this episode we're talking all things loveeee, are you in it? Have you had it? How do you know? We call on one of Alexa's idols, the one the only Oprah! Hahahah well an article written by Oprah...but still.Santa baby tell us is Damn Dani Damned? This NH gal is stoked to start ***ayyyy***We also talk Xmas gifts for SOs and a little monthly life update...oh also Alexa's therapist quit on her so there's that lolBooze Review: Après So Was Red Raspberry Rhubarb Hard Seltzer- 5% ABV Alexa: 14/15 (I may not be in love w/ someone but i'm def in love w/this lol) Dani: 13/15Follow us on Insta, Rate, Subscribe, Download, and Share...we mostly market by word of mouth so it helps a lot!!
NOTHING PERSONAL HAHAHAH! Chelsea 0-1 Arsenal Match Reaction | Premier League Tom presents a daily show on The Gooner Talk covering all the latest Arsenal news, Arsenal transfer news, match reaction, press conferences and much more plus a Q&A session taking questions from the LIVE chat. Get all your Arsenal news now and every day. Links to Fantasy code, Twitter, Instagram, audio-only platforms, The Arsenal Way and our channel membership scheme including entry to the Discord community: https://linktr.ee/TheGoonerTalk Become a member at https://plus.acast.com/s/the-gooner-talk. Hosted on Acast. See acast.com/privacy for more information.
Já ligou pra ex e se declarou? Ficou com uma pessoa de caráter duvidoso? Fez uma serenata? HAHAHAH vem contar para as minas @soufernandacunha, @larissavguerra e @laiskuchler, qual foi a maior loucura que você fez por carência.
www.prepperbroadcasting.comwww.disastercoffee.comSupport Our Great SponsorsThe Preppers Medical Handbook https://amzn.to/3piYAlUEmergency Antibiotic Kit Jase Medical http://www.jasemedical.com/?utm_source=pbn&utm_medium=podcastThe Preppers Guide to Surviving Pandemics, Bioterrorism and Infectious Disease https://amzn.to/3djoKzwDisaster Coffee www.disastercoffee.comSupport The Prepper Broadcasting NetworkBecome a Member and Receive Exclusive Content https://bit.ly/3pniGLYSign up for the Newsletter https://bit.ly/3Df15e0Check out Patreon! https://bit.ly/3uDkBQHCome Unity; Community https://amzn.to/3ddsN0dThe Christmas Hook https://amzn.to/3rxTlS1Some of My Favorite Preps The Home Security Super Store https://bit.ly/3QmRV72My EDC Bag 3VGear Outlaw Sling Pack https://amzn.to/3oklKZZMy EDC Flashlight Olight S1R https://amzn.to/3djpBQKQuick Aquaponics System https://amzn.to/31keqVA20-1 Gallon Mylar Bags and 02 Absorbers https://amzn.to/3KgN8AaMr. OCAX predator deterrents for chickens https://amzn.to/3Isbg2KAffordable Hot Tent https://amzn.to/3lxKX0ZAffordable Stove https://amzn.to/3Dxu4tPShow DescriptionMusic Credits:Peculate - Opium of the PeopleChecky Brown - City WalkKeiLoKaz - Dar Saltos de AlegriaKeLoKaz - Rainy NightsMeluran - Vanilla There are affiliate links up there! ^^^
Haiii Haii! kembali lagi bersama SMAPODT! Pada episode kali ini akan bersama UKM Olahraga lagi nihh bidangnya dalam permainan bola kecil. UKM ini diam-diam menghanyutkan, lhooo!! . HAHAHAH iyaa mereka keren banget!! telah mengikuti berbagai Kejuaraan baik dalam lingkungan kampus ataupun Nasional!. YUPP!! UKM Tennis, Kira-kira UKM Tennis UNPAR sekeren apa yaa??, terus UKM Tennis UNPAR kira-kira pas pandemi gitu ngapain aja yaa?? dan ngapain aja sii UKM Tennis ini kesehariannya kalo udah masuk kampus ini???. Nah, daripada penasaran, NIH!!. YUKK!! dengerin podcast pada episode 8 ini bersama ketua UKM Tennis periode 2022 Apredo Laneva. Semoga bisa menjawab pertanyaan yang sering terlintas dipikiran kamu yaaa!! #SMUNPAR22 #SiapBerdampak
Steve Hsu is a Professor of Theoretical Physics at Michigan State University and cofounder of the company Genomic Prediction.We go deep into the weeds on how embryo selection can make babies healthier and smarter. Steve also explains the advice Richard Feynman gave him to pick up girls, the genetics of aging and intelligence, & the psychometric differences between shape rotators and wordcels.Watch on YouTube. Listen on Apple Podcasts, Spotify, or any other podcast platform.Subscribe to find out about future episodes!Read the full transcript here.Follow Steve on Twitter. Follow me on Twitter for updates on future episodes.Please share if you enjoyed this episode! Helps out a ton!Timestamps(0:00:14) - Feynman’s advice on picking up women(0:11:46) - Embryo selection(0:24:19) - Why hasn't natural selection already optimized humans?(0:34:13) - Aging(0:43:18) - First Mover Advantage(0:53:49) - Genomics in dating(1:00:31) - Ancestral populations(1:07:58) - Is this eugenics?(1:15:59) - Tradeoffs to intelligence(1:25:01) - Consumer preferences(1:30:14) - Gwern(1:34:35) - Will parents matter?(1:45:25) - Word cells and shape rotators(1:57:29) - Bezos and brilliant physicists(2:10:23) - Elite educationTranscriptDwarkesh Patel 0:00 Today I have the pleasure of speaking with Steve Hsu. Steve, thanks for coming on the podcast. I'm excited about this.Steve Hsu 0:04 Hey, it's my pleasure! I'm excited too and I just want to say I've listened to some of your earlier interviews and thought you were very insightful, which is why I was excited to have a conversation with you.Dwarkesh Patel 0:14That means a lot for me to hear you say because I'm a big fan of your podcast.Feynman’s advice on picking up womenDwarkesh Patel 0:17 So my first question is: “What advice did Richard Feynman give you about picking up girls?”Steve Hsu 0:24 Haha, wow! So one day in the spring of my senior year, I was walking across campus and saw Feynman coming toward me. We knew each other from various things—it's a small campus, I was a physics major and he was my hero–– so I'd known him since my first year. He sees me, and he's got this Long Island or New York borough accent and says, "Hey, Hsu!" I'm like, "Hi, Professor Feynman." We start talking. And he says to me, "Wow, you're a big guy." Of course, I was much bigger back then because I was a linebacker on the Caltech football team. So I was about 200 pounds and slightly over 6 feet tall. I was a gym rat at the time and I was much bigger than him. He said, "Steve, I got to ask you something." Feynman was born in 1918, so he's not from the modern era. He was going through graduate school when the Second World War started. So, he couldn't understand the concept of a health club or a gym. This was the 80s and was when Gold's Gym was becoming a world national franchise. There were gyms all over the place like 24-Hour Fitness. But, Feynman didn't know what it was. He's a fascinating guy. He says to me, "What do you guys do there? Is it just a thing to meet girls? Or is it really for training? Do you guys go there to get buff?" So, I started explaining to him that people are there to get big, but people are also checking out the girls. A lot of stuff is happening at the health club or the weight room. Feynman grills me on this for a long time. And one of the famous things about Feynman is that he has a laser focus. So if there's something he doesn't understand and wants to get to the bottom of it, he will focus on you and start questioning you and get to the bottom of it. That's the way his brain worked. So he did that to me for a while because he didn't understand lifting weights and everything. In the end, he says to me, "Wow, Steve, I appreciate that. Let me give you some good advice."Then, he starts telling me how to pick up girls—which he's an expert on. He says to me, "I don't know how much girls like guys that are as big as you." He thought it might be a turn-off. "But you know what, you have a nice smile." So that was the one compliment he gave me. Then, he starts to tell me that it's a numbers game. You have to be rational about it. You're at an airport lounge, or you're at a bar. It's Saturday night in Pasadena or Westwood, and you're talking to some girl. He says, "You're never going to see her again. This is your five-minute interaction. Do what you have to do. If she doesn't like you, go to the next one." He also shares some colorful details. But, the point is that you should not care what they think of you. You're trying to do your thing. He did have a reputation at Caltech as a womanizer, and I could go into that too but I heard all this from the secretaries.Dwarkesh Patel 4:30 With the students or only the secretaries? Steve Hsu 4:35 Secretaries! Well mostly secretaries. They were almost all female at that time. He had thought about this a lot, and thought of it as a numbers game. The PUA guys (pick-up artists) will say, “Follow the algorithm, and whatever happens, it's not a reflection on your self-esteem. It's just what happened. And you go on to the next one.” That was the advice he was giving me, and he said other things that were pretty standard: Be funny, be confident—just basic stuff. Steve Hu: But the main thing I remember was the operationalization of it as an algorithm. You shouldn’t internalize whatever happens if you get rejected, because that hurts. When we had to go across the bar to talk to that girl (maybe it doesn’t happen in your generation), it was terrifying. We had to go across the bar and talk to some lady! It’s loud and you’ve got a few minutes to make your case. Nothing is scarier than walking up to the girl and her friends. Feynman was telling me to train yourself out of that. You're never going to see them again, the face space of humanity is so big that you'll probably never re-encounter them again. It doesn't matter. So, do your best. Dwarkesh Patel 6:06 Yeah, that's interesting because.. I wonder whether he was doing this in the 40’–– like when he was at that age, was he doing this? I don't know what the cultural conventions were at the time. Were there bars in the 40s where you could just go ahead and hit on girls or? Steve Hsu 6:19 Oh yeah absolutely. If you read literature from that time, or even a little bit earlier like Hemingway or John O'Hara, they talk about how men and women interacted in bars and stuff in New York City. So, that was much more of a thing back than when compared to your generation. That's what I can’t figure out with my kids! What is going on? How do boys and girls meet these days? Back in the day, the guy had to do all the work. It was the most terrifying thing you could do, and you had to train yourself out of that.Dwarkesh Patel 6:57 By the way, for the context for the audience, when Feynman says you were a big guy, you were a football player at Caltech, right? There's a picture of you on your website, maybe after college or something, but you look pretty ripped. Today, it seems more common because of the gym culture. But I don’t know about back then. I don't know how common that body physique was.Steve Hsu 7:24 It’s amazing that you asked this question. I'll tell you a funny story. One of the reasons Feynman found this so weird was because of the way body-building entered the United States. They were regarded as freaks and homosexuals at first. I remember swimming and football in high school (swimming is different because it's international) and in swimming, I picked up a lot of advanced training techniques from the Russians and East Germans. But football was more American and not very international. So our football coach used to tell us not to lift weights when we were in junior high school because it made you slow. “You’re no good if you’re bulky.” “You gotta be fast in football.” Then, something changed around the time I was in high school–the coaches figured it out. I began lifting weights since I was an age group swimmer, like maybe age 12 or 14. Then, the football coaches got into it mainly because the University of Nebraska had a famous strength program that popularized it.At the time, there just weren't a lot of big guys. The people who knew how to train were using what would be considered “advanced knowledge” back in the 80s. For example, they’d know how to do a split routine or squat on one day and do upper body on the next day–– that was considered advanced knowledge at that time. I remember once.. I had an injury, and I was in the trainer's room at the Caltech athletic facility. The lady was looking at my quadriceps. I’d pulled a muscle, and she was looking at the quadriceps right above your kneecap. If you have well-developed quads, you'd have a bulge, a bump right above your cap. And she was looking at it from this angle where she was in front of me, and she was looking at my leg from the front. She's like, “Wow, it's swollen.” And I was like, “That's not the injury. That's my quadricep!” And she was a trainer! So, at that time, I could probably squat 400 pounds. So I was pretty strong and had big legs. The fact that the trainer didn't really understand what well-developed anatomy was supposed to look like blew my mind!So anyway, we've come a long way. This isn't one of these things where you have to be old to have any understanding of how this stuff evolved over the last 30-40 years.Dwarkesh Patel 10:13 But, I wonder if that was a phenomenon of that particular time or if people were not that muscular throughout human history. You hear stories of Roman soldiers who are carrying 80 pounds for 10 or 20 miles a day. I mean, there's a lot of sculptures in the ancient world, or not that ancient, but the people look like they have a well-developed musculature.Steve Hsu 10:34 So the Greeks were very special because they were the first to think about the word gymnasium. It was a thing called the Palaestra, where they were trained in wrestling and boxing. They were the first people who were seriously into physical culture specific training for athletic competition.Even in the 70s, when I was a little kid, I look back at the guys from old photos and they were skinny. So skinny! The guys who went off and fought World War Two, whether they were on the German side, or the American side, were like 5’8-5’9 weighing around 130 pounds - 140 pounds. They were much different from what modern US Marines would look like. So yeah, physical culture was a new thing. Of course, the Romans and the Greeks had it to some degree, but it was lost for a long time. And, it was just coming back to the US when I was growing up. So if you were reasonably lean (around 200 pounds) and you could bench over 300.. that was pretty rare back in those days.Embryo selectionDwarkesh Patel 11:46 Okay, so let's talk about your company Genomic Prediction. Do you want to talk about this company and give an intro about what it is?Steve Hsu 11:55 Yeah. So there are two ways to introduce it. One is the scientific view. The other is the IVF view. I can do a little of both. So scientifically, the issue is that we have more and more genomic data. If you give me the genomes of a bunch of people and then give me some information about each person, ex. Do they have diabetes? How tall are they? What's their IQ score? It’s a natural AI machine learning problem to figure out which features in the DNA variation between people are predictive of whatever variable you're trying to predict.This is the ancient scientific question of how you relate the genotype of the organism (the specific DNA pattern), to the phenotype (the expressed characteristics of the organism). If you think about it, this is what biology is! We had the molecular revolution and figured out that it’s people's DNA that stores the information which is passed along. Evolution selects on the basis of the variation in the DNA that’s expressed as phenotype, as that phenotype affects fitness/reproductive success. That's the whole ballgame for biology. As a physicist who's trained in mathematics and computation, I'm lucky that I arrived on the scene at a time when we're going to solve this basic fundamental problem of biology through brute force, AI, and machine learning. So that's how I got into this. Now you ask as an entrepreneur, “Okay, fine Steve, you're doing this in your office with your postdocs and collaborators on your computers. What use is it?” The most direct application of this is in the following setting: Every year around the world, millions of families go through IVF—typically because they're having some fertility issues, and also mainly because the mother is in her 30s or maybe 40s. In the process of IVF, they use hormone stimulation to produce more eggs. Instead of one per cycle, depending on the age of the woman, they might produce anywhere between five to twenty, or even sixty to a hundred eggs for young women who are hormonally stimulated (egg donors).From there, it’s trivial because men produce sperm all the time. You can fertilize eggs pretty easily in a little dish, and get a bunch of embryos that grow. They start growing once they're fertilized. The problem is that if you're a family and produce more embryos than you’re going to use, you have the embryo choice problem. You have to figure out which embryo to choose out of say, 20 viable embryos. The most direct application of the science that I described is that we can now genotype those embryos from a small biopsy. I can tell you things about the embryos. I could tell you things like your fourth embryo being an outlier. For breast cancer risk, I would think carefully about using number four. Number ten is an outlier for cardiovascular disease risk. You might want to think about not using that one. The other ones are okay. So, that’s what genomic prediction does. We work with 200 or 300 different IVF clinics in six continents.Dwarkesh Patel 15:46 Yeah, so the super fascinating thing about this is that the diseases you talked about—or at least their risk profiles—are polygenic. You can have thousands of SNPs (single nucleotide polymorphisms) determining whether you will get a disease. So, I'm curious to learn how you were able to transition to this space and how your knowledge of mathematics and physics was able to help you figure out how to make sense of all this data.Steve Hsu 16:16 Yeah, that's a great question. So again, I was stressing the fundamental scientific importance of all this stuff. If you go into a slightly higher level of detail—which you were getting at with the individual SNPs, or polymorphisms—there are individual locations in the genome, where I might differ from you, and you might differ from another person. Typically, each pair of individuals will differ at a few million places in the genome—and that controls why I look a little different than youA lot of times, theoretical physicists have a little spare energy and they get tired of thinking about quarks or something. They want to maybe dabble in biology, or they want to dabble in computer science, or some other field. As theoretical physicists, we always feel, “Oh, I have a lot of horsepower, I can figure a lot out.” (For example, Feynman helped design the first parallel processors for thinking machines.) I have to figure out which problems I can make an impact on because I can waste a lot of time. Some people spend their whole lives studying one problem, one molecule or something, or one biological system. I don't have time for that, I'm just going to jump in and jump out. I'm a physicist. That's a typical attitude among theoretical physicists. So, I had to confront sequencing costs about ten years ago because I knew the rate at which they were going down. I could anticipate that we’d get to the day (today) when millions of genomes with good phenotype data became available for analysis. A typical training run might involve almost a million genomes, or half a million genomes. The mathematical question then was: What is the most effective algorithm given a set of genomes and phenotype information to build the best predictor? This can be boiled down to a very well-defined machine learning problem. It turns out, for some subset of algorithms, there are theorems— performance guarantees that give you a bound on how much data you need to capture almost all of the variation in the features. I spent a fair amount of time, probably a year or two, studying these very famous results, some of which were proved by a guy named Terence Tao, a Fields medalist. These are results on something called compressed sensing: a penalized form of high dimensional regression that tries to build sparse predictors. Machine learning people might notice L1-penalized optimization. The very first paper we wrote on this was to prove that using accurate genomic data and these very abstract theorems in combination could predict how much data you need to “solve” individual human traits. We showed that you would need at least a few hundred thousand individuals and their genomes and their heights to solve for height as a phenotype. We proved that in a paper using all this fancy math in 2012. Then around 2017, when we got a hold of half a million genomes, we were able to implement it in practical terms and show that our mathematical result from some years ago was correct. The transition from the low performance of the predictor to high performance (which is what we call a “phase transition boundary” between those two domains) occurred just where we said it was going to occur. Some of these technical details are not understood even by practitioners in computational genomics who are not quite mathematical. They don't understand these results in our earlier papers and don't know why we can do stuff that other people can't, or why we can predict how much data we'll need to do stuff. It's not well-appreciated, even in the field. But when the big AI in our future in the singularity looks back and says, “Hey, who gets the most credit for this genomics revolution that happened in the early 21st century?”, they're going to find these papers on the archive where we proved this was possible, and how five years later, we actually did it. Right now it's under-appreciated, but the future AI––that Roko's Basilisk AI–will look back and will give me a little credit for it. Dwarkesh Patel 21:03 Yeah, I was a little interested in this a few years ago. At that time, I looked into how these polygenic risk scores were calculated. Basically, you find the correlation between the phenotype and the alleles that correlate with it. You add up how many copies of these alleles you have, what the correlations are, and you do a weighted sum of that. So that seemed very simple, especially in an era where we have all this machine learning, but it seems like they're getting good predictive results out of this concept. So, what is the delta between how good you can go with all this fancy mathematics versus a simple sum of correlations?Steve Hsu 21:43 You're right that the ultimate models that are used when you've done all the training, and when the dust settles, are straightforward. They’re pretty simple and have an additive structure. Basically, I either assign a nonzero weight to this particular region in the genome, or I don't. Then, I need to know what the weighting is, but then the function is a linear function or additive function of the state of your genome at some subset of positions. The ultimate model that you get is straightforward. Now, if you go back ten years, when we were doing this, there were lots of claims that it was going to be super nonlinear—that it wasn't going to be additive the way I just described it. There were going to be lots of interaction terms between regions. Some biologists are still convinced that's true, even though we already know we have predictors that don't have interactions.The other question, which is more technical, is whether in any small region of your genome, the state of the individual variants is highly correlated because you inherit them in chunks. You need to figure out which one you want to use. You don't want to activate all of them because you might be overcounting. So that's where these L-1 penalization sparse methods force the predictor to be sparse. That is a key step. Otherwise, you might overcount. If you do some simple regression math, you might have 10-10 different variants close by that have roughly the same statistical significance.But, you don't know which one of those tends to be used, and you might be overcounting effects or undercounting effects. So, you end up doing a high-dimensional optimization, where you grudgingly activate a SNP when the signal is strong enough. Once you activate that one, the algorithm has to be smart enough to penalize the other ones nearby and not activate them because you're over counting effects if you do that. There's a little bit of subtlety in it. But, the main point you made is that the ultimate predictors, which are very simple and addictive—sum over effect sizes and time states—work well. That’s related to a deep statement about the additive structure of the genetic architecture of individual differences. In other words, it's weird that the ways that I differ from you are merely just because I have more of something or you have less of something. It’s not like these things are interacting in some incredibly understandable way. That's a deep thing—which is not appreciated that much by biologists yet. But over time, they'll figure out something interesting here.Why hasn’t natural selection already optimized humans?Dwarkesh Patel 24:19 Right. I thought that was super fascinating, and I commented on that on Twitter. What is interesting about that is two things. One is that you have this fascinating evolutionary argument about why that would be the case that you might want to explain. The second is that it makes you wonder if becoming more intelligent is just a matter of turning on certain SNPs. It's not a matter of all this incredible optimization being like solving a sudoku puzzle or anything. If that's the case, then why hasn't the human population already been selected to be maxed out on all these traits if it's just a matter of a bit flip?Steve Hsu 25:00 Okay, so the first issue is why is this genetic architecture so surprisingly simple? Again, we didn't know it would be simple ten years ago. So when I was checking to see whether this was a field that I should go into depending on our capabilities to make progress, we had to study the more general problem of the nonlinear possibilities. But eventually, we realized that most of the variance would probably be captured in an additive way. So, we could narrow down the problem quite a bit. There are evolutionary reasons for this. There’s a famous theorem by Fisher, the father of population genetics (aka. frequentist statistics). Fisher proved something called Fisher's Fundamental Theorem of Natural Selection, which says that if you impose some selection pressure on a population, the rate at which that population responds to the selection pressure (lets say it’s the bigger rats that out-compete the smaller rats) then at what rate does the rat population start getting bigger? He showed that it's the additive variants that dominate the rate of evolution. It's easy to understand why if it's a nonlinear mechanism, you need to make the rat bigger. When you sexually reproduce, and that gets chopped apart, you might break the mechanism. Whereas, if each short allele has its own independent effect, you can inherit them without worrying about breaking the mechanisms. It was well known among a tiny theoretical population of biologists that adding variants was the dominant way that populations would respond to selection. That was already known. The other thing is that humans have been through a pretty tight bottleneck, and we're not that different from each other. It's very plausible that if I wanted to edit a human embryo, and make it into a frog, then there are all kinds of subtle nonlinear things I’d have to do. But all those identical nonlinear complicated subsystems are fixed in humans. You have the same system as I do. You have the not human, not frog or ape, version of that region of DNA, and so do I. But the small ways we differ are mostly little additive switches. That's this deep scientific discovery from over the last 5-10 years of work in this area. Now, you were asking about why evolution hasn't completely “optimized” all traits in humans already. I don't know if you’ve ever done deep learning or high-dimensional optimization, but in that high-dimensional space, you're often moving on a slightly-tilted surface. So, you're getting gains, but it's also flat. Even though you scale up your compute or data size by order of magnitude, you don't move that much farther. You get some gains, but you're never really at the global max of anything in these high dimensional spaces. I don't know if that makes sense to you. But it's pretty plausible to me that two things are important here. One is that evolution has not had that much time to optimize humans. The environment that humans live in changed radically in the last 10,000 years. For a while, we didn't have agriculture, and now we have agriculture. Now, we have a swipe left if you want to have sex tonight. The environment didn't stay fixed. So, when you say fully optimized for the environment, what do you mean? The ability to diagonalize matrices might not have been very adaptive 10,000 years ago. It might not even be adaptive now. But anyway, it's a complicated question that one can't reason naively about. “If God wanted us to be 10 feet tall, we'd be 10 feet tall.” Or “if it's better to be smart, my brain would be *this* big or something.” You can't reason naively about stuff like that.Dwarkesh Patel 29:04 I see. Yeah.. Okay. So I guess it would make sense then that for example, with certain health risks, the thing that makes you more likely to get diabetes or heart disease today might be… I don't know what the pleiotropic effect of that could be. But maybe that's not that important one year from now.Steve Hsu 29:17 Let me point out that most of the diseases we care about now—not the rare ones, but the common ones—manifest when you're 50-60 years old. So there was never any evolutionary advantage of being super long-lived. There's even a debate about whether the grandparents being around to help raise the kids lifts the fitness of the family unit.But, most of the time in our evolutionary past, humans just died fairly early. So, many of these diseases would never have been optimized against evolution. But, we see them now because we live under such good conditions, we can regulate people over 80 or 90 years.Dwarkesh Patel 29:57 Regarding the linearity and additivity point, I was going to make the analogy that– and I'm curious if this is valid– but when you're programming, one thing that's good practice is to have all the implementation details in separate function calls or separate programs or something, and then have your main loop of operation just be called different functions like, “Do this, do that”, so that you can easily comment stuff away or change arguments. This seemed very similar to that where by turning these names on and off, you can change what the next offering will be. And, you don't have to worry about actually implementing whatever the underlying mechanism is. Steve Hsu 30:41 Well, what you said is related to what Fisher proved in his theorems. Which is that, if suddenly, it becomes advantageous to have X, (like white fur instead of black fur) or something, it would be best if there were little levers that you could move somebody from black fur to white fur continuously by modifying those switches in an additive way. It turns out that for sexually reproducing species where the DNA gets scrambled up in every generation, it's better to have switches of that kind. The other point related to your software analogy is that there seem to be modular, fairly modular things going on in the genome. When we looked at it, we were the first group to have, initially, 20 primary disease conditions we had decent predictors for. We started looking carefully at just something as trivial as the overlap of my sparsely trained predictor. It turns on and uses *these* features for diabetes, but it uses *these* features for schizophrenia. It’s the stupidest metric, it’s literally just how much overlap or variance accounted for overlap is there between pairs of disease conditions. It's very modest. It's the opposite of what naive biologists would say when they talk about pleiotropy.They're just disjoint! Disjoint regions of your genome that govern certain things. And why not? You have 3 billion base pairs—there's a lot you can do in there. There's a lot of information there. If you need 1000 to control diabetes risk, I estimated you could easily have 1000 roughly independent traits that are just disjoint in their genetic dependencies. So, if you think about D&D, your strength, decks, wisdom, intelligence, and charisma—those are all disjoint. They're all just independent variables. So it's like a seven-dimensional space that your character lives in. Well, there's enough information in the few million differences between you and me. There's enough for 1000-dimensional space of variation.“Oh, how considerable is your spleen?” My spleen is a little bit smaller, yours is a little bit bigger - that can vary independently of your IQ. Oh, it's a big surprise. The size of your spleen can vary independently of the size of your big toe. If you do information theory, there are about 1000 different parameters, and I can vary independently with the number of variants I have between you and me. Because you understand some information theory, it’s trivial to explain, but try explaining to a biologist, you won't get very far.Dwarkesh Patel 33:27 Yeah, yeah, do the log two of the number of.. is that basically how you do it? Yeah.Steve Hsu 33:33 Okay. That's all it is. I mean, it's in our paper. We look at how many variants typically account for most of the variation for any of these major traits, and then imagine that they're mostly disjoint. Then it’s just all about: how many variants you need to independently vary 1000 traits? Well, a few million differences between you and me are enough. It's very trivial math. Once you understand the base and how to reason about information theory, then it's very trivial. But, it ain’t trivial for theoretical biologists, as far as I can tell.AgingDwarkesh Patel 34:13 But the result is so interesting because I remember reading in The Selfish Gene that, as he (Dawkins) hypothesizes that the reason we could be aging is an antagonistic clash. There's something that makes you healthier when you're young and fertile that makes you unhealthy when you're old. Evolution would have selected for such a trade-off because when you're young and fertile, evolution and your genes care about you. But, if there's enough space in the genome —where these trade-offs are not necessarily necessary—then this could be a bad explanation for aging, or do you think I'm straining the analogy?Steve Hsu 34:49 I love your interviews because the point you're making here is really good. So Dawkins, who is an evolutionary theorist from the old school when they had almost no data—you can imagine how much data they had compared to today—he would tell you a story about a particular gene that maybe has a positive effect when you're young, but it makes you age faster. So, there's a trade-off. We know about things like sickle cell anemia. We know stories about that. No doubt, some stories are true about specific variants in your genome. But that's not the general story. The general story you only discovered in the last five years is that thousands of variants control almost every trait and those variants tend to be disjoint from the ones that control the other trait. They weren't wrong, but they didn't have the big picture.Dwarkesh Patel 35:44 Yeah, I see. So, you had this paper, it had polygenic, health index, general health, and disease risk.. You showed that with ten embryos, you could increase disability-adjusted life years by four, which is a massive increase if you think about it. Like what if you could live four years longer and in a healthy state? Steve Hsu 36:05 Yeah, what's the value of that? What would you pay to buy that for your kid?Dwarkesh Patel 36:08 Yeah. But, going back to the earlier question about the trade-offs and why this hasn't already been selected for, if you're right and there's no trade-off to do this, just living four years older (even if that's beyond your fertility) just being a grandpa or something seems like an unmitigated good. So why hasn’t this kind of assurance hasn't already been selected for? Steve Hsu 36:35 I’m glad you're asking about these questions because these are things that people are very confused about, even in the field. First of all, let me say that when you have a trait that's controlled by 10,000 variants (eg. height is controlled by order 10,000 variants and probably cognitive ability a little bit more), the square root of 10,000 is 100. So, if I could come to this little embryo, and I want to give it one extra standard deviation of height, I only need to edit 100. I only need to flip 100 minus variance to plus variance. These are very rough numbers. But, one standard deviation is the square root of “n”. If I flip a coin “n” times, I want a better outcome in terms of the number of ratio heads to tails. I want to increase it by one standard deviation. I only need to flip the square root of “n” heads because if you flip a lot, you will get a narrow distribution that peaks around half, and the width of that distribution is the square root of “n”. Once I tell you, “Hey, your height is controlled by 10,000 variants, and I only need to flip 100 genetic variants to make you one standard deviation for a male,” (that would be three inches tall, two and a half or three inches taller), you suddenly realize, “Wait a minute, there are a lot of variants up for grabs there. If I could flip 500 variants in your genome, I would make you five standard deviations taller, you'd be seven feet tall.” I didn't even have to do that much work, and there's a lot more variation where that came from. I could have flipped even more because I only flipped 500 out of 10,000, right? So, there's this quasi-infinite well of variation that evolution or genetic engineers could act on. Again, the early population geneticists who bred corn and animals know this. This is something they explicitly know about because they've done calculations. Interestingly, the human geneticists who are mainly concerned with diseases and stuff, are often unfamiliar with the math that the animal breeders already know. You might be interested to know that the milk you drink comes from heavily genetically-optimized cows bred artificially using almost exactly the same technologies that we use at genomic prediction. But, they're doing it to optimize milk production and stuff like this. So there is a big well of variance. It's a consequence of the trait's poly genicity. On the longevity side of things, it does look like people could “be engineered” to live much longer by flipping the variants that make the risk for diseases that shorten your life. The question is then “Why didn't evolution give us life spans of thousands of years?” People in the Bible used to live for thousands of years. Why don't we? I mean, *chuckles* that probably didn’t happen. But the question is, you have this very high dimensional space, and you have a fitness function. How big is the slope in a particular direction of that fitness function? How much more successful reproductively would Joe caveman have been if he lived to be 150 instead of only, 100 or something? There just hasn't been enough time to explore this super high dimensional space. That's the actual answer. But now, we have the technology, and we're going to f*****g explore it fast. That's the point that the big lightbulb should go off. We’re mapping this space out now. Pretty confident in 10 years or so, with the CRISPR gene editing technologies will be ready for massively multiplexed edits. We'll start navigating in this high-dimensional space as much as we like. So that's the more long-term consequence of the scientific insights.Dwarkesh Patel 40:53 Yeah, that's super interesting. What do you think will be the plateau for a trait of how long you’ll live? With the current data and techniques, you think it could be significantly greater than that?Steve Hsu 41:05 We did a simple calculation—which amazingly gives the correct result. This polygenic predictor that we built (which isn't perfect yet but will improve as we gather more data) is used in selecting embryos today. If you asked, out of a billion people, “What's the best person typically, what would their score be on this index and then how long would they be predicted to live?”’ It's about 120 years. So it's spot on. One in a billion types of person lives to be 120 years old. How much better can you do? Probably a lot better. I don't want to speculate, but other nonlinear effects, things that we're not taking into account will start to play a role at some point. So, it's a little bit hard to estimate what the true limiting factors will be. But one super robust statement, and I'll stand by it, debate any Nobel Laureate in biology who wants to discuss it even, is that there are many variants available to be selected or edited. There's no question about that. That's been established in animal breeding in plant breeding for a long time now. If you want a chicken that grows to be *this* big, instead of *this* big, you can do it. You can do it if you want a cow that produces 10 times or 100 times more milk than a regular cow. The egg you ate for breakfast this morning, those bio-engineered chickens that lay almost an egg a day… A chicken in the wild lays an egg a month. How the hell did we do that? By genetic engineering. That's how we did it. Dwarkesh Patel 42:51 Yeah. That was through brute artificial selection. No fancy machine learning there.Steve Hsu 42:58 Last ten years, it's gotten sophisticated machine learning genotyping of chickens. Artificial insemination, modeling of the traits using ML last ten years. For cow breeding, it's done by ML. First Mover AdvantageDwarkesh Patel 43:18 I had no idea. That's super interesting. So, you mentioned that you're accumulating data and improving your techniques over time, is there a first mover advantage to a genomic prediction company like this? Or is it whoever has the newest best algorithm for going through the biobank data? Steve Hsu 44:16 That's another super question. For the entrepreneurs in your audience, I would say in the short run, if you ask what the valuation of GPB should be? That's how the venture guys would want me to answer the question. There is a huge first mover advantage because they're important in the channel relationships between us and the clinics. Nobody will be able to get in there very easily when they come later because we're developing trust and an extensive track record with clinics worldwide—and we're well-known. So could 23andme or some company with a huge amount of data—if they were to get better AI/ML people working on this—blow us away a little bit and build better predictors because they have much more data than we do? Possibly, yes. Now, we have had core expertise in doing this work for years that we're just good at it. Even though we don't have as much data as 23andme, our predictors might still be better than theirs. I'm out there all the time, working with biobanks all around the world. I don't want to say all the names, but other countries are trying to get my hands on as much data as possible.But, there may not be a lasting advantage beyond the actual business channel connections to that particular market. It may not be a defensible, purely scientific moat around the company. We have patents on specific technologies about how to do the genotyping or error correction on the embryo, DNA, and stuff like this. We do have patents on stuff like that. But this general idea of who will best predict human traits from DNA? It's unclear who's going to be the winner in that race. Maybe it'll be the Chinese government in 50 years? Who knows?Dwarkesh Patel 46:13 Yeah, that's interesting. If you think about a company Google, theoretically, it's possible that you could come up with a better algorithm than PageRank and beat them. But it seems like the engineer at Google is going to come up with whatever edge case or whatever improvement is possible.Steve Hsu 46:28 That's exactly what I would say. PageRank is deprecated by now. But, even if somebody else comes up with a somewhat better algorithm if they have a little bit more data, if you have a team doing this for a long time and you're focused and good, it's still tough to beat you, especially if you have a lead in the market.Dwarkesh Patel 46:50 So, are you guys doing the actual biopsy? Or is it just that they upload the genome, and you're the one processing just giving recommendations? Is it an API call, basically?Steve Hsu 47:03 It's great, I love your question. It is totally standard. Every good IVF clinic in the world regularly takes embryo biopsies. So that's standard. There’s a lab tech doing that. Okay. Then, they take the little sample, put it on ice, and ship it. The DNA as a molecule is exceptionally robust and stable. My other startup solves crimes that are 100 years old from DNA that we get from some semen stain on some rape victim, serial killer victims bra strap, we've done stuff that.Dwarkesh Patel 47:41 Jack the Ripper, when are we going to solve that mystery?Steve Hsu 47:44 If they can give me samples, we can get into that. For example, we just learned that you could recover DNA pretty well if someone licks a stamp and puts on their correspondence. If you can do Neanderthals, you can do a lot to solve crimes. In the IVF workflow, our lab, which is in New Jersey, can service every clinic in the world because they take the biopsy, put it in a standard shipping container, and send it to us. We’re actually genotyping DNA in our lab, but we've trained a few of the bigger clinics to do the genotyping on their site. At that point, they upload some data into the cloud and then they get back some stuff from our platform. And at that point it's going to be the whole world, every human who wants their kid to be healthy and get the best they can– that data is going to come up to us, and the report is going to come back down to their IVF physician. Dwarkesh Patel 48:46 Which is great if you think that there's a potential that this technology might get regulated in some way, you could go to Mexico or something, have them upload the genome (you don't care what they upload it from), and then get the recommendations there. Steve Hsu 49:05 I think we’re going to evolve to a point where we are going to be out of the wet part of this business, and only in the cloud and bit part of this business. No matter where it is, the clinics are going to have a sequencer, which is *this* big, and their tech is going to quickly upload and retrieve the report for the physician three seconds later. Then, the parents are going to look at it on their phones or whatever. We’re basically there with some clinics. It’s going to be tough to regulate because it’s just this. You have the bits and you’re in some repressive, terrible country that doesn’t allow you to select for some special traits that people are nervous about, but you can upload it to some vendor that’s in Singapore or some free country, and they give you the report back. Doesn’t have to be us, we don’t do the edgy stuff. We only do the health-related stuff right now. But, if you want to know how tall this embryo is going to be…I’ll tell you a mind-blower! When you do face recognition in AI, you're mapping someone's face into a parameter space on the order of hundreds of parameters, each of those parameters is super heritable. In other words, if I take two twins and photograph them, and the algorithm gives me the value of that parameter for twin one and two, they're very close. That's why I can't tell the two twins apart, and face recognition can ultimately tell them apart if it’s really good system. But you can conclude that almost all these parameters are identical for those twins. So it's highly heritable. We're going to get to a point soon where I can do the inverse problem where I have your DNA and I predict each of those parameters in the face recognition algorithm and then reconstruct the face. If I say that when this embryo will be 16, that is what she will look like. When she's 32, this is what she's going to look like. I'll be able to do that, for sure. It's only an AI/ML problem right now. But basic biology is clearly going to work. So then you're going to be able to say, “Here's a report. Embryo four is so cute.” Before, we didn't know we wouldn't do that, but it will be possible. Dwarkesh Patel 51:37 Before we get married, you'll want to see what their genotype implies about their faces' longevity. It's interesting that you hear stories about these cartel leaders who will get plastic surgery or something to evade the law, you could have a check where you look at a lab and see if it matches the face you would have had five years ago when they caught you on tape.Steve Hsu 52:02 This is a little bit back to old-school Gattaca, but you don't even need the face! You can just take a few molecules of skin cells and phenotype them and know exactly who they are. I've had conversations with these spooky Intel folks. They're very interested in, “Oh, if some Russian diplomat comes in, and we think he's a spy, but he's with the embassy, and he has a coffee with me, and I save the cup and send it to my buddy at Langley, can we figure out who this guy is? And that he has a daughter who's going to Chote? Can do all that now.Dwarkesh Patel 52:49 If that's true, then in the future, world leaders will not want to eat anything or drink. They'll be wearing a hazmat suit to make sure they don't lose a hair follicle.Steve Hsu 53:04 The next time Pelosi goes, she will be in a spacesuit if she cares. Or the other thing is, they're going to give it. They're just going to be, “Yeah, my DNA is everywhere. If I'm a public figure, I can't track my DNA. It's all over.”Dwarkesh Patel 53:17 But the thing is, there's so much speculation that Putin might have cancer or something. If we have his DNA, we can see his probability of having cancer at age 70, or whatever he is, is 85%. So yeah, that’d be a very verified rumor. That would be interesting. Steve Hsu 53:33 I don't think that would be very definitive. I don't think we'll reach that point where you can say that Putin has cancer because of his DNA—which I could have known when he was an embryo. I don't think it's going to reach that level. But, we could say he is at high risk for a type of cancer. Genomics in datingDwarkesh Patel 53:49 In 50 or 100 years, if the majority of the population is doing this, and if the highly heritable diseases get pruned out of the population, does that mean we'll only be left with lifestyle diseases? So, you won't get breast cancer anymore, but you will still get fat or lung cancer from smoking?Steve Hsu 54:18 It's hard to discuss the asymptotic limit of what will happen here. I'm not very confident about making predictions like that. It could get to the point where everybody who's rich or has been through this stuff for a while, (especially if we get the editing working) is super low risk for all the top 20 killer diseases that have the most life expectancy impact. Maybe those people live to be 300 years old naturally. I don't think that's excluded at all. So, that's within the realm of possibility. But it's going to happen for a few lucky people like Elon Musk before it happens for shlubs like you and me. There are going to be very angry inequality protesters about the Trump grandchildren, who, models predict will live to be 200 years old. People are not going to be happy about that.Dwarkesh Patel 55:23 So interesting. So, one way to think about these different embryos is if you're producing multiple embryos, and you get to select from one of them, each of them has a call option, right? Therefore, you probably want to optimize for volatility as much, or if not more than just the expected value of the trait. So, I'm wondering if there are mechanisms where you can increase the volatility in meiosis or some other process. You just got a higher variance, and you can select from the tail better.Steve Hsu 55:55 Well, I'll tell you something related, which is quite amusing. So I talked with some pretty senior people at the company that owns all the dating apps. So you can look up what company this is, but they own Tinder and Match. They’re kind of interested in perhaps including a special feature where you upload your genome instead of Tinder Gold / Premium. And when you match- you can talk about how well you match the other person based on your genome. One person told me something shocking. Guys lie about their height on these apps. Dwarkesh Patel 56:41 I’m shocked, truly shocked hahaha. Steve Hsu 56:45 Suppose you could have a DNA-verified height. It would prevent gross distortions if someone claims they're 6’2 and they’re 5’9. The DNA could say that's unlikely. But no, the application to what you were discussing is more like, “Let's suppose that we're selecting on intelligence or something. Let's suppose that the regions where your girlfriend has all the plus stuff are complementary to the regions where you have your plus stuff. So, we could model that and say, because of the complementarity structure of your genome in the regions that affect intelligence, you're very likely to have some super intelligent kids way above your, the mean of your you and your girlfriend's values. So, you could say things like it being better for you to marry that girl than another. As long as you go through embryo selection, we can throw out the bad outliers. That's all that's technically feasible. It's true that one of the earliest patent applications, they'll deny it now. What's her name? Gosh, the CEO of 23andme…Wojcicki, yeah. She'll deny it now. But, if you look in the patent database, one of the very earliest patents that 23andme filed when they were still a tiny startup was about precisely this: Advising parents about mating and how their kids would turn out and stuff like this. We don't even go that far in GP, we don't even talk about stuff like that, but they were thinking about it when they founded 23andme.Dwarkesh Patel 58:38 That is unbelievably interesting. By the way, this just occurred to me—it's supposed to be highly heritable, especially people in Asian countries, who have the experience of having grandparents that are much shorter than us, and then parents that are shorter than us, which suggests that the environment has a big part to play in it malnutrition or something. So how do you square that our parents are often shorter than us with the idea that height is supposed to be super heritable.Steve Hsu 59:09 Another great observation. So the correct scientific statement is that we can predict height for people who will be born and raised in a favorable environment. In other words, if you live close to a McDonald's and you're able to afford all the food you want, then the height phenotype becomes super heritable because the environmental variation doesn't matter very much. But, you and I both know that people are much smaller if we return to where our ancestors came from, and also, if you look at how much food, calories, protein, and calcium they eat, it's different from what I ate and what you ate growing up. So we're never saying the environmental effects are zero. We're saying that for people raised in a particularly favorable environment, maybe the genes are capped on what can be achieved, and we can predict that. In fact, we have data from Asia, where you can see much bigger environmental effects. Age affects older people, for fixed polygenic scores on the trait are much shorter than younger people.Ancestral populationsDwarkesh Patel 1:00:31 Oh, okay. Interesting. That raises that next question I was about to ask: how applicable are these scores across different ancestral populations?Steve Hsu 1:00:44 Huge problem is that most of the data is from Europeans. What happens is that if you train a predictor in this ancestry group and go to a more distant ancestry group, there's a fall-off in the prediction quality. Again, this is a frontier question, so we don't know the answer for sure. But many people believe that there's a particular correlational structure in each population, where if I know the state of this SNP, I can predict the state of these neighboring SNPs. That is a product of that group's mating patterns and ancestry. Sometimes, the predictor, which is just using statistical power to figure things out, will grab one of these SNPs as a tag for the truly causal SNP in there. It doesn't know which one is genuinely causal, it is just grabbing a tag, but the tagging quality falls off if you go to another population (eg. This was a very good tag for the truly causal SNP in the British population. But it's not so good a tag in the South Asian population for the truly causal SNP, which we hypothesize is the same). It's the same underlying genetic architecture in these different ancestry groups. We don't know if that's a hypothesis. But even so, the tagging quality falls off. So my group spent a lot of our time looking at the performance of predictor training population A, and on distant population B, and modeling it trying to figure out trying to test hypotheses as to whether it's just the tagging decay that’s responsible for most of the faults. So all of this is an area of active investigation. It'll probably be solved in five years. The first big biobanks that are non-European are coming online. We're going to solve it in a number of years.Dwarkesh Patel 1:02:38 Oh, what does the solution look like? Unless you can identify the causal mechanism by which each SNP is having an effect, how can you know that something is a tag or whether it's the actual underlying switch?Steve Hsu 1:02:54 The nature of reality will determine how this is going to go. So we don't truly know if the innate underlying biology is true. This is an amazing thing. People argue about human biodiversity and all this stuff, and we don't even know whether these specific mechanisms that predispose you to be tall or having heart disease are the same in these different ancestry groups. We assume that it is, but we don't know that. As we get further away to Neanderthals or Homo Erectus, you might see that they have a slightly different architecture than we do. But let's assume that the causal structure is the same for South Asians and British people. Then it's a matter of improving the tags. How do I know if I don't know which one is causal? What do I mean by improving the tags? This is a machine learning problem. If there's a SNP, which is always coming up as very significant when I use it across multiple ancestry groups, maybe that one's casual. As I vary the tagging correlations in the neighborhood of that SNP, I always find that that one is the intersection of all these different sets, making me think that one's going to be causal. That's a process we're engaged in now—trying to do that. Again, it's just a machine learning problem. But we need data. That's the main issue.Dwarkesh Patel 1:04:32 I was hoping that wouldn't be possible, because one way we might go about this research is that it itself becomes taboo or causes other sorts of bad social consequences if you can definitively show that on certain traits, there are differences between ancestral populations, right? So, I was hoping that maybe there was an evasion button where we can't say because they're just tags and the tags might be different between different ancestral populations. But with machine learning, we’ll know.Steve Hsu 1:04:59 That's the situation we're in now, where you have to do some fancy analysis if you want to claim that Italians have lower height potential than Nordics—which is possible. There's been a ton of research about this because there are signals of selection. The alleles, which are activated in height predictors, look like they've been under some selection between North and South Europe over the last 5000 years for whatever reason. But, this is a thing debated by people who study molecular evolution. But suppose it's true, okay? That would mean that when we finally get to the bottom of it, we find all the causal loci for height, and the average value for the Italians is lower than that for those living in Stockholm. That might be true. People don't get that excited? They get a little bit excited about height. But they would get really excited if this were true for some other traits, right?Suppose the causal variants affecting your level of extraversion are systematic, that the average value of those weighed the weighted average of those states is different in Japan versus Sicily. People might freak out over that. I'm supposed to say that's obviously not true. How could it possibly be true? There hasn't been enough evolutionary time for those differences to arise. After all, it's not possible that despite what looks to be the case for height over the last 5000 years in Europe, no other traits could have been differentially selected for over the last 5000 years. That's the dangerous thing. Few people understand this field well enough to understand what you and I just discussed and are so alarmed by it that they're just trying to suppress everything. Most of them don't follow it at this technical level that you and I are just discussing. So, they're somewhat instinctively negative about it, but they don't understand it very well.Dwarkesh Patel 1:07:19 That's good to hear. You see this pattern that by the time that somebody might want to regulate or in some way interfere with some technology or some information, it already has achieved wide adoption. You could argue that that's the case with crypto today. But if it's true that a bunch of IVF clinics worldwide are using these scores to do selection and other things, by the time people realize the implications of this data for other kinds of social questions, this has already been an existing consumer technology.Is this eugenics?Steve Hsu 1:07:58 That's true, and the main outcry will be if it turns out that there are massive gains to be had, and only the billionaires are getting them. But that might have the consequence of causing countries to make this free part of their national health care system. So Denmark and Israel pay for IVF. For infertile couples, it's part of their national health care system. They're pretty aggressive about genetic testing. In Denmark, one in 10 babies are born through IVF. It's not clear how it will go. But we're in for some fun times. There's no doubt about that.Dwarkesh Patel 1:08:45 Well, one way you could go is that some countries decided to ban it altogether. And another way it could go is if countries decided to give everybody free access to it. If you had to choose between the two, you would want to go for the second one. Which would be the hope. Maybe only those two are compatible with people's moral intuitions about this stuff. Steve Hsu 1:09:10 It’s very funny because most wokist people today hate this stuff. But, most progressives like Margaret Sanger, or anybody who was the progressive intellectual forebears of today's wokist, in the early 20th century, were all that we would call today in Genesis because they were like, “Thanks to Darwin, we now know how this all works. We should take steps to keep society healthy and (not in a negative way where we kill people we don't like, but we should help society do healthy things when they reproduce, and have healthy kids).” Now, this whole thing has just been flipped over among progressives. Dwarkesh Patel 1:09:52 Even in India, less than 50 years ago, Indira Gandhi, she's on the left side of India's political spectrum. She was infamous for putting on these forced sterilization programs. Somebody made an interesting comment about this where they were asked, “Oh, is it true that history always tilts towards progressives? And if so, isn't everybody else doomed? Aren't their views doomed?”The person made a fascinating point: whatever we consider left at the time tends to be winning. But what is left has changed a lot over time, right? In the early 20th century, prohibition was a left cause. It was a progressive cause, and that changed, and now the opposite is the left cause. But now, legalizing pot is progressive. Exactly. So, if Conquest’s second law is true, and everything tilts leftover time, just change what is left is, right? That's the solution. Steve Hsu 1:10:59 No one can demand that any of these woke guys be intellectually self-consistent, or even say the same things from one year to another? But one could wonder what they think about these literally Communist Chinese. They’re recycling huge parts of their GDP to help the poor and the southern stuff. Medicine is free, education is free, right? They're clearly socialists, and literally communists. But in Chinese, the Chinese characters for eugenics is a positive thing. It means healthy production. But more or less, the whole viewpoint on all this stuff is 180 degrees off in East Asia compared to here, and even among the literal communists—so go figure.Dwarkesh Patel 1:11:55 Yeah, very based. So let's talk about one of the traits that people might be interested in potentially selecting for: intelligence. What is the potential for us to acquire the data to correlate the genotype with intelligence?Steve Hsu 1:12:15 Well, that's the most personally frustrating aspect of all of this stuff. If you asked me ten years ago when I started doing this stuff what were we going to get, everything was gone. On the optimistic side of what I would have predicted, so everything's good. Didn't turn out to be interactively nonlinear, or it didn't turn out to be interactively pleiotropic. All these good things, —which nobody could have known a priori how they would work—turned out to be good for gene engineers of the 21st century. The one frustrating thing is because of crazy wokeism, and fear of crazy wokists, the most interesting phenotype of all is lagging b
Halooo smart people pendengar setia IAAS Wanna Talks! Database? Apa yang pertama kali terlintas di pikiranmu? Pusheeeeng? Hahahah sama guys. Tapi dari Kak Aisyah dari IAAS Indonesia bakal kasih perspektif lain tentang pengelolaan database kepartnershipan. Penasaran? langsung aja cabs dengerin!
How this episode started, and where it went, couldn't possibly be further apart. We discuss the loss of the most badass Bastard of us all, Will's grandma, and then move on to just what it takes to have a funeral these days. Brent wraps things up talking about his vacation and catching Covid (I'M NOT DEAD, HAHAHAH!) We've somehow made it 50 whole episodes of this shitshow!
TIME FOR THE AG DOLL EMPIRE TO RISE! This is our time to shine!!!!!! Thanks for listening to the most random episode I could ever come up with HAHAHAH xo Hallie Shop The Common Room: HTTP://THECOMMONROOMSHOP.COM
Happy Thursday, mga inday! Kumain na ba u? Kain na ü hihi. Tapos habang kumakain u pakinggan u na latest episode namin hihi. Kasi alam namin na panay kayo reklamo na palagi namin kayong pinapatay sa inggit. Today naman kuwento namin yung mga times na kami ang halos kami naman ang muntikang mamatay sa inggit with JOLENE. Kilala pa ba ng mga bagets si Jolene? Hahahah. Ilang araw naming pinagawayan title ng episode na to. Kaya kinig na mga kapitbahay! lablab
Wait...NWO...AT NWO?!?!?! HAHAHAH! I have so many questions about this show....why is Mr Perfect here? Why are RVD and Goldust fighting? Why is Stephanie McMahon's acting so horrendous? We try to answer all these questions and more on this episode; it's a weird PPV but a fun podcast! Joined by Nick and Sacco from the "Universal Wrestling Podcast", check them out wherever you listen to podcasts! https://www.uwpod.com/ @TheUWPod on Twitter https://twitter.com/TheUWPod @uwpodcast on Instagram https://www.instagram.com/uwpodcast/ Follow me! ApronBump.com @Apron_Bump on Instagram https://www.instagram.com/Apron_Bump/ @ApronBump on Twitter https://twitter.com/ApronBump “Apron Bump” on Facebook https://www.facebook.com/Apron-Bump-1... “Apron Bump” on Youtube https://www.youtube.com/c/ApronBump
Em Tempo de Matar, Nicolas Cage nos faz odiar tudo e todos. Nos tirem desse sofrimento! Hahahah! (é sério) Bem-vindos ao Nicolas, a investigação aleatória e recorrente sobre a carreira do grande ator internacional Nicolas Cage. Com PJ Brandão, Rudy, Jotapê e Rafael Mordente. COLABORE COM NOSSO APOIA.SE! E no próximo episódio... Arsenal, 2017. Nos encontre por aí: Grupo de ouvintes do Nicolas no Telegram / HQ Sem Roteiro / Iradex / The Brazilian Rafael Mordente / Decrépitos / Garotão Bronzeado @pedropjbrandao / @rudylonia / @jumbopaulo / @flaviagasi no Twitter / @rafaelmordente no Twitter/ @rafaelmordente no Instagram / rafaelmordente no Twitch Créditos: Edição: Roberto Rudiney e JP Martins Arte: JP Martins Voz de veludo do início: Anderson Dias
Apakah episode ini akan ada part 2? HAHAHAH
HAHAHAH!! Wenn ihr wissen wollt wieso ich lache, hört euch diese Folge an!!
This week's episode endured a whole lot of caffeine-endured mic peaking. Sorry y'all, Sydney is loud. And Adam is once again done. Hahahah. Enjoy our ADHD centric convo. Hope you all have a great week!! --- Support this podcast: https://podcasters.spotify.com/pod/show/sillytalk/support
We dive deep into NFTs...actually, not really because we still have NO idea what they are. Also, Caleb says he could stay on the run from the law forever. Hahahah. Yeah right. --- Support this podcast: https://podcasters.spotify.com/pod/show/jeffandcaleb/support
E ai pessoal, firmes e fortes igual prego no angu? Hahahah. No episódio dessa semana trouxe uma França pré-revolucionária. Trouxe algumas informações e fatos importantes que nos ajudam a compreender a França do Século XVIII que beira à Revolução Francesa. Bora lá!
Masih diluar nih take nya! Topik kali ini kita bakal ngebahas tentang salah satu nama panggilan kita di basecamp yaitu “Sentot”. Siapa sih sentot? Kenapa sih namanya sentot?. Penasaran? Gak kan. Sama dong HAHAHAH. Yaudah ah langsung aja dengerin! Jaga kesehatan ya guys, dengerin podlot buat nambah imun guys jangan lupa! --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app
John and Judith and Arsenic!
Buat #GengNgontek yang udah kangen denger suara kitaaa nihhh! Hahahah we definitely baacckk! Langsung ngobrolin seputar klaim BPJamsostek yang sungguh amat mudah, cepat, anti ribet-ribet club karena pelayanan kita semua sudah full digitalisasi, biar ga last year donggg.. Dan pastinya semua untuk kenyamanan dan keamanan peserta di masa pandemi. Serunya lagiii, kita ngobrol sama beliau yang approve seluruh proses klaim di Bekasi Kota! Jadi kita tau dehh, estimasi proses klaim itu gimana sihhh? Yuukk #GengNgontek!
Welcome back for Episode 11! We've made some mistakes, we've been ghosted & we dive into what your COVID-19 mask says about you. You won't want to miss this, See you in 6 months....HAHAHAH
WHATS UP SHITHEADS!? It's Righteous Ryan and Travis Gone Wild back at it again! This week we get straight into ranking different types of people. Spandex bikers, horse girls, car guys, vegans, overly religious, cross fitters, crystal believers. They all suck! HAHAHAH. Do you have more personalities that you'd add on the sucky list? Follow us on Instagram @dudestalkingshit Follow Travis on Instagram @ilikehotwheels Follow Ryan on Instagram @drunkryan
Happy Halloween, on this episode Uncle Jim and THE Leslie Hoffman talk horro movies. What kinda stunts are invloved, is working a horror movie different that working on Star Trek? What was it like to wear Freddy's glove and sweater? Studio lines will be open (646)668-2433, NO RUNNING IN THE HALLWAYS.....HAHAHAH
Fala galera!!! Mais um episódio no ar e esse com um tema um pouco polêmico né!? Hahahah. Falamos um pouco sobre essa resistência que a sociedade tem em ver e aceitar as mulheres nesse mundo, que também é dela; e para ajudar nesse bate-papo tivemos duas convidadas que contaram um pouco sobre suas experiências.
Akhirnya di temani oleh Raifan yang ketiduran tadi siang, hahaha. Kali ini kedatangan tamu dari kandidat no 3, Puan Chantika Alif Asshidiq. Kami membahas seputar latar belakang, tujuan, problematika organisasi hingga role model lho. Oiya, quote of the day "Role model aku, itu cuma diri aku sendiri" - Raifan. Hahahah penasaran kan? Enjoyy!!
Nempelin nomor Whatsapp di jok motor Cowok dengan harapan dapet pasangan?? Hahahah namanya juga usaha Atau udah lama in relationship tapi sering nyiksa batin karena hubungan ga sehat tapi tetep aja dilanjutin dengan dalih "Ga siap sendiri"? Huhuhu Markimak, mari kita simak bund, si Jola mulai aktif nih
Just a little update for you guys! Hahahah. It's been real, online dating, buuuuuttttt, I'm awwwwf! --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app --- Send in a voice message: https://anchor.fm/simpin-sibs/message
This is the first episode of our mini series for this podcast season. And it's way different then you think. Hahahah. --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app --- Send in a voice message: https://anchor.fm/simpin-sibs/message
Hahahah masih percaya ga kalian dengan kata kata YouTube lebih dari tv, kalo gw sih engga.. buktinya youtube banyaknya artis tv, channel tv.. dan kita yang the real content creator hanya mendapatkan receh:(( ko kejam banget ya.. yaudah lah jan lup kasi support ke irgihhh.. https://sociabuzz.com/irghifari/support --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app
Vejam só a diversidade desse podcast HAHAAHAH Cá estou eu reagindo aos prazeres mais estranhos dos ouvintes e é claro me divertindo muito com os relatos HAHAHAH vem ouvir esse episódio!!! Só vem! Segue a gente nas redes: insta: @empretecendocast / @esbragga email: empretecendocast@gmail.com
Haiiii apa kabar sahabat nyolot? Pasti pada gak peduli kan? Hahahah kali ini kita bakal ngebahas kesalahan manusia yaitu salah upload dan salah pegang pokoknya yang salah kita bahas disini! Tapi ini dari opini kita ya! Yuk yang ada kritik dan saran bisa DM ig kita masing - masing ya! Mau follow juga boleh! Follow dan share jangan lupa guys! --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app
This game of Mental Giants almost pushed Anna over the edge… And the laughs just keep on coming! The post Mental Giants – Anna turns and the game is in doubt hahahah!!! appeared first on JOY Breakfast.
Hal yang paling sering dilakukan oleh laki adalah sok gengsi, harus ngeluarin duit, nganterin, dll, karena kalo nggak katanya nggak gentle, eh iya nggak sih? HAHAHAH dengerin aja kali ya!
Hahahah im just cracking up because I legitimately tried to drink coffee with my mask on - also remember if you’re tired IT IS ABSOLUTELY NORMAL! Tune in
HAHAHAH okay! Katie & Claire talk about spray tans and lots of questions and a bunch of other stuff I forgot but you guys don’t read this anyways right? Lol! --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app
So, apparently you can get banned from tinder Hahahah wait till you hear my story about this - I also forgot to say that i emailed them to complain about this Bc it’s tinder - who the the fuck gets banned from tinder dude?! Lmaooo
Fala galeraaaaaa! Ep30 chegando pra fazer você pensar quais são os top 3 em qualquer assunto, desde coisas clichês até aleatoriedades e, obviamente, gerando algumas polêmicas de leve..Tem gente aí querendo fazer Os especialistas terem um grupo de haters, formar uma gangue de Squirtles e pagando de conselheiro amoroso HAHAHAH..Instagram: @castexpert..Apresentação: Lucas Gomes @dhomespassos / Gabriel Gonçalves @biel_g / Otávio Costa @otavioecosta
Esse drops era pra ser o easter egg do tavatoa #10, mas tava tão engraçado que achamos melhor lançar separado HAHAHAH com a participação do gênio Eduardo Dantas, não da pra deixar passar hahaha da um confere e manda aquele feedback brabo. Ps: Feliz dias das mulheres para todas essas maravilhosas e desculpem qualquer coisa HAHAHA Nos siga nas nossas redes sociais! http://instagram.com/tavatoa http://twitter.com/tavatoacast tavatoacast@gmail.com
we were messing around --- Send in a voice message: https://anchor.fm/calvin-kerridge/message
In this episode of Adventures With Abigail I asked you guys to ask me questions, and now I'm answering your questions, that you guys asked me! Hahahah!
Gua ngakak anjir liat akun salah satu membernya yaitu letjend reni khairani miller sunda empire polwan wanna be
Follow us on twitter @_meridians yes, I was supposed to say hapi 2020 HAHAHAH me tired to record it again
Manoooo 2019 já respirando por aparelhos, mas antes da gente lascar um caixão nesse ano sinistro, que tal um remember ?!? O bagulho foi doido e vocês não vão acreditar no que trouxemos hoje nessa caótica retrospectivis .. é cada notícia que só mostra quanto o mundo tá viajado demais e que o ser humano tem que acabar kkkkkkkkkkkkE é craro que não esquecemos dos memes e zueras que dominaram a internata BR, solta o play e let's bora !! Ps: sabia que escutar/ajudar Os especialistas custa menos de 3 reais? KkkkkkE que não adianta você se vestir de mauricinho e pedir para o Gabriel parar com o caos não é efetivo? Hahahah..Instagram: @castexpertApresentação: Lucas Gomes @dhomespassos / Gabriel Gonçalves @biel_g / Otávio Costa @otavioecosta
Naar een moeilijke opstart van mijn eigen bedrijf , krijg ik eindelijk de energie om weer mezelf te zijn! Ik ben vrijgezel en heb een onderneming ! Nu is het tijd om geld te verdienen en mijn netwerk uit te breiden met nieuwe partners en samenwerkingen to make some sshhmoney !! Zoals Cardi B zou zeggen Hahahah . Ik leg jullie in deze aflevering precies uit hoe en wat je moet doen om te doen wat ik doe en op welke manier je veel geld kan verdienen have fun & let me know!
Hai Ultimates, ini episode perdana gue nih. Gue kan anak TV ya, pasti pada penasaran dong kenapa tiba tiba gue banting stir ke Podcast? Ini karena gue dapet tugas dari dosen #IntroductionToCommunicationScience gue buat bikin podcast tentang hambatan komunikasi. Gue berasa pinter banget nih pas bikin episode ini HAHAHAH. Doain ya, nilai gue bagus kebantu podcast ini
HAHAHAH! If you want to prevent Alzheimer's, then pay attention to the acronym NEURO. It was developed by Doctors Dean and Ayesha Sherzia. N is for Nutrition E is for Exercise U is for Unwinding R is for Rest O is for optimizing cognitive and social activities Hope this helps!
E lá vem o paaaadre!! HAHAHAH! Hoje temos um episódio sobre essa época maravilhosa, FESTA JUNINA!! Vem que vamos contar as melhores (piores) histórias envolvendo rojões, dedos queimados, fogueiras e muito mais! Confia no São João!
Essa foi uma das edições mais doidas que já fizemos! HAHAHAH.
Kid Fury is family. He's one of my heroes and he doesn't know how much he inspires me. He'll probably know if he reads this but I won't tell him to because, you know- toxic masculinity. Hahahah. Anyway, this episode is great and I hope y'all fux with it. PS: If you like the podcast, share it with your friends! Trying to build an audience and keep the convos going.
Branko sits down with club coaches Matt and Esther Fleigle at the Reno Pole Vault Summit. They discuss what its like coaching in Minnesota, and Branko thought Jersey winters were tough, as well as what they think club coaches need or should do for their members, like attending meets. Oh and that Reno Pole Summit was pretty cool too. Hahahah
In this episode we find out a little more about what makes "werkhunty" and "makeupbygilly" tick! Please excuse all the “likes” and “ummms” and all the small errors... I’m learrrrrrning! Hahahah! Love you all!
Hahahah gak tau kenapa paling gak suka melihat startup dengan founder yang seperti ini, ditambah kalau dia sebenarnya adalah seorang devloper atau progremmer.
-- Inscreva-se em nosso canal! ----- Timão inicia o Brasileirão com o pé esquerdo... Do Rodriguinho marcando gol pra decidir a partida! Hahahah! A Irmandade debate o jogo e mais as novidades da semana! Jogos desta semana: - Domingo, 15/Abr - Corinthians x Fluminense (Campeonato Brasileiro - 1ª rodada) Gostou do nosso podcast? Então assine o nosso canal e siga-nos no SoundCloud! Siga a Irmandade Corinthiana em todas as redes sociais! www.facebook.com/irmandadecorinthiana www.instagram.com/irmandadecorinthiana www.twitter.com/irmandadetimao @irmandadecorinthiana www.youtube.com/channel/irmandadecorinthiana ou envie-nos um e-mail para irmandadecorinthiana@outlook.com
This week the guys get you loaded up for your league winning moves. The mid-way point is a week away and it’s time to make your push. We get into bye week trade strategies, players who numbers aren’t telling the whole story, Amari Cooper, Aaron Jones, why it’s hard to trust Atlanta, and why Carson Wentz makes us rock hard. Will Tyler have to eat a turd this week? Hahahah, no stop it. JStew sucks fam.
Vols lost let's get red
Vols lost let's get red
Télécharger l'épisode⎮⎮ S'abonner La haine. La douleur. La peur. L'odeur du sang. Les injections.. Mais encore plus: LA HAINE TOTALE. Stuffy était avachi sur le bloc en ciment servant de lit au fond de son résidu de cellule. Tout était humide, la prison elle-même se trouvait en bord de mer, et au 20eme sous-sol les infiltrations d'eau était encore courante. Pas de lumière, juste la lueur du néon bleu métallique au milieu d'un long couloir. Au loin un râle.. Puis plus rien. Sans doute un prisonnier qui venait de se réveiller, réalisant que son cauchemar se trouvait dans la réalité et pas dans le monde des songes. Amorphe, le cerveau de Stuffy commençait à émerger des brumes vaporeuses dans lesquelles le sérum qui lui était administré le plongeait régulièrement. Stuffy est un Mental, un être capable d'agir sur les esprits des autres à courte distance, d'entendre les pensées proches, de ressentir de l'empathie pour des émotions d'êtres lointains. Stuffy est également un membre des forces de sécurité de Mater One, un agent actif rompu à de nombreuses techniques de combat, un des meilleurs homme de la redoutable Section 9 du service de sécurité de l'armée, sous les ordre du Contre-Amiral Pofeus. Mais pour bien comprendre le personnage il faut ajouter que Stuffy est un mutualiste, un utopiste qui pense qu'un modèle de société basé sur le profit n'ira jamais aussi loin qu'un autre basé sur le partage. Un militant parmi les gardiens des clefs de l'ordre établi. Cela l'avait récemment rapproché de celle qui troublait son sommeil depuis qu'il l'avait rencontré. Ses pensées les plus profondes, les plus intimes et les plus cachées recelaient une femme habillée de gaze blanche, dansant sur elle même dans un moment unique de magie musicale. La Princesse héritière de l'ancienne monarchie de Mater One: Azala. Elle était partie, lui laissant quelques clefs de son réseau, avec pour mission de faire parvenir des informations sur la situation le plus longtemps possible, et de promouvoir ses idées, qui deviendrait peut-être un jour un mouvement politique capable de balayer les dictateurs ayant pris en otage la Révolution Castiks pour leurs propres profits.. Quand le Lieutenant Ralato était venu l'arrêter à son bureau, Stuffy n'avait eu le temps de ressentir qu'une chose avant la première injection paralysante: “Dénonciation” Il avait été vendu par quelqu'un, un traître de l'intérieur. Un autre du réseau Azala? Peu probable.. Un mutualiste? Difficile à concevoir tant cette organisation était compartimentée.. Dans le couloir, de nombreux pas approchaient. C'était l'heure de l'injection, et Stuffy tenta de donner son maximum de volonté pour reprendre le contrôle de son corps et se battre. Il réussit seulement à tomber sur le sol, aux pieds de ses gardiens hilares: -Alors le Mental, on veut se rebeller? Hoooo c'est bien les gars regardez: il a réussi à faire 60 cm en rampant! Il se senti soulevé puis rejeté sans ménagement sur la couchette dure et froide. -Tu est une vrai charogne sale Mental, et plus que çà: tu es une vermine de Mutualiste. Les porcs comme toi ne méritent qu'une chose. Ses pouvoir en semi-veille ressentait la haine que lui vouaient ses geôliers: Mutualiste, Mental.. Traitre! Tout pour se faire détester. Une étrange chaleur se diffusa alors depuis plusieurs endroits de son corps, suivi d'une odeur.. d'urine! -On le mouille bien les gars! Si on n'a pas le droit de le frapper, on peut au moins l'aider à avoir bien chaud cette nuit Hahahah! Stuffy nota qu'on était donc en soirée.. Puis une douleur lui perça la carotide, l'aiguille tournant un peu lançait des éclairs de spasmes sur tout le visage. -Oups! J'ai dû enfoncer l'aiguille au mauvais endroit. Désolé monsieur le Mental, je suis trop maladroit. Et si j'envoyais le produit hein? La douleur fut pire. Les muscles du visage de Stuffy se contractèrent involontairement en un rictus, un simulacre de plaisir que son bourreau remarqua avec amusement! -Hê les gars, cette tarlouze aime çà! Regardez, je suis sur qu'il bande en plus! On devrait le foutre à poil pour voir.. ha bah non, il pue trop la pisse pour que je le touche.. Charogne va! Je te crèverais un jour.. Il retira la seringue violemment, sans même désinfecter la plaie puis se retourna avec ses deux adjoints vers la porte. Il l'ouvrit, commença à marcher.. Poursuivi son chemin et… Recula vers la porte à l'envers! -Bon Dieu mais qu'est ce qu'il se passe? Il tenta de se retourner mais il ne put rien. Une voix dans sa tête lui fournit une indication. “La prochaine fois que tu veux prendre ton pied contre un Mental, ne te trompe pas: injecte-lui son sérum, pas un fortifiant rapide.” La porte se referma devant lui, loin, très loin, immensément loin…
his was shot durring the making of "you should'a Said hi" Consider this the behind the scenes video
© 2020-2025 Ivy Podcast Discovery LLC
