Dan is joined once again by Dr. David Chao (ProFootballDoc.com) to tackle the most pressing injury questions for Week 6. Later, Dan and Yates preview every single game taking place this week! Sponsors: Underdog Fantasy - Underdog Fantasy is the best and easiest place to play fantasy football for big cash prizes. Go to underdogfantasy.com, the app store, or the Google Play store, sign up with the code FANTASYPROS, and get a free $25 in bonus cash. Manscaped - Manscaped is #1 in men's below the belt grooming. They offer precision engineered tools for your family jewels. Get 20% off and free shipping with the code YATES at Manscaped.com. AirMedCare - If a medical emergency arises, AirMedCare Network provides members with world class emergency air transport services to the nearest hospital with NO out of pocket expenses. Visit airmedcarenetwork.com/fantasypros and use offer code FANTASYPROS to get up to a $50 Visa or Amazon gift card with a new membership. Timestamps: Injury Analysis - 0:00:22 Dalvin Cook - 0:01:29 Christian McCaffrey - 0:02:24 Nick Chubb - 0:04:54 Saquon Barkley - 0:06:31 Ezekiel Elliott - 0:07:49 Tyreek Hill - 0:09:12 Damien Harris - 0:10:32 Terry McLaurin - 0:11:50 Dan & Kyle in the Morning - 0:14:34 Over/Under Challenge - 0:16:13 Justin Herbert - 0:16:33 Nick Chubb - 0:17:44 Kadarius Toney - 0:18:24 Marquise Brown - 0:19:29 TB vs. PHI - 0:21:00 Leonard Fournette - 0:21:00 TB WRs - 0:23:06 O.J. Howard/Cameron Brate - 0:24:59 Jalen Hurts - 0:25:44 Miles Sanders - 0:28:01 DeVonta Smith - 0:28:46 MIA vs. JAC - 0:30:22 Marvin Jones/Laviska Shenault - 0:30:32 Dan Arnold - 0:32:59 Jaylen Waddle - 0:34:27 Mike Gesicki - 0:35:52 GB vs. CHI - 0:36:25 Aaron Rodgers - 0:36:25 A.J. Dillon - 0:37:02 Khalil Herbert - 0:37:46 Allen Robinson/Darnell Mooney - 0:38:34 CIN vs. DET - 0:41:10 Joe Mixon - 0:41:20 CIN WRs - 0:41:59 Jamaal Williams - 0:42:50 Amon-Ra St. Brown - 0:43:47 HOU vs. IND - 0:44:26 Michael Pittman - 0:44:28 Carson Wentz - 0:45:10 Brandin Cooks - 0:46:03 LAR vs. NYG - 0:46:49 Devontae Booker - 0:47:17 Kadarius Toney - 0:47:56 Sony Michel - 0:49:35 KC vs. WAS - 0:50:32 Ricky Seals-Jones - 0:50:58 Mecole Hardman - 0:51:41 MIN vs. CAR - 0:53:49 Adam Thielen - 0:54:34 Chuba Hubbard - 0:55:53 LAC vs. BAL - 0:56:41 Latavius Murray/Ty'Son Williams - 0:57:48 ARI vs. CLE - 0:58:22 Demetric Felton - 0:58:22 Odell Beckham - 0:59:14 David Njoku - 0:59:49 Chase Edmonds/James Conner - 1:00:37 ARI WRs - 1:01:13 LV vs. DEN - 1:02:17 Melvin Gordon/Javonte Williams - 1:02:17 Courtland Sutton - 1:03:03 Henry Ruggs - 1:03:56 DAL vs. NE - 1:04:56 Tony Pollard - 1:05:00 Dalton Schultz - 1:05:38 Rhamondre Stevenson - 1:06:33 Hunter Henry - 1:07:20 SEA vs. PIT - 1:07:53 SEA RBs - 1:08:41 Tyler Lockett - 1:09:37 Gerald Everett - 1:10:20 BUF vs. TEN - 1:11:00 A.J. Brown/Julio Jones - 1:11:00 Ryan Tannehill - 1:11:34 Stefon Diggs - 1:13:43 Emmanuel Sanders - 1:14:28 Dawson Knox - 1:14:47 Zack Moss/Devin Singletary - 1:15:17 Cole Beasley - 1:15:42
This week's podcast, sponsored by NewLeaf Symbiotics, features Mike Brocksmith, a grower from Vincennes, Ind. Brocksmith will be a speaker at the upcoming 2021 National Cover Crop Summit: Fall Edition. He will discuss how his family's operation utilizes cover crops to reduce soil erosion, how they seed their cover crops, his experiences planting green, and more.
Welcome in thanks for making that call! On this episode I cover the Bucs and PhI game who to start and sit. I also cover the following games MIA vs JAX, LAC vs BAL, MIN vs CAR, GB vs CHI, CIN vs DET, HOU vs IND and LAR vs NYG. Be sure to follow me on Twitter @thedynasty411 --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app
Andy and Drew go through the slate game by game and give you their thoughts, analysis for each game and which bets they're making for the NFL slate. Welcome :34 TB at PHI 4:30 MIA vs JAX 10:41 HOU at IND 17:44 GB at CHI 23:09 KC at WFT 30:43 MIN at CAR 41:53 LAC at BAL 49:48 CIN at DET 59:12 LAR at NYG 1:05:40 ARI at CLE 1:09:48 LV at DEN 1:13:31 DAL at NE 1:20:25 SEA at PIT 1:22:50
Ken Carman and Anthony Lima go 7 in Heaven where they project the AFC Playoff picture. Did Lamar Jackson change the conversation about the AFC North? And who has Kansas City dropping? Ken: 1 BUF, 2 KC, 3 CLE, 4 TEN...5 LAC, 6 BAL, 7 NE Lima: 1 BUF, 2 BAL, 3 LAC, 4 IND...5 CLE, 6 KC, 7 LV Here is last week's 7 in Heaven. Listen to The Ken Carman Show with Anthony Lima weekday mornings 6-10am on Sports Radio 92.3 The Fan and the Audacy App! See omnystudio.com/listener for privacy information.
Nick Offerman is best known for his role as Ron Swanson, the mustachioed, libertarian outdoorsman who led the Pawnee, Ind., Parks and Recreation Department on the beloved show “Parks and Recreation.” But there's more to Offerman than Swanson: His new book, “Where the Deer and the Antelope Play,” was inspired in part by his conversation with the agrarian poet-philosopher Wendell Berry, and a hiking trip he took with the writer George Saunders and the musician Jeff Tweedy (both of whom you may remember from past episodes of this show).Offerman is fascinating. He plays, inhabits and ultimately subverts a kind of camp masculinity. Some of it is real. He really does own a woodworking shop. He really did release a whiskey with Lagavulin. But some of it is a container Offerman is using to try to get people to think about different ways to live. Like his famed character, Offerman loves the outdoors and thinks we've lost touch with the role it should play in our lives and the role it has played in our past. That's the subject of his book, and to some degree, of this conversation. But Offerman is also just a wonderful storyteller and possessed of a generous, earthy wisdom. So this one is a delight.Mentioned:The Unsettling of America by Wendell BerryBook Recommendations:Fidelity by Wendell BerryWanderlust by Rebecca SolnitGirls and Sex by Peggy OrensteinBoys and Sex by Peggy OrensteinYou can find transcripts (posted midday) and more episodes of "The Ezra Klein Show" at nytimes.com/ezra-klein-podcast, and you can find Ezra on Twitter @ezraklein. Book recommendations from our guests are listed at https://www.nytimes.com/article/ezra-klein-show-book-recs.Thoughts? Guest suggestions? Email us at email@example.com.“The Ezra Klein Show” is produced by Annie Galvin, Jeff Geld and Rogé Karma; fact-checking by Michelle Harris; original music by Isaac Jones; mixing by Jeff Geld, audience strategy by Shannon Busta. Special thanks to Kristin Lin.Love listening to New York Times podcasts? Help us test a new audio product in beta and give us your thoughts to shape what it becomes. Visit nytimes.com/audio to join the beta.
Dan is joined once again by Dr. David Chao (ProFootballDoc.com) to tackle the most pressing injury questions for Week 5. Later, Dan and Yates preview every single game taking place this week! Sponsors: Bachan's - It's still grilling season and the ideal time to check out Bachan's. Bring your family and friends together with delicious, rich flavor. Go to bachans.com/fantasypros and use the code “FantasyPros” at checkout for 20% off. Magic Spoon - Magic Spoon offers tasty, healthy cereal that cuts down on sugar and carbs. Go to magicspoon.com/fantasypros to grab a variety pack and try it today! And be sure to use our promo code FANTASYPROS at checkout to get $5 off. PrizePicks - Turn your picks into real cash with PrizePicks! Use our Promo Code “GRIDIRON” to receive a 100% instant deposit match up to $100. Timestamps: Injury Analysis - 0:00:21 Russell Wilson - 0:01:09 Christian McCaffrey - 0:03:46 Joe Mixon - 0:06:52 Baker Mayfield - 0:07:48 Dalvin Cook - 0:09:51 A.J. Brown - 0:10:41 Jimmy Garoppolo - 0:12:14 Dan & Kyle in the Morning - 0:14:37 Over/Under Challenge - 0:16:44 Jalen Hurts - 0:17:05 Chuba Hubbard - 0:18:19 Allen Robinson - 0:18:58 TNF Recap - 0:20:30 LAR vs. SEA - 0:20:30 Robert Woods - 0:21:05 Darrell Henderson - 0:22:26 Sony Michel - 0:23:33 Tyler Higbee - 0:23:59 Russell Wilson - 0:25:16 D.K. Metcalf/Tyler Lockett - 0:25:52 Alex Collins - 0:26:55 NYJ vs. ATL - 0:29:59 Kyle Pitts - 0:29:59 Corey Davis - 0:32:24 Jamison Crowder - 0:33:09 Michael Carter - 0:33:41 NE vs. HOU - 0:33:59 Jakobi Meyers - 0:34:12 Hunter Henry - 0:35:00 D'Andre Swift/Jamaal Williams - 0:35:56 Kirk Cousins - 0:37:17 PHI vs. CAR - 0:39:51 Chuba Hubbard - 0:39:51 Sam Darnold - 0:40:26 Robby Anderson - 0:41:04 DeVonta Smith - 0:42:05 Dallas Goedert/Zach Ertz - 0:42:34 NO vs. WAS - 0:43:16 Antonio Gibson - 0:43:16 NO WRs - 0:44:36 TEN vs. JAC - 0:44:56 Ryan Tannehill - 0:45:15 Marvin Jones/Laviska Shenault - 0:46:32 MIA vs. TB - 0:47:29 MIA RBs - 0:47:29 Jaylen Waddle/DeVante Parker - 0:47:57 TB WRs - 0:48:53 Tom Brady - 0:50:12 Leonard Fournette - 0:51:13 GB vs. CIN - 0:53:18 Aaron Rodgers - 0:53:18 Robert Tonyan - 0:54:15 Samaje Perine - 0:54:47 CIN WRs - 0:56:00 Melvin Gordon/Javonte Williams - 0:56:27 Courtland Sutton/Tim Patrick - 0:57:48 Najee Harris - 1:00:00 CHI vs. LV - 1:02:44 Darnell Mooney/Allen Robinson - 1:03:15 Henry Ruggs - 1:04:00 Hunter Renfrow - 1:04:38 CLE vs. LAC - 1:05:57 Odell Beckham - 1:06:45 Nick Chubb - 1:07:40 Mike Williams - 1:08:21 Jared Cook - 1:09:28 NYG vs. DAL - 1:10:06 CeeDee Lamb - 1:10:08 Dalton Schultz - 1:11:04 Kenny Golladay - 1:12:04 Kadarius Toney - 1:12:42 Daniel Jones - 1:13:29 SF vs. ARI - 1:13:58 DeAndre Hopkins - 1:14:01 A.J. Green - 1:14:46 James Conner/Chase Edmonds - 1:15:35 Elijah Mitchell/Trey Sermon - 1:16:47 BUF vs. KC - 1:18:00 Emmanuel Sanders - 1:18:07 Dawson Knox - 1:18:45 Cole Beasley - 1:19:39 Josh Gordon - 1:20:30 IND vs. BAL - 1:20:49 Michael Pittman - 1:20:54 Marquise Brown - 1:21:48 Ty'Son Williams/Latavius Murray - 1:22:40
Neste podcast vamos falar sobre Machine Learning, ou em bom português: Aprendizagem de Máquina. Neste podcast vamos falar sobre Machine Learning, ou em bom português: Aprendizagem de Máquina. Feed do podcast: www.lambda3.com.br/feed/podcast Feed do podcast somente com episódios técnicos: www.lambda3.com.br/feed/podcast-tecnico Feed do podcast somente com episódios não técnicos: www.lambda3.com.br/feed/podcast-nao-tecnico Lambda3 · 268 - Machine Learning (Aprendizagem de máquina) Pauta: O que é Machine Learning (Aprendizagem de Máquina)? Academia x indústria Boom e "hype" na área Onde está presente/inserido? Projetos mais interessantes e exemplos de aplicações em machine learning Trabalhando e estudando Machine Learning Quais as principais diferenças quando comparado com desenvolvimento convencional? Como normalmente se configura o trabalho de um Cientista de Dados / Engenheiro de Machine Learning e outros papéis que lidam com Aprendizagem de Máquina? Descolamento Academia x Indústria na área/assunto. Estamos formando profissionais para atender a essas demandas? Qual a visão com relação aos recentes desenvolvimentos na área, por exemplo novos modelos e redes pré treinadas voltadas para a área de Processamento de Linguagem Natural? (Vide GPT-3, BERT etc.). O que esperar com relação ao mercado e o uso de ML? Quais problemas podem advir do uso indiscriminado de ML? Como enxergam a questão do futuro do trabalho? Ainda haverá espaço para o trabalho do programador/cientista de dados? Como ética e responsabilidade podem se encaixar nesse contexto? Por que aprender Machine Learning? Para quem já é desenvolvedor, pode fazer diferença num futuro próximo? Qual a visão a respeito da LGPD e outras leis de proteção aos dados? Como essas novas práticas vão impactar o trabalho a partir de técnicas em ML? (Ex: uso de dados sensíveis para forecasting). Links Citados: Vertex AI [2103.03206] Perceiver: General Perception with Iterative Attention MUM: A new AI milestone for understanding information Government response to House of Lords Artificial Intelligence Select Committee's Report on AI in the UK: Ready, Willing and A Inteligência Artificial Data Ethics Framework Livro - A Lógica do Consumo Participantes: Ahirton Lopes – @AhirtonLopes Bianca Ximenes – @biancaxis Filipe Dornellas – @fdornelasx Edição: Compasso Coolab Créditos das músicas usadas neste programa: Music by Kevin MacLeod (incompetech.com) licensed under Creative Commons: By Attribution 3.0 - creativecommons.org/licenses/by/3.0
Thanks for making that call! I have Week 5 starters part 2 for you starting with the Saints and Washington, CHI vs LV, CLE vs LAC, SF vs ARI, NYG vs DAL, BUF vs KC and IND vs BAL. Be sure to follow me on Twitter @thedynasty411 Hit me up with any questions you might have I'm happy to help.
Comme le disait le rappeur Jay-Z dans une de ses chansons en 2005 "I am not a business man. I am a BUSINESS, man!"Né à Brooklyn, Jay-Z a grandi dans une cité HLM, élevé par une mère célibataire. Au lycée, il vendait du crack pour s'en sortir mais sa a vie a brusquement changé le jour où sa maman lui a acheté une boombox pour son anniversaire. Il s'est intéressé à la musique et après un premier single en 1995 il est devenu aujourd'hui le premier artiste hip-hop milliardaire. Marié à Beyoncé sa fortune est aujourd'hui estimée à plus de 2 milliards de dollars. Vous allez me dire mais quel rapport avec le sujet. Jay-Z est en fait l'archétype d'un phénomène mondial qui va bouleverser l'économie : la désintégration du travail. Les gens deviennent leurs propres entreprises. Si la SARL était la petite entreprise du XXe siècle, les individus sont les petites entreprises du XXIe siècle. Indépendants, entrepreneurs, créateurs, ils sont tous des exemples d'une forme de souveraineté individuelle. Le travail "traditionnel" tel que nous le connaissons ne fait plus recette et on voit émerger une nouvelle économie où les individus préfèrent investir leur temps plutôt que de le vendre. Bref est-ce que c'est la fin du sacro-saint contrat de travail ? On en parle cette semaine dans Silicon Carne.
Podemos dizer que o problema da seca no nordeste do Brasil é histórico, pois a região, por uma série de fatores geográficos e climáticos é suscetível a vivenciar grandes períodos de estiagem. Porém, não é de hoje que o Estado brasileiro busca por soluções para resolver o problema, seja na transposição de grandes volumes fluviais de rios, na construção de açudes, com medidas paliativas e também com tentativas de aplicação da ciência e da engenharia. É justamente sobre as ações estatais realizadas nas últimas décadas do Império e no início da República que recebemos a historiadora Aline Lima (Museu da Indústria), que nos brindou com um papo sobre o papel dos engenheiros, a história da ciência, a cultura popular e as relações históricas entre os sertanejos e o clima.
Ken Carman and Anthony Lima go 7 in Heaven where they project the AFC Playoff picture. Who decided to put the Indianapolis Colts in their 7 in Heaven and why? Ken: 1 KC, 2 BUF, 3 CLE, 4 TEN...5 LAC, 6 BAL, 7 NE Lima: 1 BUF, 2 CLE, 3 LAC, 4 IND...5 BAL, 6 KC, 7 LV Here is last week's 7 in Heaven. Listen to The Ken Carman Show with Anthony Lima weekday mornings 6-10am on Sports Radio 92.3 The Fan and the Audacy App! See omnystudio.com/listener for privacy information.
Dan and Pat react to Week 4's NFL action and recap each Sunday afternoon game! Sponsors: Kraken - If you're interested in investing in cryptocurrencies but aren't sure where to get started, check out the Kraken app. Visit kraken.com/fantasypros now to learn more or search for "Kraken" in the app store. TickPick - TickPick, the original no-fee ticket site, is teaming up with ZIP, the buy now, pay later service provider, to give away five huge season ticket packages for the 2022 season! You can try your luck today and enter to win by going to TICKPICK.COM/PROS. Timestamps: Trust or Bust - 0:02:12 I Am Confused by Your Opinion, Sir - 0:08:00 WAS vs. ATL - 0:10:29 HOU vs. BUF - 0:16:57 DET vs. CHI - 0:22:26 CAR vs. DAL - 0:26:21 IND vs. MIA - 0:33:10 CLE vs. MIN - 0:39:11 NYG vs. NO - 0:42:03 TEN vs. NYJ - 0:47:22 KC vs. PHI - 0:50:12 ARI vs. LAR - 0:54:45 SEA vs. SF - 0:58:52 BAL vs. DEN - 1:06:44 PIT vs. GB - 1:10:48
In French in this CDA S3#11 (Monday online), " A French architect in ‘America' ", an interview of Jean-Michel Humbert, architect, founder of Plan H office. In English in CDA S3#12 (Wednesday online), "Church conversion in Washington D.C.", by Plan H.En français dans le CDA S3#11 (lundi en ligne), " Un architecte français en ‘Amérique' ", une interview de Jean-Michel Humbert, architecte, fondateur de l'agence Plan H – En anglais dans CDA S3#12 (Mercredi en ligne), "Reconversion d'une église à Washington D.C. ", par Plan H.___Plan H est une agence, française au départ, fondée par Jean-Michel Humbert il y a moins de dix ans. En effet, perplexe face aux difficultés d'accès à la commande que rencontrent les jeunes architectes français, Jean-Michel Humbert, suite à un voyage à New-York décide de tenter le rêve américain. C'est à Washington D.C. qu'il ancre sa nouvelle pratique, et après 4,5 ans d'adaptation, il y réactive son agence Plan H. Indépendant depuis maintenant deux ans, son bagage français peu courant à Washington lui permet de réaliser des projets de reconversion et de réhabilitation très prometteurs, et ce en dépit de la crise Covid. Ses premières expériences françaises autour du patrimoine architectural Lorrain (Jean Prouvé, Maison Godin) renforcent indéniablement son aptitude à traiter des sujets de réhabilitation, et pourquoi pas historiques.Dans ce numéro de Com d'Archi, Jean-Michel nous raconte son parcours atypique d'architecte, jonché de défis et d'obstacles franchis à force de patience et de courage ; de sa Lorraine natale à Washington D.C. en passant par Paris à l'agence Toury-Vallet devenue Vallet-de Martinis (CDAS2 #60#61). Dans son récit, strates après strates, on le voit patiemment faire émerger sa pratique individuelle. Un parcours qui parlera certainement beaucoup aux tous jeunes architectes et qui touchera plus largement tous les publics. Car quel plaisir que d'entendre encore parler, dans le respect, de la différence et de l'enrichissement mutuel de nos cultures américaines et françaises !Portrait teaser Jean-Michel Humbert © Ingénierie son : Julien Rebours____Si le podcast COM D'ARCHI vous plaît n'hésitez pas :. à vous abonner pour ne pas rater les prochains épisodes,. à nous laisser des étoiles et un commentaire, :-),. à nous suivre sur Instagram @comdarchipodcast pourretrouver de belles images, toujours choisies avec soin, demanière à enrichirvotre regard sur le sujet.Bonne semaine à tous ! Voir Acast.com/privacy pour les informations sur la vie privée et l'opt-out.
Dan is joined once again by Dr. David Chao (ProFootballDoc.com) to tackle the most pressing injury questions for Week 4. Later, Dan and Yates preview every single game taking place this week! Sponsors: TickPick - TickPick, the original no-fee ticket site, is teaming up with ZIP, the buy now, pay later service provider, to give away five huge season ticket packages for the 2022 season! You can try your luck today and enter to win by going to TICKPICK.COM/PROS. Pristine Auction - Get the best deals in sports memorabilia including signed helmets and custom jerseys with guaranteed authenticity. Enter registration code "FantasyPros" when you sign up to receive a free $5 credit. AirMedCare - If a medical emergency arises, AirMedCare Network provides members with world class emergency air transport services to the nearest hospital with NO out of pocket expenses. Visit airmedcarenetwork.com/fantasypros and use offer code FANTASYPROS to get up to a $50 Visa or Amazon gift card with a new membership. Timestamps: Injury Analysis - 0:00:18 Dalvin Cook - 0:00:46 Chase Claypool - 0:01:35 Tyler Lockett - 0:03:42 Darrell Henderson - 0:04:45 A.J. Brown/Julio Jones - 0:05:48 Joe Mixon - 0:06:45 Christian McCaffrey - 0:08:05 Dan & Kyle in the Morning - 0:10:23 Over/Under Challenge - 0:11:49 JAC vs. CIN - 0:14:49 Joe Mixon - 0:14:56 CIN WRs - 0:17:19 Laviska Shenault - 0:17:49 James Robinson - 0:19:02 WAS vs. ATL - 0:21:20 Antonio Gibson - 0:21:20 Cordarelle Patterson - 0:22:28 Calvin Ridley - 0:23:23 Mike Davis - 0:23:50 HOU vs. BUF - 0:24:17 Zack Moss - 0:24:30 Emmanuel Sanders/Cole Beasley/Gabriel Davis - 0:25:07 Dawson Knox - 0:26:11 Brandin Cooks - 0:26:52 DET vs. CHI - 0:27:37 Justin Fields - 0:27:37 Allen Robinson/Darnell Mooney - 0:28:22 Jamaal Williams/T.J. Hockenson/D'Andre Swift - 0:29:37 CAR vs. DAL - 0:30:55 Tony Pollard - 0:31:07 Dalton Schultz/Blake Jarwin - 0:31:56 Chuba Hubbard - 0:33:11 Robby Anderson - 0:33:56 Sam Darnold - 0:35:01 IND vs. MIA - 0:37:29 Jonathan Taylor - 0:37:29 Nyheim Hines - 0:38:39 Jaylen Waddle - 0:39:49 Robert Tonyan - 0:40:48 CLE vs. MIN - 0:41:14 Odell Beckham, Jr. - 0:41:30 Tyler Conklin - 0:43:12 NYG vs. NO - 0:45:09 Alvin Kamara/Marquez Callaway - 0:45:15 Kenny Golladay - 0:46:08 TEN vs. NYJ - 0:48:01 Ryan Tannehill - 0:48:04 Corey Davis - 0:49:14 KC vs. PHI - 0:49:51 Mecole Hardman - 0:50:10 Jalen Hurts - 0:50:55 DeVonta Smith - 0:51:57 ARI vs. LAR - 0:52:39 Chase Edmonds/James Conner - 0:52:46 DeAndre Hopkins - 0:53:24 Christian Kirk/Rondale Moore - 0:53:52 Cooper Kupp - 0:54:59 Robert Woods - 0:55:50 Darrell Henderson - 0:56:52 SEA vs. SF - 0:58:05 Tyler Lockett - 0:58:09 D'Wayne Eskridge - 0:58:49 BAL vs. DEN - 1:00:31 Marquise Brown - 1:00:40 Ty'Son Williams - 1:02:08 Courtland Sutton/Tim Patrick - 1:03:53 PIT vs. GB - 1:04:49 Chase Claypool/JuJu Smith-Schuster - 1:05:08 Najee Harris - 1:05:42 TB vs. NE - 1:06:53 Damien Harris - 1:06:56 Ronald Jones/Leonard Fournette - 1:08:28 LV vs. LAC - 1:09:28 Jared Cook - 1:10:03 Derek Carr - 1:10:29 Henry Ruggs - 1:11:15
Deze week werd het Nederlanderschap van de 47-jarige Moussa Lghoul ingetrokken. Volgens de IND is deze man, die in 2015 werd veroordeeld als lid van een terroristische organisatie, nog altijd staatsgevaarlijk en moet hij naar Marokko, waar hij nog wél staatsburger is. Maar ook dat land zit niet op hem te wachten. Binnenlandredacteuren Andreas Kouwenhoven en Romy van der Poel tekenden zijn verhaal op.Gast: Andreas KouwenhovenPresentatie: Floor BoonProductie: Felicia Alberding & Iris VerhulsdonkMontage: Misja van Waterschoot Zie het privacybeleid op https://art19.com/privacy en de privacyverklaring van Californië op https://art19.com/privacy#do-not-sell-my-info.
For the fourth year in a row, Robby Kalland joins Sam for the only essential preview podcast: NBA Win total over/unders. This episode is on the Eastern Conference. We use our good friends over at BetMGM and their win total lines to dive deep into each team, and discuss what we think will happen this year for every one. The teams go in alphabetical order. The numbers we go off of can be found below: ATL 47.5; BOS 45.5; BKN 56.6; CHA 38.5; CHI 42.5; CLE 26.5; DET 24.5; IND 42.5; MIA 48.5; MIL 54.5; NYK 41.5; ORL 22.5; PHI 50.5; TOR 35.5; WAS 33.5 Learn more about your ad choices. Visit megaphone.fm/adchoices
Dan and Pat react to Week 3's NFL action and recap each Sunday afternoon game. Sponsors: Pristine Auction - Get the best deals in sports memorabilia including signed helmets and custom jerseys with guaranteed authenticity. Enter registration code "FantasyPros" when you sign up to receive a free $5 credit. DraftKings - The Official Daily Fantasy Partner of the NFL -- is putting you in the center of the action for Week 4. Download the DraftKings app NOW and use code FANTASYPROS. This week, new customers can get a free shot at MILLIONS of dollars in total prizes. Enter code FANTASYPROS to get a FREE shot at MILLIONS in total prizes with your first deposit! Timestamps: Trust or Bust - 0:02:43 I Am Confused by Your Opinion, Sir - 0:07:11 LAC vs. KC - 0:10:03 ARI vs. JAC - 0:13:14 CHI vs. CLE - 0:21:08 WAS vs. BUF - 0:25:52 IND vs. TEN - 0:30:39 NO vs. NE - 0:34:14 ATL vs. NYG - 0:38:51 CIN vs. PIT - 0:44:25 BAL vs. DET - 0:49:41 NYJ vs. DEN - 0:54:44 MIA vs. LV - 0:57:59 TB vs. LAR - 1:03:41 SEA vs. MIN - 1:08:09
Dan is joined once again by Dr. David Chao (ProFootballDoc.com) to tackle the most pressing injury questions for Week 3. Later, Dan and Yates preview every single game taking place this week! Sponsors: PrizePicks - Turn your picks into real cash with PrizePicks! Use our Promo Code “GRIDIRON” to receive a 100% instant deposit match up to $100. Timestamps: Injury Analysis - 0:01:50 Christian McCaffrey - 0:01:50 Amari Cooper - 0:03:31 Diontae Johnson - 0:04:05 Odell Beckham Jr. - 0:05:19 Carson Wentz - 0:06:56 Dalvin Cook - 0:08:32 Over/Under Challenge - 0:11:18 Daniel Jones - 0:11:49 TNF Recap - 0:14:36 CAR vs. HOU - 0:14:49 Christian McCaffrey/Chuba Hubbard - 0:14:49 Robby Anderson - 0:16:13 D.J. Moore - 0:17:57 Brandin Cooks - 0:19:17 LAC vs. KC - 0:20:27 Justin Herbert - 0:20:34 Mike Williams - 0:21:31 Jared Cook - 0:21:56 Clyde Edwards-Helaire - 0:22:56 ARI vs. JAC - 0:25:39 DeAndre Hopkins - 0:25:44 Rondale Moore - 0:26:38 Christian Kirk - 0:27:43 James Robinson - 0:28:55 Marvin Jones - 0:29:31 CHI vs. CLE - 0:30:20 Justin Fields - 0:30:20 Darnell Mooney - 0:31:22 Kareem Hunt - 0:32:35 Odell Beckham Jr. - 0:33:28 WAS vs. BUF - 0:34:50 Logan Thomas - 0:34:59 Zack Moss/Devin Singletary - 0:35:35 IND vs. TEN - 0:36:26 Michael Pittman/Jonathan Taylor - 0:36:37 Ryan Tannehill - 0:38:05 NO vs. NE - 0:40:57 Jonnu Smith - 0:41:30 ATL vs. NYG - 0:42:13 Saquon Barkley - 0:43:26 Sterling Shepard/Kenny Golladay - 0:44:18 CIN vs. PIT - 0:45:24 Tee Higgins/JaMarr Chase - 0:45:24 Tyler Boyd - 0:46:34 Najee Harris - 0:47:19 PIT WRs - 0:47:51 BAL vs. DET - 0:49:01 Ty'Son Williams - 0:49:01 Marquise Brown - 0:49:44 T.J. Hockenson - 0:50:38 Jamaal Williams - 0:51:08 NYJ vs. DEN - 0:51:38 Corey Davis - 0:51:38 Michael Carter - 0:52:17 Melvin Gordon/Javonte Williams - 0:52:40 Noah Fant - 0:53:27 Teddy Bridgewater - 0:53:58 MIA vs. LV - 0:54:58 Myles Gaskin - 0:54:58 Derek Carr - 0:56:04 LV WRs - 0:56:43 Josh Jacobs/Kenyan Drake - 0:57:16 TB vs. LAR - 0:57:52 Chris Godwin/Mike Evans - 0:57:58 Darrell Henderson/Sony Michel - 0:59:06 Tyler Higbee - 0:59:42 SEA vs. MIN - 1:00:07 Dalvin Cook/Alexander Mattison - 1:00:33 GB vs. SF - 1:01:41 Trey Sermon - 1:02:33 PHI vs. DAL - 1:03:13 DeVonta Smith - 1:03:56 Dallas Goedert - 1:04:26 Tony Pollard - 1:05:24
João Carvalho, Cris Tupan e Ivo Makuxi discutiram sobre a resistência dos povos indígenas contra o Marco Temporal.Este programa é criado e produzido por Revolushow e distribuído pela Half Deaf.Produtor executivo - Gus LanzettaGerente de projeto - Lídia RonconiProdução - Zamiliano, Larissa Coutinho, Diego Miranda, João Carvalho e Jones ManoelEdição de Lucas Gelo e Revisão de ZamilianoOuça nosso podcast na Orelo e nos auxílie financeiramente direto da plataforma e com seu play! Baixe o app ou entre no link https://escute.orelo.audio/revolushowSeja você nosso padrim também em http://padrim.com.br/revolushow e concorra ao sorteio de duas bolsas de estudos pela Classe Esquerda, a partir de R$5,00, e tenha acesso a nossa newsletter a partir de R$10,00; ou através do PicPay em https://www.picpay.me/revolushowLinksA Questão Indígena - https://revolushow.com/91-a-questao-indigena/Cupons de Descontorevolushow - 5% de desconto em toda a loja da Cervejaria Soviet - https://www.lojasoviet.com.br/#REVOLUSHOW - 20% de desconto em todos os livros da editora Boitempo - https://www2.boitempoeditorial.com.br/revolushowREVOLUSHOW20 - 20% de Desconto nos livros da Editora Expressão Popular - https://www.expressaopopular.com.br/loja/revolushow20 - 20% de Desconto nos posteres da Revolustore - https://revolustore.com.br/Revolushow202007 - 10% de desconto nos seguintes títulos da editora Lutas Anticapital: Luiz Carlos Prestes textos resgatados do esquecimento; A cidadania burguesa e os limites da democracia; Elementos de Contraposição à Cidadania Burguesa nas Práticas Pedagógicas do Movimento dos Trabalhadores Rurais Sem Terra (MST); Sob o Fio da Navalha: Relações Estado e sociedade a partir da ação política da Economia Solidária no Brasil; Reforma Nacional Democrática e Contrarreforma no ABC paulista (1956-1964) ; A conspiração contra a escola pública; A Estratégia Democrático Popular um inventário crítico; Do Beco dos Sapos aos canaviais de Catende os ciclos de lutas pelo socialismo autogestionário ; O Fetiche da Tecnologia e a experiência das fábricas recuperadas; Mundo do Trabalho Associado e Embriões de Educação para além do capital; Reatando um fio interrompido a relação universidade-movimentos sociais na América Latina; Empresas recuperadas pelos trabalhadores: ocupações e autogestão na Argentina; Educação Democrática, Trabalho e Organização Produtiva no Movimento dos Trabalhadores Rurais Sem Terra (MST); A Tragédia Educacional Brasileira no Século XX: diálogos com Florestan Fernandes; Trabalho, Sindicalismo e Consciência de Classe.revolushow2019 - 15% de descontos nos livros da Editora BaionetaREVOLUSHOW - 10% de descontos nos livros da editora Ciências RevolucionáriasREVOLUSHOW – 20% de desconto nos livros da NovaCulturaREVOLUSHOW10 – 10% Descontos em todas as camisas da Camisa CríticaREVOLUSHOW10 – 10% Descontos em todas as camisas da Veste EsquerdaTrilha sonora:Enxugando o Gelo by BNegão & Seletores de Freqüência is licensed under a Attribution-Noncommercial-Share Alike 3.0 Brazil License. Disponível em: https://bit.ly/30dbBjvIn The Hall of the Montain King Peer Gynt Suite no. 1, Op. 46 . Disponível em: https://bit.ly/2XsGGhx
La Confederación Nacional de Organizaciones Campesinas, Indígenas y Negras (Fenocin) busca dialogar con el presidente Guillermo Lasso para exponerle su plan de propuestas para la reactivación económica y atención a los pueblos rurales. El titular de la Fenocin, Gary Espinoza, comentó que piden al mandatario que cumpla sus promesas de campaña, como bajar las tasas de interés para los créditos al 1 %, que se reduzcan los índices de pobreza rural, que se acojan sus propuestas para impulsar el acceso a educación y salud intercultural.
Two games into the season, there's not a lot to like about the way the Colts have played so far. IndyStar's Colts beat writer, Joel A. Erickson, and Tucker Bitting of Pendleton, Ind., dive into the issues, trying to sift the problems that might be temporary, like the offensive line, from the problems that look like they're going to give the Colts fits the entire season, like the lack of pass rush off of the edge.
Dan and Pat react to Week 2's NFL action and recap each Sunday afternoon game! Sponsors: PrizePicks - Turn your picks into real cash with PrizePicks! Use our Promo Code “GRIDIRON” to receive a 100% instant deposit match up to $100. Magic Spoon - Magic Spoon offers tasty, healthy cereal that cuts down on sugar and carbs. Go to magicspoon.com/fantasypros to grab a variety pack and try it today! And be sure to use our promo code FANTASYPROS at checkout to get $5 off. Timestamps: Trust or Bust - 0:02:16 I'm Confused by Your Opinion, Sir - 0:04:39 LV vs. PIT - 0:09:59 SF vs. PHI - 0:19:54 HOU vs. CLE - 0:27:01 DEN vs. JAC - 0:33:57 NO vs. CAR - 0:39:50 LAR vs. IND - 0:44:13 BUF vs. MIA - 0:48:03 NE vs. NYJ - 0:51:38 CIN vs. CHI - 0:56:22 ATL vs. TB - 1:01:48 MIN vs. ARI - 1:06:48 TEN vs. SEA - 1:11:06 DAL vs. LAC - 1:15:29
Dan is joined once again by Dr. David Chao (ProFootballDoc.com) to tackle our most pressing injury questions for Week 2. Later, Dan and Yates preview every single game taking place this week! Sponsors: Pristine Auction - Get the best deals in sports memorabilia including signed helmets and custom jerseys with guaranteed authenticity. Enter registration code "FantasyPros" when you sign up to receive a free $5 credit. PrizePicks - Turn your picks into real cash with PrizePicks! Use our Promo Code “GRIDIRON” to receive a 100% instant deposit match up to $100. Timestamps: Injury Analysis - 0:01:03 Saquon Barkley - 0:01:03 Odell Beckham Jr. - 0:02:36 Joe Burrow - 0:04:55 Amari Cooper/Dak Prescott - 0:06:50 Over/Under Challenge - 0:11:39 NYG vs. WAS - 0:14:50 Terry McLaurin - 0:14:50 Antonio Gibson - 0:16:26 Daniel Jones - 0:18:20 Saquon Barkley - 0:19:09 Sterling Shepard - 0:20:58 Kenny Golladay - 0:22:33 LV vs. PIT - 0:25:41 Najee Harris - 0:25:41 PIT WRs - 0:26:40 Ben Roethlisberger - 0:28:20 Josh Jacobs - 0:28:57 SF vs. PHI - 0:30:45 Elijah Mitchell/Trey Sermon - 0:30:45 Brandon Aiyuk/Deebo Samuel - 0:32:57 DeVonta Smith - 0:34:24 Dallas Goedert - 0:35:11 Jalen Reagor - 0:35:43 HOU vs. CLE - 0:36:14 Nick Chubb - 0:36:51 Kareem Hunt - 0:37:42 Jarvis Landry/Anthony Schwartz - 0:39:07 DEN vs. JAC - 0:41:27 Melvin Gordon/Javonte Williams - 0:41:27 Courtland Sutton - 0:42:23 JAC WRs - 0:43:51 NO vs. CAR - 0:44:50 Marquez Callaway - 0:44:50 Jameis Winston - 0:45:42 D.J. Moore/Robby Anderson - 0:46:24 LAR vs. IND - 0:48:16 Robert Woods/Cooper Kupp - 0:48:22 Jonathan Taylor - 0:49:26 BUF vs. MIA - 0:51:58 Devin Singletary - 0:51:58 MIA WRs - 0:53:22 NE vs. NYJ - 0:55:39 Jonnu Smith - 0:56:04 Jakobi Meyers/Nelson Agholor - 0:56:42 NYJ WRs - 0:57:25 CIN vs. CHI - 0:58:17 CIN WRs - 0:58:17 Joe Burrow - 0:59:51 Allen Robinson - 1:00:36 Darnell Mooney - 1:01:04 Cole Kmet - 1:01:50 ATl vs. TB - 1:02:11 TB WRs - 1:03:04 Ronald Jones/Leonard Fournette - 1:03:33 MIN vs. ARI - 1:04:34 Chase Edmonds/James Conner - 1:05:15 Christian Kirk/Rondale Moore/AJ Green - 1:05:44 TEN vs. SEA - 1:06:24 Julio Jones - 1:06:34 Ryan Tannehill - 1:07:36 Russell Wilson - 1:08:08 Gerald Everett - 1:08:44 DAL vs. LAC - 1:09:37 Blake Jarwin/Dalton Schultz - 1:10:33 Austin Ekeler - 1:11:08 Jared Cook - 1:11:52 KC vs. BAL - 1:12:26 Clyde Edwards-Helaire - 1:12:37 Ty'Son Williams - 1:13:38 DET vs. GB - 1:15:32 Jamaal Williams - 1:15:41 Robert Tonyan - 1:16:46
NFL Week 2 is here and we are back to bring you everything you need to make the most of it. Week 1 recap, weekly breakdown, all your favorite segments along with 2 new ones! Come join the action!Show NotesIntro 0:00Week 1 Recap 2:00Heroes/Zero's 5:00NYG vs WAS 12:30SF vs PHI 21:00DEN vs JAX 27:20BUF vs MIA 30:30HOU vs CLE 34:00CIN vs CHI 40:00NO vs CAR 43:00LAR vs IND 49:25LVR vs PIT 54:00NE vs NYJ 57:30MIN vs ARZ 1:01:00ATL vs TB 1:03:00DAL vs LAC 1:05:00TEN vs SEA 1:08:00KC vs BAL 1:11:30DET vs GB 1:16:40Would You Rather 1:20:00Long Shots 1:23:45Favorite Bets of the Week 1:25:15Parlay of the Day 1:28:00Click here to receive The Bookie free daily newsletter
Jeffrey Goldberg is the president and CEO of Immunitas. Jeff is an experienced biotech program and brand leader with over 20 years of industry experience. He has driven programs from discovery and pre-clinical through IND, clinical trials, NDA, and commercialization in multiple therapeutic areas, including oncology, neurology, renal, and other rare and orphan diseases. Prior to joining Immunitas, Jeff was at Akcea Therapeutics, where he was chief operating officer from the time of its formation in January 2015. Previously, Jeff was vice president of business operations, leading both program management and business development at Proteostasis Therapeutics, Inc., a biotech company focusing on neurology and rare diseases. He also spent more than 11 years in positions of increasing responsibility with Genzyme and Sanofi, providing brand management for two marketed products within Sanofi Oncology. Prior to joining Sanofi Oncology, Jeff served as Global Program Lead for Genzyme's stem cell mobilization agent Mozobil, leading the global launch team and overseeing the program management and marketing functions for the product. He began his career at Genzyme as Director, Program Management overseeing the development and launch of Renvela in patients undergoing dialysis. Jeff has both an MBA and a Master's degree in Chemical Engineering from the Massachusetts Institute of Technology, and a B.S. in Chemical Engineering from Cornell University.
Dan and the latest addition to our team, Pat Fitzmaurice, react to the season's first week of action and recap each Sunday afternoon game! Sponsors: FanDuel - Get a 20% bonus on your first deposit — up to $500 — when you sign up at fanduel.com/fantasypros or when you download the FanDuel fantasy app and use the code FANTASYPROS. Pristine Auction - Get the best deals in sports memorabilia including signed helmets and custom jerseys with guaranteed authenticity. Enter registration code "FantasyPros" when you sign up to receive a free $5 credit. Timestamps: Trust or Bust - 0:02:49 What's Your Problem, Man? - 0:06:35 Matchups - 0:08:37 PHI vs. ATL - 0:08:43 PIT vs. BUF - 0:15:17 MIN vs. CIN - 0:22:18 SF vs. DET - 0:28:47 ARI vs. TEN - 0:37:03 SEA vs. IND - 0:41:56 LAC vs. WAS - 0:44:50 NYJ vs. CAR - 0:48:42 JAC vs. HOU - 0:53:33 CLE vs. KC - 0:56:19 MIA vs. NE - 1:00:15 GB vs. NO - 1:05:18 DEN vs. NYG - 1:09:33
durée : 00:29:10 - Une histoire particulière, un récit documentaire en deux parties - par : Elise Gruau - Au début du XXe siècle, l'invention du pneu en caoutchouc révolutionne les modes de vie. Dans l'État Indépendant du Congo, propriété privée de Leopold II roi des Belges, les colons terrorisent la population pour intensifier la production de caoutchouc - réalisation : François Teste
Dan is joined by Dr. David Chao (ProFootballDoc.com) to tackle our most pressing injury questions for Week 1. Then, Dan and Yates preview every single game taking place this week! Sponsors: FanDuel - Get a 20% bonus on your first deposit — up to $500 — when you sign up at fanduel.com/fantasypros or when you download the FanDuel fantasy app and use the code FANTASYPROS. Pristine Auction - Get the best deals in sports memorabilia including signed helmets and custom jerseys with guaranteed authenticity. Enter registration code "FantasyPros" when you sign up to receive a free $5 credit. Timestamps: Injury Analysis - 0:00:39 Saquon Barkley - 0:01:17 Austin Ekeler - 0:03:14 Courtland Sutton - 0:07:22 Trey Lance - 0:09:00 Carson Wentz - 0:12:11 Accuracy Challenge - 0:18:35 DAL vs. TB - 0:21:27 Mike Evans - 0:22:33 Antonio Brown - 0:23:26 Ronald Jones/Leonard Fournette - 0:24:49 Amari Cooper - 0:27:22 Dak Prescott - 0:28:11 Ezekiel Elliott - 0:28:41 Dalton Schultz/Blake Jarwin - 0:30:39 PHI vs. ATL - 0:34:02 Miles Sanders - 0:34:11 Dallas Goedert - 0:35:09 DeVonta Smith - 0:36:06 Russell Gage - 0:37:56 PIT vs. BUF - 0:38:40 Najee Harris - 0:38:40 PIT WRs - 0:39:29 Gabriel Davis - 0:41:35 MIN vs. CIN - 0:42:08 CIN WRs - 0:42:17 Joe Burrow - 0:43:18 Adam Thielen - 0:44:14 SF vs. DET - 0:45:17 D'Andre Swift - 0:45:25 Raheem Mostert/Trey Sermon - 0:46:34 Brandon Aiyuk/Deebo Samuel - 0:47:31 ARI vs. TEN - 0:51:15 Chase Edmonds/James Conner - 0:51:52 SEA vs. IND - 0:53:09 Michael Pittman - 0:53:22 Chris Carson - 0:54:24 LAC vs. WAS - 0:55:29 Justin Herbert - 0:56:27 Austin Ekeler - 0:57:21 NYJ vs. CAR - 0:59:01 D.J. Moore/Robby Anderson - 0:59:08 Terrace Marshall - 0:59:41 JAC vs. HOU - 1:01:28 James Robinson - 1:01:36 JAC WRs - 1:02:03 CLE vs. KC - 1:03:50 Mecole Hardman - 1:04:02 Jarvis Landry - 1:05:21 Austin Hooper - 1:06:22 MIA vs. NE - 1:07:07 Damien Harris - 1:07:09 Jakobi Meyers - 1:07:42 Jaylen Waddle - 1:09:01 GB vs. NO - 1:09:56 Marquez Callaway - 1:09:59 DEN vs. NYG - 1:12:00 Saquon Barkley - 1:12:00 Jerry Jeudy/Courtland Sutton - 1:13:26 Javonte Williams/Melvin Gordon - 1:14:26 Noah Fant - 1:15:13 CHI vs. LAR - 1:15:54 Matthew Stafford - 1:15:59 Tyler Higbee - 1:16:41 David Montgomery - 1:17:31 Darnell Mooney - 1:18:38 BAL vs. LV - 1:19:15 Josh Jacobs - 1:19:23 Ty'Son Williams/Latavius Murray - 1:20:52
This episode continues to explore the findings of CUNA's "Women in Credit Union Leadership" issue brief through discussions with three female CEOs in the credit union movement:Karen Madry, CEO of $80 million asset Afena Federal Credit Union in Marion, Ind.Stephanie Teubner, CEO of 1.5 billion asset Blue Federal Credit Union in Cheyenne, Wyo.Tracie Kenyon, CEO of Montana's Credit Unions in Helena.Madry, Teubner, and Kenyon share their thoughts on how the research findings reflect their experiences as female credit union leaders. As the CEO of a small credit union, Madry has a firsthand perspective on why the environment at a small credit union provides leadership opportunities for women. Teubner had experience in the banking industry before joining the credit union movement, allowing her to speak to the differences in leadership opportunities between the two. League CEO Kenyon has a big-picture view of female leadership in credit unions—and on credit union boards—in her state. Listen to a previous episode on the "Women in Credit Union Leadership" issue brief featuring Mike Schenk, chief economist and deputy chief advocacy officer for CUNA, and Samira Salem, vice president of diversity, equity, and inclusion for CUNA.
In this episode of the No-Till Farmer Influencers & Innovators podcast, brought to you by Martin Industries, Frank Lessiter talks with Betsy Bower, an agronomist for Ceres Solutions in Lafayette, Ind., about the task force and some of the hottest areas in no-till farming – from carbon sequestration to biologicals and more.
The NFL is finally back and we are here to bring you everything you need to get the most out of week 1. Game breakdowns, props, teasers, longshots, our favorite bets, and all the fun you have come to expect. Come join the action and let's get ready for some football!Show NotesIntro - 0:00DAL vs TB - 3:30PIT vs BUF - 9:45SF vs DET - 14:15SEA vs IND - 17:45PHI vs ATL - 21:45LAC vs WAS - 26:30AZ vs TEN - 30:00NYJ vs CAR - 34:30MIN vs CIN - 39:45JAX vs HOU - 43:45DEN vs NYG - 46:00GB vs NO - 50:15MIA vs NO - 53:00CLE vs KC - 58:00CHI vs LAR - 1:01:30BAL vs LVR - 1:06:30Favorite Bets of the Week - 1:13:45Long Shots - 1:15:45Parlay of the Day - 1:18Click here to receive The Bookie free daily newsletter
WEST LAFAYETTE, Ind. - The Always Aggressive Podcast welcomed special guest Peyton Stovall to the show Thursday, ready to talk about the Boilermakers' EMPOWER program, all things Name, Image & Likeness, and his path to joining the Purdue family. Stovall serves as Purdue's Assistant Athletics Director for Student-Athlete Development and is a Lafayette native, growing up in the area and attending Lafayette Jefferson High School.A member of the varsity basketball team in his undergraduate studies at Ball State University, Stovall jumps into the conversation regarding the athletics department noon hoops game, and talk steers to the concept of lunch-hour wrestling. Stovall also served as the athletics director at Lafayette Jeff and Evansville North High School before coming to join the Boilermakers.0:00 - Welcome Peyton Stovall4:15 - EMPOWER9:40 - NIL & College Changes20:20 - Craziest NIL Deal?26:10 - Intra-department Sports Activities33:40 - Purdue Football is Back (and so are recruits!)38:45 - and a new Twitter Poll…
En este episodio, escucharemos a 3 jóvenes mujeres Indígenas de Guatemala, quienes nos compartirán su punto de vista sobre el tema de la descolonización, así como sus experiencias en procesos comunitarios y de liderazgo en sus comunidades y sus diferentes luchas para hacer valer sus derechos. Este programa es resultado del proyecto: “Capacitando mujeres Indígenas para la defensa de sus derechos humanos”, una serie de talleres sobre comunicación y derechos humanos realizados entre marzo y junio de 2021 por Cultural Survival y el Alumni Engagement Innovation Fund. Los temas de las capacitaciones incluyeron sanación, información y documentación de los derechos humanos individuales y colectivos. Puede escuchar, descargar y compartir todos nuestros programas de forma gratuita Musicalización: Bajo responsabilidad de la producción Producción: Radio Nakoj Voces: - Sucely Puluc, Maya K'iche', Guatemala - Manuela Damiana Tzaj, Maya K'iche', Guatemala - Gilda Maricela Tucubal Maya Kaqchikel, Guatemala Imagen: Cultural Survival Esto es una producción de Radio de Derechos Indígenas. Nuestros programas son gratuitos para escuchar, descargar y difundir.
En este episodio, escucharemos a 2 jóvenes mujeres Indígenas de Guatemala y México, quienes nos compartirán su punto de vista sobre el tema de la descolonización, así como sus experiencias en procesos comunitarios y de liderazgo en sus comunidades y sus diferentes luchas para hacer valer sus derechos. Este programa es resultado del proyecto: “Capacitando mujeres Indígenas para la defensa de sus derechos humanos”, una serie de talleres sobre comunicación y derechos humanos realizados entre marzo y junio de 2021 por Cultural Survival y el Alumni Engagement Innovation Fund. Los temas de las capacitaciones incluyeron sanación, información y documentación de los derechos humanos individuales y colectivos. Puede escuchar, descargar y compartir todos nuestros programas de forma gratuita Musicalización: Trío Brasileiro/Dudu Maia, Douglas Lora, Alexandre Lora Producción: Rosenda Maldonado Voces: - Rosenda Maldonado - María de los Ángeles Ramos, Purépech, Mexico - Calendaria Xí Ché, Maya Q'eqchi', Guatemala Imagen: Cultural Survival Esto es una producción de Radio de Derechos Indígenas. Nuestros programas son gratuitos para escuchar, descargar y difundir.
En este episodio, escucharemos a 3 jóvenes mujeres Indígenas de Guatemala y México, quienes nos compartirán su punto de vista sobre el tema de la descolonización, así como sus experiencias en procesos comunitarios y de liderazgo en sus comunidades y sus diferentes luchas para hacer valer sus derechos. Este programa es resultado del proyecto: “Capacitando mujeres Indígenas para la defensa de sus derechos humanos”, una serie de talleres sobre comunicación y derechos humanos realizados entre marzo y junio de 2021 por Cultural Survival y el Alumni Engagement Innovation Fund. Los temas de las capacitaciones incluyeron sanación, información y documentación de los derechos humanos individuales y colectivos. Puede escuchar, descargar y compartir todos nuestros programas de forma gratuita Musicalización: La primera de mi tierra. Autoría, composición e interpretación: Luis Ramírez (El Cha) Producción: Radio San Juan Voces: - Julian Bal, Maya Kaqchikel, Guatemala - Catarina Josefina Ajtzalam Maya K'iche', Guatemala - Mactzil Camey, Maya Kaqchikel, Guatemala - Bety Aracely Piche, Zapoteca, Mexico Imagen: Cultural Survival Esto es una producción de Radio de Derechos Indígenas. Nuestros programas son gratuitos para escuchar, descargar y difundir.
En este episodio, escucharemos a 2 jóvenes mujeres Indígenas de México, quienes nos compartirán su punto de vista sobre el tema de la descolonización, así como sus experiencias en procesos comunitarios y de liderazgo en sus comunidades y sus diferentes luchas para hacer valer sus derechos. Este programa es resultado del proyecto: “Capacitando mujeres Indígenas para la defensa de sus derechos humanos”, una serie de talleres sobre comunicación y derechos humanos realizados entre marzo y junio de 2021 por Cultural Survival y el Alumni Engagement Innovation Fund. Los temas de las capacitaciones incluyeron sanación, información y documentación de los derechos humanos individuales y colectivos. Puede escuchar, descargar y compartir todos nuestros programas de forma gratuita Musicalización: Ajito, Byt Band. 2012. Producción: Sócrates Vásquez, Ayuujk, México Voces: - Rode Soralla Procopio López - Angélica Ayala, Nahua, México - Graciela López, Amuzga Imagen: Cultural Survival Esto es una producción de Radio de Derechos Indígenas. Nuestros programas son gratuitos para escuchar, descargar y difundir.
En este episodio, escucharemos a 3 jóvenes mujeres Indígenas de Guatemala, Honduras y México, quienes nos compartirán su punto de vista sobre el tema de la descolonización, así como sus experiencias en procesos comunitarios y de liderazgo en sus comunidades y sus diferentes luchas para hacer valer sus derechos. Este programa es resultado del proyecto: “Capacitando mujeres Indígenas para la defensa de sus derechos humanos”, una serie de talleres sobre comunicación y derechos humanos realizados entre marzo y junio de 2021 por Cultural Survival y el Alumni Engagement Innovation Fund. Los temas de las capacitaciones incluyeron sanación, información y documentación de los derechos humanos individuales y colectivos. Puede escuchar, descargar y compartir todos nuestros programas de forma gratuita Musicalización: Inti illimani - 1975 - canto de los pueblos andinos- amores hallarás; Inti illimani - canto de pueblos andinos pueblos - Solo de Quena Producción: Radio Jenpöj Voces: - Estela Vásquez Martinez - Angie Milady López, Lenca Honduras - Rosemary Dioincio Maya K'iche', Guatemala - Silvia Jacinto, Mixteca, México Imagen: Cultural Survival Esto es una producción de Radio de Derechos Indígenas. Nuestros programas son gratuitos para escuchar, descargar y difundir.
En este episodio, escucharemos a 2 jóvenes mujeres Indígenas de Guatemala y México, quienes nos compartirán su punto de vista sobre el tema de la descolonización, así como sus experiencias en procesos comunitarios y de liderazgo en sus comunidades y sus diferentes luchas para hacer valer sus derechos. Este programa es resultado del proyecto: “Capacitando mujeres Indígenas para la defensa de sus derechos humanos”, una serie de talleres sobre comunicación y derechos humanos realizados entre marzo y junio de 2021 por Cultural Survival y el Alumni Engagement Innovation Fund. Los temas de las capacitaciones incluyeron sanación, información y documentación de los derechos humanos individuales y colectivos. Puede escuchar, descargar y compartir todos nuestros programas de forma gratuita Musicalización: - Música del grupo Sotz' il. Usado con permiso - Tema Wuarmigu de Yarina. Usado con permiso. Guión y Producción: Rosy Gonzáles Sul Voces: - Brenda Xitumul, Maya Achí, Guatemala - Nayelli López, Triqui, México - Rosario Sul González Imagen: Cultural Survival Esto es una producción de Radio de Derechos Indígenas. Nuestros programas son gratuitos para escuchar, descargar y difundir.
Após o recuo da Federação das Indústrias do Estado de São Paulo, entidades do agronegócio brasileiro divulgaram nesta segunda-feira, 30, um manifesto no qual defendem o estado democrático de direito garantidor da “liberdade empreendedora” – o inverso de “qualquer politização ou partidarização nociva” que agrava os problemas do País. O texto é assinado por agremiações do setor agroexportador nacional. A exemplo do documento produzido na Fiesp, o manifesto das entidades do agronegócio não cita o presidente Jair Bolsonaro. Porém, opta por uma mensagem mais incisiva, ao descrever a atual sociedade brasileira como “permanentemente tensionada em crises intermináveis ou em risco de retrocessos e rupturas institucionais”. O documento das entidades do agronegócio foi divulgado após a Fiesp decidir adiar a publicação de um manifesto que pediria a pacificação entre os três Poderes. A decisão surpreendeu signatários do documento e foi considerada unilateral. Skaf tomou a decisão depois de conversar por telefone com o presidente da Câmara, Arthur Lira (Progressistas-AL), aliado de Bolsonaro. #PerguntePraEliane Os ouvintes podem mandar perguntas para Eliane Cantanhêde pelas redes sociais da Eldorado e pelo WhatsApp no quadro #PerguntepraEliane. Para participar, basta encaminhar suas perguntas com essa hashtag para o perfil da Rádio Eldorado no Facebook, cujo endereço é facebook.com/radioeldorado. O perfil do Twitter é @eldoradoradio e do Instagram, @radioeldorado. O telefone para participar via WhatsApp é (11) 99481-1777. See omnystudio.com/listener for privacy information.
UnFollowVic S:2 Ep:17 Aired 08/30/2021Click The Link Below & Show Us Some Lovehttps://linktr.ee/UnFollowVicIntroNo Man Left BehindFunny Children Book TitlesTo Our Service MembersThis Show Was Dedicated to the Men and Women Who Tragically Lost Their Lives Last Thursday at the Airport in Kabul, Afghan.US Navy Corpsman, Maxton Soviak, of Berlin Heights, OhioUS Army Staff Sgt. Ryan Knauss, of Corryton, Tenn.US Marine Corps Staff Sgt. Darin Hoover, of Salt Lake CityUS Marine Corps Sgt. Nicole Gee, Sacramento, Calif.US Marine Corps Sgt. Johanny Rosario Pichardo, of Lawrence, Mass.US Marine Corps Cpl. Hunter Lopez, of Indio, Calif.US Marine Corps Cpl. Humberto Sanchez, of Logansport, Ind.US Marine Corps Cpl. Daegan Page, of Omaha, Neb.US Marine Corps Lance Cpl. David Espinoza, of Rio Bravo, TexasUS Marine Corps Lance Cpl. Rylee McCollum, of Jackson, Wyo.US Marine Corps Lance Cpl. Dylan Merola, of Rancho Cucamonga, Calif.US Marine Corps Lance Cpl. Kareem Nikoui, of Norco, Calif.US Marine Corps Lance Cpl. Jared Schmitz, of St. Charles, Missouri.And to all Men and Women who paid the ultimate sacrifice while protecting the greatest country of all, The United States of America. YouTube:https://youtu.be/_T2vFQc_pcYThank You to All the Listeners Support the show (https://linktr.ee/UnFollowVic)
Febraban e Fiesp reagem ao clima de tensão institucional, mas Banco do Brasil e Caixa Econômica Federal ameaçam retaliar. O manifesto da Federação das Indústrias do Estado de São Paulo, que pede pacificação entre os três Poderes, teve origem na Federação Brasileira de Bancos (Febraban) e já havia reunido até este domingo, 29, mais de 200 assinaturas. Com o cuidado de não assumir um caráter antigoverno, o documento tem por objetivo demonstrar claramente o incômodo nos setores produtivo e financeiro com a crise institucional fomentada pelo presidente Jair Bolsonaro. Uma das razões para o Banco do Brasil e a Caixa Econômica Federal terem comunicado ao governo que pretendem deixar a Febraban teria sido o fato de a entidade das instituições financeiras ser a origem do documento. O polêmico código eleitoral deve ser votado nesta semana na Câmara dos Deputados, com quarentena contra Sérgio Moro. Além do juiz, a proposta incluiu na última hora um dispositivo que também pode barrar eventual candidatura de militares com ambições eleitorais em 2022. O texto prevê a exigência de uma quarentena de cinco anos para que militares, policiais, juízes e promotores possam concorrer às eleições. Apesar do pedido de pressa que o presidente Jair Bolsonaro teria feito, até agora não há previsão de votação de André Mendonça no Senado. E mais: Na CPI da covid no Senado, grande expectativa com depoimento do empresário Marcos Tolentino. Ele é apontado como sócio oculto da empresa FIB Bank, que teria fornecido à Precisa Medicamentos uma garantia irregular no negócio de compra da vacina indiana Covaxin pelo Ministério da Saúde. #PerguntePraEliane Os ouvintes podem mandar perguntas para Eliane Cantanhêde pelas redes sociais da Eldorado e pelo WhatsApp no quadro #PerguntepraEliane. Para participar, basta encaminhar suas perguntas com essa hashtag para o perfil da Rádio Eldorado no Facebook, cujo endereço é facebook.com/radioeldorado. O perfil do Twitter é @eldoradoradio e do Instagram, @radioeldorado. O telefone para participar via WhatsApp é (11) 99481-1777. See omnystudio.com/listener for privacy information.
పెద్దలు ఎప్పుడో చెప్పారు , ఇల్లు అలాగ్గానే (Lord's test) పండగ కాదు అని Talking points: The over the top reactions to Lord's test. Problems against moving ball for the IND batting line-up Pujara back to form ? Joe Root - The greatest English batsman ? Ishant and Siraj looking tired and battered. How good is this ENG side inspite of the innings victory ? Can IND still turn it around ? Team combinations for the next match. Have you subscribed for our weekly newsletter yet? https://cricketnagaram.substack.com Support us: https://www.buymeacoffee.com/cricketnagaram Follow us on Twitter, Instagram.
Door nieuw beleid van de IND hadden minderjarige vluchtelingen geen recht meer op hereniging met hun vader of moeder als ze door een ander familielid opgevangen kunnen worden, ontdekten Steven Derix en Sheila Kamerman. Verantwoordelijk demissionair staatssecretaris Broekers-Knol drong - ondanks waarschuwingen van de IND - aan op dit beleid. Na kritiek werd het beleid teruggedraaid. Hoe kwam het zover? Gast: Sheila KamermanPresentatie: Geertje TuenterProductie: Iris Verhulsdonk, Julia Vié en Esmee DirksMontage: JP GeersingZie het privacybeleid op https://art19.com/privacy en de privacyverklaring van Californië op https://art19.com/privacy#do-not-sell-my-info.
The Last Wicket gang (sans Himanish) reflect on the dramatic finish to the Lord's game, and revisit other memorable instances in recent times where emotions got the better of calmer heads on a cricket field. Links England collapse to a shock defeat - by Freehit - Freehit's Blog (substack.com) Free hits for no-balls would have stopped Jasprit Bumrah's attack on James Anderson (telegraph.co.uk) Virat Kohli Fight With Mitchell Johnson | Virat Kohli Vs Mitchell Johnson 2014 - 2015 Test Series 'Get ready for a broken fucken arm': how Michael Clarke got ruthless Full coverage of the Anderson-Jadeja altercation Cricket: England choke on their jelly beans as Zaheer savours sweet revenge Eng vs Ind 2021 - James Anderson vs India - A history of wickets and verbals (espncricinfo.com) Please answer our survey to tell us how we're doing! The Last Wicket podcast Survey --- Send in a voice message: https://anchor.fm/lastwicket/message Support this podcast: https://anchor.fm/lastwicket/support
Harry traveled to the San Francisco Bay Area this summer, and while there he interviewed the co-founders of three local data-driven diagnostics and drug discovery startups, all of whom participated in the same graduate program: the Biomedical Informatics Program at Stanford's School of Medicine. Joining Harry were Aria Pharmaceuticals co-founder and CEO Andrew Radin, BigHat Biosciences co-founder and chief scientific officer Peyton Greenside, and Inflammatix co-founder and CEO Tim Sweeney. The conversation covered how each company's work to advance healthcare and therapeutics rests on data and computation, and how the ideas, skills, connections each entrepreneur picked up at Stanford have played into their startups and their careers.Radin's company, formerly known as twoXar, models pathogenesis computationally to identify potential drug molecules, shaving years off the drug development process. Radin developed Aria's core technology, a collection of proprietary algorithms for discovering novel small molecule therapies. The algorithms incorporate system biology data, disease-specific data, chemistry libraries, and more than 60 separate AI methods to sift through molecules with known chemistry to find those with novel mechanisms of action and favorable safety profiles absorption properties. Whereas traditional drug discovery methods have a 1-2% success rate after 4 years, Aria claims its approach has a 30% success rate after just 6 months. It has a pipeline of at 18 drug candidates in areas including kidney, lung, and liver diseases, lupus, cancers of the liver and lung, glioblastoma, and glaucoma. Radin holds MS and BS degrees in computer science from Rochester Institute of Technology, studied computational biology and medicine through the Stanford Center for Professional Development, and was formerly an advisor to several venture capital firms and startup accelerators. Greenside started BigHat to combine wet-lab science and machine learning with the goal of speeding up the design of antibody therapies. BigHat's lab consists of numerous “workcells,” each of which cycles through multiple tests of a given set of antibodies synthesized from in silico designs. Assays characterize each antibody variant for traits such as yield, stability, solubility, specificity, affinity, and function. Machine learning algorithms determine how mutations affected each of these properties and feed this learning back into a new set of designs for the next round. The company says this approach allows it to identify therapeutic-grade antibodies faster than traditional bulk screening techniques (in days rather than weeks or months). Greenside is a computational biologist with a PhD from Stanford, an MPhil from Cambridge University, and a BA from Harvard. Silicon Valley Business Journal named her to its 2021 list of “Women of Influence in Silicon Valley.”Sweeney co-founded Inflammatix to develop a new class of diagnostic tests that—rather than searching for a specific bug—“read” the host response of a patient's immune system for clues about the cause and severity of an infection. The problem, as Sweeney originally saw it, is that traditional tests can only detect infections once a pathogen has spread to the bloodstream, meaning that doctors often guess incorrectly about whether a patient needs an antibiotic, or which one they need. Inflammatix is built around the idea that the human immune system has evolved targeted responses to different kinds of infections and other diseases. These responses are complex and vary according to age and setting, but by analyzing mRNA samples from multiple, diverse cohorts, the company believes it can identify a “reproducible signal in the ‘noise' of multiple datasets.” Inflammatix is developing a cartridge-based system called Myrna for use in emergency rooms, urgent care clinics, and outpatient clinics that can screen for acute bacterial infections, viral infections, and sepsis in 30 minutes. Sweeney is a physician and data scientist who earned an MD/PhD from Duke and then trained as a general surgery resident at Stanford.Please rate and review MoneyBall Medicine on Apple Podcasts! Here's how to do that from an iPhone, iPad, or iPod touch:1. Open the Podcasts app on your iPhone, iPad, or Mac. 2. Navigate to the page of the MoneyBall Medicine podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.3.Scroll down to find the subhead titled "Ratings & Reviews."4.Under one of the highlighted reviews, select "Write a Review."5.Next, select a star rating at the top — you have the option of choosing between one and five stars. 6.Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.7.Once you've finished, select "Send" or "Save" in the top-right corner. 8.If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 9.After selecting a nickname, tap OK. Your review may not be immediately visible.Full TranscriptHarry Glorikian: I'm Harry Glorikian, and this is MoneyBall Medicine, the interview podcast where we meet researchers, entrepreneurs, and physicians who are using the power of data to improve patient health and make healthcare delivery more efficient. You can think of each episode as a new chapter in the never-ending audio version of my 2017 book, “MoneyBall Medicine: Thriving in the New Data-Driven Healthcare Market.” If you like the show, please do us a favor and leave a rating and review at Apple Podcasts.Harry Glorikian:Home base for MoneyBall Medicine is the Boston area. It's one of the world capitals for biomedical innovation and the digital revolution in healthcare. So I don't have to venture far to find great guests.But obviously Boston isn't the only capital for biosciences innovation. This summer, during the brief break between surges in the coronavirus pandemic, I escaped to the San Francisco Bay area. And while I was there, I got a lesson about the considerable impact created by one particular Bay Area institution. Namely, the Stanford School of Medicine's Biomedical Informatics program, or BMI for short.BMI trains students how to use and adapt computational methods like machine learning to solve hard problems in biology and medicine. And a remarkable number of BMI alumni have fanned out into the world of life science startups. On today's show you'll hear from three of them. We'll talk about the work their companies are doing now and how the skills and connections they picked up at Stanford have played into their careers.The first guest, and the person who helped to organize the group interview, has actually been on the show twice before. His name is Andrew Radin, and he joined me in November of 2018 and again in August of 2020 to talk about his Palo Alto-based company Aria Pharmaceuticals, formerly known as twoXar. Aria uses a collection of proprietary AI algorithms to discover new small-molecule drugs for a range of diseases. In traditional drug discovery, years can go by between the identification of a new drug candidate and testing the drug in animals. Radin says Aria's AI can reduce that time to just weeks.Andrew kindly recruited two of his fellow Stanford BMI alumni for our conversation. One is Peyton Greenside, the co-founder and chief scientific officer at BigHat Biosciences in San Carlos, California. The company combines wet-lab science and machine learning to make it easier and faster to design new antibody therapies. And again, the leap forward is that BigHat's rapid cycle of antibody design, synthesis, and characterization vastly speed things up, reducing the time required to identify new therapeutic antibodies from months to just days.And our final guest is Tim Sweeney. He trained as a surgery resident at Stanford and then founded a company to tackle one of the biggest problems in acute care, namely how to diagnose infections faster and more accurately. The company is called Inflammatix, and it's building a device that emergency departments and outpatient clinics can use to rapidly analyze messenger RNA in patients' blood to screen for sepsis and other kinds of infections.All three of these companies are benefiting in different ways from the computational methods their founders studied at Stanford. And they've got some great stories to share about how their time at BMI convinced them that future progress in medicine and drug discovery would depend on data above all else.We originally planned to meet up in person for this interview. But we switched to Zoom at the last minute out of concerns over the Delta variant. So without further ado, here's my talk with Andrew Radin, Peyton Greenside, and Tim Sweeney.Harry Glorikian: Well, hello everybody. And welcome to today's show. Tim Sweeney: Thank you. Peyton Greenside: It's great to be here. Harry Glorikian: Yeah, it's, it's great to have all of you here. For everybody listening and watching, we were actually supposed to do this in person, but unfortunately the Delta variant sort of threw a monkey wrench in that whole process. So I reserve the right that we can do this in the future and actually get together when this whole thing is over, like normal human beings. Each of you are working on super exciting things. Different companies, focusing in different areas. And I know you all know each other, so I'm going to step back one second and say, if you had to give a brief description of your company or pretend you don't know each other, where we're at a cocktail party and you're going to give me two or three sentences about what you're doing and why it's interesting, how would you sort of do that? And Andrew, since you're the ringleader that sort of helped bring this group together, I'll throw it out to you first to sort of get going.Andrew Radin: Well, that's a lot of pressure, but certainly like, our description I think is pretty simple. We are a preclinical stage pharmaceutical company. And we happen to have a proprietary artificial intelligence platform that's discovered all the assets that we have under development. And these days we have 18 programs, 18 different disease areas where we've got new experimental medications and we are working on progressing those new inventions to the clinic and ultimately to FDA approval.Harry Glorikian: Peyton?Peyton Greenside: Hi everyone. I'm Peyton and one of the co-founders of Big Hat Biosciences, and our mission is to improve human health by making it easier to design advanced antibody therapeutics. So we actually do that through a combination of a high-speed wet lab and machine learning techniques in order to very iteratively design and improve antibodies until they meet unmet patient need. And it's been a lot of fun. Then we've been founded since 2019.Harry Glorikian: And finally, Tim. Tim Sweeney: thanks for the opportunity, Harry. Inflammatix was founded about five years ago, spun out of Stanford along with, of course, Aria and Big Hat. We are designing novel diagnostics focused on acute care and critical illness needs. So we basically have a data analytics platform that allows us to decode certain signals of gene expression within the immune system. And then for those of you watching, I'll show you, we have a cartridge that allows us to sort of implement that in a 30 minute point of care diagnostic setting.So our particular focus is basically bringing precision medicine into acute care settings, the hospital, the clinic, the ICU, where sort of historically there hasn't been a lot of diagnostic innovation. Harry Glorikian: Interesting. That's funny because I actually, I wrote a a textbook on how to commercialize novel diagnostics a few years ago. Because you know, unless you've been through the ringer, you may not know all the different pieces.But you guys now all know each other right? Now, that may not surprising because we're in Silicon Valley, and I'm actually in Berkeley right now, but that's close enough. And drug discovery companies and tech companies are all swimming around each other. But your connection is a little bit deeper. I mean, you guys all went to Stanford together. So this is not necessarily a commercial for Stanford, but it's, that's pretty interesting that three CEOs of data-driven, you know, healthcare companies out of the same class, whoosh, come out of Stanford. So how did you, how did you guys meet at first?Andrew Radin: Well, and I would say we're not the only ones to—it's just, you know, the people that happen to be in front of you today. It was funny. So, right before this, I sent a panicked email, because I didn't want to say something that wasn't true. I was like, Peyton, you were in this class, weren't you? Peyton Greenside: Yeah. I don't know if I was Andrew's TA or if we'd all actually been in the same class. But I think our Stanford journeys all started, it sounds like, the same year. Same time. And we all were taking translational bioinformatics, which was a course taught by, I believe, Atul Butte who I think, you know, really brought to fame the idea of big data for biology, what you can draw out a very large data sets and drawing insights. So we were all in the same class and with many other people, as Andrew said, and it was a lot of fun. And I think it was the start of long journeys for all of us than in a similar vein. Andrew Radin: And it was a place for…I think what was awesome about that class, again, not to be an advertisement for the coursework, but it was kind of my characterization of the class was, you basically learned how other people use data science to solve some medical mystery, like across the spectrum. And so the, the purpose of learning all that was to just kind of fill you full of ideas of things that you could do. And then the kind of the capstone of the class was a final project where you basically had to come up with something, right? And so you were just sort of primed with all this like super interesting sort of research on how other people had approached very different problems in the space. And for me, it was just the source of lots of interesting ideas that then, you know, helped me ultimately create what's the technology behind our company today. Tim Sweeney: It is remarkable how much came out of Stanford biomedical informatics. Though, I mean, to Andrew's point, there are, there are a number of other CEOs that came through in that sort of in maybe a five or seven year stretch, all out of the same program. And I think a lot of it had to do with that, yes, this one particular class had all the different applications of data science sort of across the spectrum of life sciences, but they also attracted people like that. Right? I mean, everyone on this call has a very different background before Stanford BMI. And I think that was part of what made that culture so special is that it ended up being a real team sport, whether your background was medicine or business or math or computer science or bio-engineering or anything else, learning a technique from A, and applying it into area B, I think, was a pretty successful way to grow innovation. Harry Glorikian: I feel like as a venture guy, I should be standing at the exit door and just sort of saying, you know, “What's your idea, what's your idea,” screening as they're coming out the door.Peyton Greenside: Well, you know, some folks have also become venture capitalists. Harry Glorikian: That's true. Peyton Greenside: Yep.Harry Glorikian: So was there anything in particular that you guys, interests or questions or discussions that you sort of bonded over that sort of brought you together? I mean, even, even as just friends that decided to keep in touch? Andrew Radin: Well, I think it's probably different for different people. I think the first real interaction I had with Tim, you know,the details escape me, because this is almost 10 years ago now, but I remember, he's a medical doctor, right? He's got a MD and a PhD if I'm, if I'm not mistaken. And so my, you know, I'm a hardcore computer scientist. That's my background. And so back in those days, I was rapidly learning all I could about medicine and biology. And I don't remember the topic, but I do recall him helping me after class was something that wasn't just quite, you know, sitting in my head correctly. And I remember thinking like, what a nice dude, to, like, you know, kind of take some time and give me like, you know, a little private tutoring. And then and then if I recall afterwards, you said, yeah, so I'm trying to do this stuff with some clinical data. Can you help me with this sort of stuff? Which if I remember correctly, I never actually helped you. I was talking about, oh, I might be able to help you. And then eventually you said, “I figured it out. I don't need you”Tim Sweeney: I said I needed to build a web scraper. And I said, I have no idea how to.Andrew Radin: Oh yeah, I have totally done that. Lots of times. So yeah, something like that. That's how the conversation started with Tim, which was sort of to the point about having very different backgrounds, You know, with Peyton, I don't really recall the first interaction. I remember we were in a journal club, maybe with Russ and you were talking about some stuff, but I think the more I got connected to her was around the time she was working on her defense and I actually went to her PhD defense. And I have this BS detector that sometimes go off a little early, right? When people make a statement, I'm like, “I don't know about that.” We're sitting in her defense and every time she said something that made me, do one of these, like, “Wait a minute,” she instantly resolved that in the next sentence. I was like, “Okay. All right. That's cool.”Peyton Greenside: Okay, that feels good. Fortunately, fortunately. Andrew Radin: You don't have to pass my scrutiny obviously, but yeah, I think that led to a number of kind of interesting conversations as she was contemplating, you know, what to do next. She was moving through her career, but yeah, I think that the interactions are very, very different for each person. At least that's my view, but I don't know if you guys have different memories. Peyton Greenside: Yeah, I think what's, what's interesting, I mean, just generally I agree with that. And I think one of the most interesting parts of BMI, as Tim said, is just the backgrounds that everyone has. And I also come from the kind of applied math, computer science background, and there's this kind of fascination of what you can do with computational skills in biology. I think to me, a lot of the conversations were around where do I even apply this to? I think people sort of think of computational biology as a, maybe sort of a niche, small field at the intersection of maybe somewhere where biology meets, I guess, you know, statistics, computer science and math. But it's so broad and it's so vast. And I think most of the, I say the most exciting conversations I've had are, you know, we work in immunology, you know, you're a clinician, you work with clinical data. How do you apply these tools? The most daunting but fun task upon showing up at Stanford with such an incredible ecosystem here is, where do you even focus your attention? Where should you work? There's too many exciting opportunities to pick. And I think some of the fun conversations I remember also having a Tim, with a more clinical background, is what's actually useful? You know, I want, I want to do something useful and sort of try to figure out, you know, where this, you know, where are you can actually kind of apply your time to the most impactful problem. It was a lot of fun. Andrew Radin: And I think, Tim, it'd be great for you to share. I mean, when we first met, I'd asked you kind of like, what were you doing there? What your story was? I can't remember the words back then. But you basically said like, “Look, I'm a surgeon,” if I recall, “I'm trying to save people's lives and I'm just thinking like, is there a better way? Can I like just, you know, do something that's going to have a much larger impact? And I don't know what that is yet.” I know I'm wildly paraphrasing what you said, right. But I'm thinking about like what that could be. And I think. You know, when I met you, you were sort of on the hunt for figuring out where to apply, you know, kind of the, the skill set.Tim Sweeney: I think that the everyone shows up with their strengths and weaknesses. Mine certainly was the summer before the program actually started, I had to take, you know, basic courses in computer science and linear algebra. And I remember, I mean, I literally went from my last overnight call at Santa Clara Valley Medical Center, running two ICUs, to the next morning CS 106x. Which, because it was the summer, was filled with all the high school students that are just total whiz kids, like 16 year olds, and they're like, you know, we're learning like order of operations or something and they're raising their hands and I'm like desperately trying to write down like, oh, if n means....You know, and obviously Andrew and Peyton were among the folks that sort of helped me on the basic science side of things. But I think that the story about sort of getting the question right is absolutely correct. And I remember actually the time that I knew I was in the right program was maybe two or three months in to training. They used to have these like sort of work in progress talks, and it was like, you know, Wednesday or Thursday or something, you bring a lunch. And somebody was talking about this thing that sounded very, very cool to me. It was all about how you could, you could program a system to learn new knowledge on its own. And it was like, you know, generalized AI for health data. And I was incredibly impressed. And, and the first example that was given was like, you know, so we've sifted through all of the billions of data points. And I have discovered—he stumbles over the drug name—I've discovered that plopacapagril, by which he meant clopidogrel, is associated with bleeding events. And everyone goes, “oh.” And I put my hand up, like, “That's an anti-platelet medication.” And he looks at me and I'm like, “the point of that is that it thins the blood.” He looked at me and was like, “So bleeding is a known side effect?” Totally crestfallen that people knew this already. Like, he had no idea. I was like, I do have something to contribute, so it's good. It's a good merge.Harry Glorikian: Yeah. So, you know, Tim, you're running a diagnostics company you know, Peyton and Andrew you're running what I'll lump together as drug discovery companies in different markets, different regulatory processes. You know, I'm sure there are common challenges to life science startups in the valley. What are some of the biggest challenges that you guys see? Is it scalability? Is it finding the right people? Is it finding the right investors? Where do you guys see your challenges?Andrew Radin: And I would just say for a little clarification to Peyton's point about there's so many different problems. Even though Peyton and I are both in the business of creating new medicines, we couldn't be any more different. We're a small molecule company. She's a large molecule company. If you know what that means. You know, I'm making motorcycles, she's making trucks. Like, we're just, we're just, we're just doing completely different things. To your question about like, kind of what are the very similar things, we're not really even competing with one another from that perspective.But I think, to answer your question, at least from my viewpoint, you kind of have to do all those things. I think, you know, in startups, everything has to work. You can't sort of have any one thing that doesn't function and whether that's the science or the fundraising or the team or all of those things, if you've got a problem in any one of those areas, it can be life-threatening to the company.And so I think part of the experience for the entrepreneur is sort of, you know, because your time is limited and your resources are limited is sort of finding a best fit to try to solve, you know, or, or to maximize all of those problems simultaneously. And I would say all the things that you've listed, they all at various points in the company, they've been critical and it's more of a juggling act rather than “Geez, all you need to do is just knock it out of the park, on, you know, financing and who cares about anything else?” We know lots of stories where that hasn't gone well. Or you knock it on the park on an exceptional team, and the other things don't come together. So, you know, from my standpoint, all of that stuff has to work. Peyton Greenside: I think my answer continues. I think one of the things I, and what many people who just find, I would say many scientific, inquiries fascinating, is just what to work on that. And I have the same problem now, you know, I think it happened when I went to Stanford and happened you know, postdoc and have it happened now.And, in the context of my company, wo we basically have a platform that can work on engineering any protein. We work on antibodies, but really can be anything. So, you know, we have this landscape. There are tons of diseases with unmet need. There's sort of tons of opportunities for the type of therapeutic protein you would use, whether that's a standard antibody, monoclonal IgG, sort of a next generation antibody. And so we always have to decide, you know, what, what are the programs gonna be? What are you going to go after? What's the modality? And I think at the crux of it, like you know, for a drug discovery company, is what is the shape of your company. But our platform is so broad that basically we can work on so many things. And I, once again, by myself faced the same problem, which is okay, like, you know, where should we focus our attention? And that's been really fun. This is getting maybe more of Tim's background, but so we're learning more about the clinical side of things and where that need is and where that pairs with our technology. But I agree with what Andrew said, nothing really can go shortchanged, but that's been the same theme, I would say just now in a different vein. Harry Glorikian: Yeah. I mean, I think about this as a balance of dynamics where you're at different stages at different points, depending on where you are in the development cycle. And you need different people and different issues become a problem at different points or maybe become more acute at different points. But you know, all of you guys have one theme in common, which is why we're on the show together. It's data and some form of machine learning or other, you know, part of artificial intelligence that's being applied to find something valuable or identify some valuable piece of information that can make something actionable. It's sort of a big question, but how do you employ machine learning and AI in what you're doing in each of your businesses? Because I think of these things as like I have a toolbox and then I have to apply that tool in a very specific way with a specific set of knowledge that can feed it, where I can get an output that I'm looking for. And so each one of you, like you said, Andrew, you're, you're working on the motorcycle, she's working on the big truck, and he's trying to make sure that everybody gets diagnosed and not, not ends up in worse than they already are. So how are you each of you thinking or approaching this in your own unique way? If you can summarize. Tim, why don't you go first?Tim Sweeney: Our tests work by measuring a discrete number of genes within the body. It's their expression levels. So for instance, for our flagship test inset, we look at 29 different gene expression levels from, from blood. And then of course we have to somehow integrate 29 different levels into actionable information. And so the backend of that is the data science part, the machine learning. So step one is actually choosing what to measure. And then after you've chosen what to measure, then it's training hardened algorithms that turn 29 different things into a score that says, “This person has a bacterial infection.” And then of course doing that repeatably, doing it in a way that is traceable and verifiable. And then all of the post hoc, you know, how is it affected by different demographics? And how has it, in the actual context of care, and of course in the coming years when actually implemented in a health system, how does it impact patients and providers and does it save costs and improve outcomes?And maybe just since I didn't get a chance to answer, I think one of the questions about challenges is a lot of times it changes with the application that you're taking farther. Right? One of the things that we all have in common, I think is that we're all platform companies. And to, to Peyton's point, like you can apply that data science platform to a lot of different areas, but each one of those areas has to be taken through a very long development process to actually help a person and the challenges totally change along that development life cycle. Harry Glorikian: And just for everybody listening—so you developed this product. What is the, so what, what is the impact? Tim Sweeney: In our case, we decided that we wanted to go after one first indication that would be a big enough hit to make the business matter. We've got lots of things we'd like to do in the long run, but sepsis is an area of outstanding unmet need. And the “so what” is right now, if you go in and you're feeling sick and you see a doctor and you want to know, Hey doc, like, do I need antibiotics? There is literally no test that can answer that question. It's a guess. So it's not to say that antibiotics aren't administered quickly, but as a physician myself, I can tell you that that is it's a guess at first, and then you have to wait for tests to come back and those tests themselves are imperfect. And so something like 40% of antibiotics are probably misprescribed. And if you knew in 30 minutes, Hey, this person has a bacterial infection or no, you could greatly simplify care and really improve outcomes. And that's the premise. But the challenge of course is that beyond the data science, there's so much that goes into building the product and proving out the clinical data and get it through FDA and then getting it reimbursed and, and, you know, getting it rolled out more broadly, if you want to get to the point where you've actually helped a number of people and built a solid business. Harry Glorikian: When I, in my last company, before I moved on to venture, I, we had a strategy consulting firm and we did a lot of digging into sepsis. That was a big problem, a nut that people were trying to crack, and, you know, if you could crack it, the opportunity is quite significant.So Peyton, Andrew, how do you guys think about it? Because I'm, I'm thinking manipulating an antibody and sort of tweaking little parts of it until you find the exact fit. [It requires] supercomputing or massive computing. Peyton Greenside: It's funny. I actually think that the context in which we all met, which is you know, when I think big data was becoming really popular in medicine is actually a great context, I think, for where Big Hat ended up, and it's funny, because it's going to been kind of a long journey—it always happens when I look back, I'm like, yeah, that makes, that makes sense. Right? Based on where I was. We actually put a lot of our attention into integrating the wet lab with the dry lab. And this is actually, you know, with a goal of making big data into what I might call sort of smart data or agile data, which is that the idea of back in the day when first, I would say you got tons and tons of really large data sets. And you can sort of mine them, or you can look for trends. You can sort of just figure out something, you know, interesting relationship between gene expression and patient outcome. And I kept throughout my career feeling frustrated by being handed the dataset and sort of having to just mine it and not having kind of, you know, ownership of being able to say, “I want to look here, I want more data here.” Right? You're sort of handed a really large data set and you're, a passenger in this dataset that has already been generated. You cannot modify it. That's kind of the fixed dataset. And, you know, as a computational person, that, that you're often the second person, like a wet lab or experimental lab is making the data, then you kind of get it right. And so, you know, throughout I would say, especially in my time at Stanford this was very much the case, where I was felt kind of trapped in being given a data set that I didn't actually design, but I could sort of mine. And so at Big Hat we're basically trying to now put computation in the driver's seat and kind of change that paradigm. We're actually now, instead of just getting one large data set that you design up front, you acknowledge that biology and the science are very iterative, right? As as you said, you sort of start with an antibody sequence, but, you know, would you stop there? If you could just make one tweak, maybe you'd make it, you know, 10x better, 100x better with two. So how do you enable it? How do you want to enable that very rapid cycling? And so we view this as kind of the intersection of how closely can a lab and the computational side interact and how can they inform each other? How can you one learn from the other? And so we actually enabled a computational person to design an antibody on Monday and in a few days you synthesize, purify, characterize the antibody and kind of understand, are you moving in the right direction or are you not? And repeat, and then repeat it and repeat and repeat. So you don't get kind of stuck in the fixed data set again. So it's really attractive for a lot of ways, right? There are a lot of reasons you kind of can end up in a really good regime and it's big data or sort of area, but, you know, there's kind of a lot of lost opportunity in terms of being able to kind of be very agile and move toward something that looks promising and then iterate more. And the goal is that that will allow us to enable types of antibodies they don't even exist today because you can't engineer them that easily. You're kind of are stuck with a fixed format. So that's been really fun. And so we've been spending a lot of time designing the wet lab to kind of support the machine learning side and data science side from the ground up and, and vice versa.And so it's a pretty unique sort of set up. And I think I like to think of it as sort of smart data, right? You're thinking really closely about what should I generate that will be helpful and can use that to inform how you redesign the next dataset and improve your antibody every time in our case.Andrew Radin: Yeah, it's interesting to hear the different stories. You know, I think all of us are kind of taking the approach that, you know, what data sources and what artificial intelligence allows you to do is to take real world data and then make some prediction under uncertainty. You know, with the expectation that prediction is potentially better than what you could, what you could do with other methods.And so, you know, kind of tying this back to when I was student and thinking about where are the places I can make a big impact, it was very interesting to me that with very complex diseases there was really no single biomedical measurement that would help kind of unravel the mystery of the biology behind that disease. And therefore could, you know, explain something about pathogenesis that would lead to a new discovery or a new medication as a result. And, you know, part of that coursework in 2.17 was this concept of integrative genomics. This idea of using, you know, different data sources that are all keyed to the same thing, maybe a, a gene or a gene product, and kind of looking for that overlapping evidence.And there were some great papers that were shown. There was one, I think, by, by Eric Lander in particular, where he was using, GWAS and proteomics and maybe some gene expression microarray data, each of which would give you, you know, like hundreds of quote-unquote “answers” and the real answers in there buried with a bunch of false positives. But ultimately what would happen in this paper is he showed that there was one overlapping gene in all three of these datasets and he ran some assays and determined, indeed that was the key to unlock this mystery. And that certainly worked well if all of your data sets are sort of keyed to the same thing, but that's not the reality of biomedical data sets. There's genomics measures, there's chemistry measures, there's phenotypical measures, there's different patient measures. And unless you're conveniently measuring them all from the same patient population over time, which is very expensive and very, very time consuming to do, there's really no easy way to sort of key all these things together. And my thought was like, “Hmm, maybe, maybe there, there is a way.” And so the technology that I created and ultimately has been expanded upon is taking this concept, the concept that the answer to a very complex disease doesn't necessarily live in any one measurement or anyone biomedical data set. And if you have the ability to ultimately pull in lots of very diverse—and by diverse I mean statistically independent—data sets across a wide range of biomedical measures and integrate them as a single processing unit, you can ultimately uncover things that other people essentially haven't noticed before. And then use that, in our case, you know, to do lots of things, but in our case specifically to develop new therapeutics. So in all of our disease areas, ultimately what this means is we are working on new mechanisms of action. These are, these are new, if you will, new concepts or new understanding of biology in these disease areas and therefore what it means or what the impact is—to your earlier statement—is, we're going after biology that potentially has a disease modifying effect that others have not approached before. And therefore the promise of the opportunity is to make a significant dent in these very complex diseases. And so that's a kind of a high level view of what we do, but ultimately it's all about, you know, integration of these very different datasets. And then using that to ultimately come up with new experimental medicine that we would explore and experiment with and see what it can mean for patient impact.Harry Glorikian: Yeah. I think that's one of the most exciting parts of when I talk to everybody. Assuming the system is designed well, and the data going in is actually good, it's like, “Wow, I didn't notice. I didn't know that that happened. I didn't know that pathway was involved or this little tweak could make this difference.” And so that's what I see when I talk to different people that are working in this area. “I just didn't know,” or “None of the papers talked about this,” or “That's not what I learned in school.” And so that's the most fascinating part of these systems where you can identify things faster, hopefully and more accurately, hopefully than you might normally do with a human being. No knock to human beings, all of them are valuable, but it seems the systems move at a different pace and can handle a much broader level of data being input into them. And so that brings me to the question that Andrew, you and I have talked about. If you had to put a timeframe around it or something is, is this shortening the time to discovery? And I think you and I, the last time we talked, you said to about three years where I can shave off on the front. And then at some point when I have to get to a mouse, I have to follow the normal trajectory of that mouse. But if that's changed and you you've, you're finding other areas, I'd love to hear it. But Peyton and Tim, where do you see the aha the speed or the financial impact of what you're doing? You're doing it because it's moving at faster or you're able to identify something that you haven't, but it's better than X or Y that's already being done in the marketplace.Peyton Greenside: For us actually, this is, I mean, we do do things faster. We do improve on a lot of metrics. But it's actually, at least for my companyl about designing antibodies that couldn't otherwise exist. So for example, the standard monoclonal IgG, there are many tools out there to sort of discover initial molecules and optimize them, but you start getting into these kinds of next-generation or kind of Frankenstein antibodies, antibodies that are a tenth of the size, or SCRBs which are these fragments that are part of car T therapies or other formats.They become more complex and people have trouble engineering them, and you can kind of run your imagination and say, well, if I had the ability to engineer things, what other formats would I conceive? Would I consider, tiny antibodies like cell-penetrating peptides that can get into cells and sort of have all sorts of characteristics? But they're difficult to engineer.And so we actually, instead of sort of doing the same thing faster we actually think more about how can we expand the universe of what could be a potential therapeutic protein and how would that solve current patient needs in ways that existing therapeutics do not. And we do that by doing things faster, sort of, and cheaper and, sort of. More smartly. But hopefully that's what we really care about. Tim Sweeney: I'd answer probably somewhat like Peyton's. But if you look at a diagnostics and biomarkers in particular, a lot of diagnostics are about, “Hey, you know, we found that if you measure this one protein that's useful for health.” So it's just a very slow process and it's not optimized. You tend to study things that are obvious because they're easy to measure. Or like in our field, there's one protein called procalcitonin that's sort of the current closest biomarker for whether or not somebody has a bacterial infection, but PCT, as procalcitonin is abbreviated, was discovered 30 years ago and it was originally basically by accident that someone even measured it in someone with bacterial infections, and then it worked pretty well. And you know what I mean, it's a sort of based on serendipity and it can't be improved upon it has. However good procalcitonin was yesterday, that's how good it's going to be tomorrow and how it's going to be the day afterwards.I think the benefit of data science and in diagnostics was really began with cancer, when you had sort of the wonderfully successful tests like Oncotype showing how you could measure signals across complex diseases by integrating things from multiple biomarkers. And a lot of those were designed and there, again, the problem was that they took a long time to develop. And of course they take a long time to actually run, right? I mean, most of them, if you've ever had one of those tests done, it's like a week to send out, you know, you send some tissue to a company, it gets processed. You get your answer seven days later. So one of the things we're doing differently, one, it has to do with the way that we gather and integrate data sets to empower faster discovery.And that's kind of like Andrew. The other is basically the ability to build new answers that haven't yet existed, sort of more like Peyton. And ultimately the hope is to create a feedback loop where you know, better and better versions of the tests can be slowly released. And so over time, it's not just that you're sort of stuck with, “Hey, you know, procalcitonin is as good as it is [going to get].” It's like, you know, you're on Insept version five in 2030, and it's now X percent more accurate. And I think that's a real benefit to patients.[musical transition]Harry Glorikian: I want to pause the conversation for a minute to make a quick request. If you're a fan of MoneyBall Medicine, you know that we've published dozens of interviews with leading scientists and entrepreneurs exploring the boundaries of data-driven healthcare and research. And you can listen to all of those episodes for free at Apple Podcasts, or at my website glorikian.com, or wherever you get your podcasts.There's one small thing you can do in return, and that's to leave a rating and a review of the show on Apple Podcasts. It's one of the best ways to help other listeners find and follow the show.If you've never posted a review or a rating, it's easy. All you have to do is open the Apple Podcasts app on your smartphone, search for MoneyBall Medicine, and scroll down to the Ratings & Reviews section. Tap the stars to rate the show, and then tap the link that says Write a Review to leave your comments. It'll only take a minute, but it'll help us out immensely. Thank you! And now back to the show.[musical transition]Harry Glorikian: So you guys have been doing this for a while. Do you see the promise of big data and AI playing out the way that you thought and or is, or is it different than you thought now that now that you like jumped into the pool and you've been swimming in it for a while? Is it fulfilling the dream you had, is it more exciting than you thought?Andrew Radin: It's a funny question. Coming from very different industries, you know, looking at where I was 10 years ago, I think I was very naïve about what it actually takes to bring a drug to market. And I think in the very early days of the company, you know, my prior startups, you know, one of them I was in and out in a year and it exited. And there's no such thing in this industry, to do anything like that. And so, you know, part of it was biased by my prior experience, but I think part of it as well is, sometimes I think it's also hard to see how far things have moved along. And I think even in Tim's description is he was sort of talking about, well, you know, this, this was state-of-the-art science, you know, in decades past you know, the work he's doing today was impossible back then. So, you know, there's sort of these steady, incremental improvements.And I, and I think part of what really is happening in the industry is that the things to solve essentially are becoming exponentially harder. For example, for high throughput screening, which is maybe the old way of doing things, to find a hit is exponentially harder. For diagnostic tests or blood tests to sort of detect these nuances, you sort of have to bring in these technologies and these capabilities that are exponentially better at solving those things.And so I think what happens is, you can therefore characterize it in a different way, you know, is the time faster compared to the old way? Well, of course, because those old ways just don't have a chance of being able to do these things. Like, is it cheaper? Well, yeah, because those old ways, again, just don't have a chance. But I think part of it is what is the pace of innovation? And that's, I think kind of where the rubber meets the road and what is actually possible and what it's capable of. And so today, you know, we're, we talk about having, you know, 18 concurrent disease programs and we've got a very small team and we haven't raised very much money. You know, that would just be flat out impossible 10 years ago. And we still like raise some eyebrows around that, but now, it's okay. We recognize software is doing a lot of what used to happen in the wet labs. So this, you know, sort of fits within the expectation of what a modern technology company would do in this space.So I think there's that other angle of where expectations are kind of catching up with what's actually been produced. And therefore, you know, at, at some point we become the old technology. Thirty years from now, some next generation we'll be talking about, oh, those, those slow, painful people that, you know, tried this in the past kind of stuff. And so it's, you know, each, I think each iteration of innovation has its moment in the sun, if you will. And this is definitely the time for the work that we're collectively doing.Peyton Greenside: I think the promise is ahead of us. We're in an amazing time where I think things are starting to gain traction. We're starting to get tools and infrastructure, but if I were to say my conception of what machine learning and data science and generally computational power is going to do in biology and medicine, I think it's just starting.So I'm excited to see things like AlphaFold. I'm excited to see a lot of these kind of tools and capabilities to be unlocked. But I think, you're solving a complex problem, right? That protein that you're affecting is in a cell, it's part of the tissue, and it's part of a human, and there's so many more layers, I think, to consider.Yeah, we're making great progress. And I still certainly believe in the potential. That's why I'm here. But I do like to say, I think we're at the very, very early days. And as Andrew said, I think it's going to be fun to see what happens in 30 years. So I'm still very excited, but I wouldn't say we're at the accomplishments that I would consider as sort of really demonstrating the cornerstones of machine learning in, in biology and medicine.Tim Sweeney: I have to agree with Peyton, I think the best is ahead of us. So one of the courses we had to take at Stanford BMI, and I don't know if you two remember this, was Marc Musen taught this course on ontologies, but part of it had to do with sort of like the history of applications of sort of clinical data systems. And the oldest one, I forget the details, but it was in like, the '70s. And it was around sort of you know, clinical decision support for therapeutic prescribing. Obviously that system isn't around today and failed for its own reasons and he sort of walked through all of the failures of systems since then.And maybe one of the most remarkable things is how, how little AI and machine learning is actually employed in most clinical practice. You know, for all the buzz around computer vision, the AI that radiologists use most is probably their dictation. I mean, it isn't yet commonplace to have machine assisted radiography reads. And so will that be coming? Absolutely. But the interesting challenges in each successive generation of like, oh, you know, we got pretty close, but it turned out that X wasn't good enough, or it wasn't built in the right way to be integrated with workflow or is coming soon, but still needs some regulatory work or whatever else. There's plenty left to do. Peyton Greenside: I, I think that's probably one thing we all experience actually transitioning from academia to industry is, what's exciting in academia is not necessarily what's going to be reliable when you really want to make a good drug. So what you might think about it, you'd be like, “Oh man, that's a really cool model. I'd love to try that, you know, that's great.” And you kind of go right into industry and you're like, okay, well this is going to matter. This is, this is going to go to patients. It has to work multiple times. I think it is a very different standard. Right. And so I actually think it's the right thing. Just because you find something to be very, very cool and kind of, you know, I would say cutting edge, you really want it to work and want it to work over and over again. I think there's an unappreciated gap between when something is first proposed or conceived of or demonstrated and when you can really make it work at scale, over and over again in areas that matter.So I think we're basically in that transition, for, I would say, a lot of these techniques in biology and medicine. Now let's get to work and practice. Let's get to work and practice reliably. And now we can start sort of really seeing where we're going with the needle on really impactful problems. But it's funny, because I do think that's an important divide between sort of where we all started together.Andrew Radin: Yeah, no, I would, I would agree with that. I mean, look, most of our focus, these days is not on discovery. It is actually in the development of the therapeutics. It is about, you know, preparing for IND filings. It's all the regulatory work we need to do there. It's medicinal chemistry. It's a whole bunch of things that are outside of the discovery process. And as we proceed to the clinic, more and more of our overall effort as an organization has less to do about the core innovation that created all of these assets and more about the heavy lifting you have to do to ultimately get that product to market.And I think, to kind of tie it back to my previous comments, I think there's been a new generation of capabilities that has been created. To what these guys just said, it's gonna be a while until we actually see those things in the clinic. And to Tim's point about, you know, computer vision and radiology, like there's, there's a lot of good science that's already there and has been shown, experimentally to do a better job than obviously the, the human looking at those images. But yeah, it it's gonna take awhile until that becomes the standard. I am, you know, my daughter was born almost five years ago now, but I was shocked to observe, even back then, which is only five years ago, that medical records were being passed from clinic to clinic with a fax machine. It just blew my mind. Like you gotta be kidding me, a fax machine? I don't think I've seen a fax machine in all these years. And so, yeah, I think part of it is, if you want to take the place where innovation moves the slowest it's certainly got to be, you know, government, healthcare, or education. I'm not sure which of those might be the slowest, but there is a time for these new technologies to permeate the industry. And that is going to take time. And I think that's when, ultimately, patients and the people that are on the receiving end of all this innovation, like that's, when they're going to see that difference. And it is going to take many years for this stuff to kind of make its way through the process and ultimately into the hands of providers and ultimately to patients. And that big benefit is going to come in the years to come. It's obviously not in front of patients in many cases.Harry Glorikian: Yeah, well, maybe my brain is wired towards risk or innovation because I'm like, “well, if you're, if you wait till it's done to get involved, you're way too late,” right. You're going to be a dinosaur or you're going to be obsolete. And we've seen that in a lot of areas of tech compared to, you know, old standard industry.There was a great piece the other day about this engineer at Ford who had been working on the gas engine for 40 years and then wakes up one morning and he's like, I need to take early retirement because software and electric EV is the way it's going to go. And now I'm just in this sort of maintenance mode of what I'm doing.And I think about healthcare and I'm like any institution that isn't at least dabbling in using image analytics. for radiology or something and starting to get used to this, I think they're way behind where they may want to be in the next five years, because technology doesn't follow just a slow curve on the way up. It has a way to go straight up at one point it before moving into an exponential curve. And I think the same for you guys. I mean, those companies that are not involved are partnering, investing in entities like you guys is, if you wait till it's finished, you're, it's already too late. Because Andrew, your system will keep kicking out new molecules and Peyton, you'll be making new antibodies and it'll be a little too late to catch up. I mean, that's, that's the way I think about it. Andrew Radin: I would temper that a little bit and the reason I would say that is because the companies that have been successful in the past in creating diagnostics and therapeutics…Products are on patent. They have long life cycles and they generate lots and lots of cash. And so, you know, big pharma, big diagnostics companies, they can kind of wait around and sort of see how things shake out with different younger companies and simply, buy or acquire, assuming that the companies are willing to be acquired. And so I think, large firms have been very successful in becoming, you know, acquisition and essentially manufacturing and marketing machines. So I don't necessarily think that some of these larger and established players that they're necessarily, their livelihoods are threatened. I think they will continue to acquire the best of the best with their, with their large cash reserves. I think some companies in this space will gather the momentum and break out. And I think in time we might see some changes over time as to what the big, you know, sort of players are in this space. But it's unlike other industries. Certainly software. It's like MySpace disappears and Facebook reappears the next day. And that's because you can deploy new technology and move users over in the course of an afternoon. And from a therapeutic perspective or a diagnostics perspective, that's just not that the pace at which those things move.So there's, there's lots of room for that. You know, and maybe similar in the automotive industry, you kind of have to build a factory and build some cars. It takes some times, right? So, so maybe there's some parallels there, I think in some cases, but. I don't see like a wholesale change happening overnight. At least from where I stand. Harry Glorikian: Not overnight, but we definitely have to have dinner and like have a discussion around this topic. Because I would love to bring some examples to the table about how I see things. Once you digitize something, the model itself doesn't have to stay the same way as it used to be. It is up for change. So I think those are the shifts that may change the dynamics of the market.But I'd love to have that discussion with a wonderful glass of wine. After having come from Napa this week, I can show up with a few nice bottles. Thank you so much for taking the time. Andrew, thank you for bringing this group together. Peyton, Tim, it was wonderful to meet both of you. I hope that we stay in touch and I'll keep watching the companies as they, progress. And I wish you guys incredible success. Peyton Greenside: Thanks so much. Tim Sweeney: Thank you Harry. Andrew Radin: It was our pleasure.Tim Sweeney: Andrew, Peyton, good to see you as always.Andrew Radin: Absolutely. Peyton Greenside: You too.Harry Glorikian: That's it for this week's show. You can find past episodes of MoneyBall Medicine at my website, glorikian.com, under the tab “Podcast.” And you can follow me on Twitter at hglorikian. Thanks for listening, and we'll be back soon with our next interview.
You may have seen the very scary headlines this weekend about the COVID-19 Delta variant. One of those was out of Florida, which hit the highest number of new COVID cases since the pandemic began. And last Wednesday Texas reported more than 10,000 new COVID cases, its highest total for a single day since February. In D.C., the indoor mask mandate for those vaccinated went back into effect, as it did for many other parts of the country. Plus, the Biden administration's messy COVID messaging. And, why the pandemic means less long-distance romance. Guests: Julie Rovner, Kaiser Health News' Chief Washington Correspondent and host of What the Health podcast, and Axios' Erica Pandey. Credits: Axios Today is produced in partnership with Pushkin Industries. The team includes Niala Boodhoo, Sara Kehaulani Goo, Dan Bobkoff, Alexandra Botti, Nuria Marquez Martinez, Sabeena Singhani, Alex Sugiura, and Michael Hanf. Music is composed by Evan Viola. You can reach us at firstname.lastname@example.org. You can text questions, comments and story ideas to Niala as a text or voice memo to 202-918-4893. Go deeper: Fauci: New lockdowns unlikely despite surge in Delta cases Biden's quick-trigger COVID problem The end of long-distance relationships Learn more about your ad choices. Visit megaphone.fm/adchoices