Podcasts about cfd

Den här veckan har det hänt otroligt mycket – både i Sverige och på andra sidan Atlanten:Världens högst värderade bolag Nvidia når fem biljoner dollar i börsvärde, efter att man presenterat planer om kvantdatorer och nya miljardaffärer. Den svenska snackisen Intellego flyttar fram sin rapport efter en tid av stor volatilitet, vad betyder det egentligen? Sällsynta jordartsmetaller och kärnkraft behövs båda för att driva AI-revolutionen, men hur intressanta är de att investera i just nu?Besök IG.COM⁠⁠⁠⁠Prenumerera på Morgonrapporten av Patrick Thomenius⁠⁠Optioner är komplexa finansiella instrument. Handel med dessa instrument medför en hög risk för snabb förlust av pengar.CFD-kontrakt är komplexa instrument som innebär stor risk för snabba förluster på grund av hävstången. 71 % av alla icke-professionella kunder förlorar pengar på CFD-handel hos den här leverantören. Du bör tänka efter om du förstår hur CFD-kontrakt fungerar, och om du har råd med den stora risken för att förlora dina pengar.

Welcome to The Chopping Block — where crypto insiders Haseeb Qureshi, Tom Schmidt, Tarun Chitra, and Robert Leshner chop it up about the latest in crypto. This week, Kaledora Linn, Co-founder and “Empress of RWAs” at Ostium, joins to break down the rise of on-chain equity perps, the funding-rate chaos that hit 365%, and why she believes the next wave of tokenized assets won't come from exchanges—but from structured liquidity markets. We dive deep into Ostium's hybrid CFD model that blends TradFi mechanics with on-chain transparency, explore why most retail traders can't stomach perp carry costs, and debate what “safe leverage” could look like in an RWA world. The panel also touches on CZ's presidential pardon and Coinbase's new Echo platform, connecting the dots between political optics, capital formation, and how crypto's product design is evolving beyond speculation. Whether you're building perpetual DEXs, tokenizing RWAs, or just trying to survive the next funding-rate spike, this episode unpacks how market design, UX, and regulation will shape crypto's next trillion-dollar frontier. Show highlights

Chilli explains what the viral "Group 7" TikTok trend means. Kidd went to a haunted house. Kidd is excited to experience his first trick-or-treaters. Chilli says he needs to choose his candy wisely. What is the best/worst candy to give out on Halloween? CFD...Amani from Hyattsville. Her date went to the bathroom and never came back. His excuse will shock you. CALLS about Halloween candy.

Välkommen till veckans avsnitt av IG Börssnack!Veckans hetaste nyheter – Trump utmanar kvantdatorbranschen, vetepriser rusar och USA:s nya sanktioner mot rysk olja får omedelbara effekter på marknaden.Nobelprisad cancerbehandling – Vi tittar på den revolutionerande tekniken som kan rädda liv och vilka bolag som leder utvecklingen framåt.Grönt stål efter Stegra – Många tvivlar efter de senaste månadernas turbulens. Men har tekniken ändå en framtid? Vi analyserar potentialen.Besök IG.COM⁠⁠Prenumerera på Morgonrapporten av Patrick Thomenius⁠Optioner är komplexa finansiella instrument. Handel med dessa instrument medför en hög risk för snabb förlust av pengar.CFD-kontrakt är komplexa instrument som innebär stor risk för snabba förluster på grund av hävstången. 71 % av alla icke-professionella kunder förlorar pengar på CFD-handel hos den här leverantören. Du bör tänka efter om du förstår hur CFD-kontrakt fungerar, och om du har råd med den stora risken för att förlora dina pengar.

TALKBACK caller shares thoughts on AI for NFL. The latest travel trend...and AIRPORT DIVORCE. CALLERS share their ghost stories. CFD...Violet in College Park. Her date's bubble tea temper tantrum was a huge turnoff. CALLERS with ghost stories.

In this episode of the Real Estate Notes Show, hosts Dave Putz (JKP Holdings) and Nathan Turner (Earnest Investing) sit down with veteran investor William Tingle (26+ years in the trenches) to bridge the gap between seller finance and note buying. From vocabulary clashes to court-tested strategies, William breaks down why he buys Subject-To, sells on contract for deed (not wraps), and how he engineers cash flow without predatory tactics. If you create notes, buy notes, or want safer, scalable deals, this one's a masterclass.

Inspector General finds “critical shortcomings” in CFD's Fire Prevention Bureau full 55 Thu, 23 Oct 2025 16:15:00 +0000 sJSgPb2013g4u8faZfdGorZxEgp0DdeU news Chicago All Local news Inspector General finds “critical shortcomings” in CFD's Fire Prevention Bureau A dive into the top headlines in Chicago, delivering the news you need in 10 minutes or less multiple times a day from WBBM Newsradio. 2024 © 2021 Audacy, Inc. News False https:/

Inspector General finds “critical shortcomings” in CFD's Fire Prevention Bureau full 55 Thu, 23 Oct 2025 16:15:00 +0000 sJSgPb2013g4u8faZfdGorZxEgp0DdeU news Chicago All Local news Inspector General finds “critical shortcomings” in CFD's Fire Prevention Bureau A dive into the top headlines in Chicago, delivering the news you need in 10 minutes or less multiple times a day from WBBM Newsradio. 2024 © 2021 Audacy, Inc. News False https:/

Inspector General finds “critical shortcomings” in CFD's Fire Prevention Bureau full 55 Thu, 23 Oct 2025 16:15:00 +0000 sJSgPb2013g4u8faZfdGorZxEgp0DdeU news Chicago All Local news Inspector General finds “critical shortcomings” in CFD's Fire Prevention Bureau A dive into the top headlines in Chicago, delivering the news you need in 10 minutes or less multiple times a day from WBBM Newsradio. 2024 © 2021 Audacy, Inc. News False https:/

Kidd is moving in two days and hasn't started packing. The "996" Work Trend. Average person has four negative thoughts about their body every day. CFD...Grace from Bethesda. Her date was going great...until he asked to take a closer look at her shoes.

Välkommen till veckans IG Börssnack!Denna vecka dyker vi ner i tre heta ämnen:Krypto under Trump - Vad betyder den nya administrationen för bitcoin, altcoins och stablecoins? Vilka bolag tjänar på att stablecoins blir mainstream?Saab rapporterar - Vi analyserar Saabs senaste siffror och vad framtiden ser ut att bjuda på för försvarsbolaget.Spannmål på väg upp - Råvaran som kan vara på väg in i en ny uppåtgående trend. Vi kollar på vad som driver priset.Plus: Spännande rörelser i Kina som kan skaka om Nvidia och andra halvledarjättar.Läs gärna Patricks artiklar relaterade till veckans avsnitt:Så här tar du rygg på uppgången i spannmålspriser Bitcoin har nått vägs ände - en analys av Bitcoin Besök IG.COMPrenumerera på Morgonrapporten av Patrick ThomeniusOptioner är komplexa finansiella instrument. Handel med dessa instrument medför en hög risk för snabb förlust av pengar.CFD-kontrakt är komplexa instrument som innebär stor risk för snabba förluster på grund av hävstången. 71 % av alla icke-professionella kunder förlorar pengar på CFD-handel hos den här leverantören. Du bör tänka efter om du förstår hur CFD-kontrakt fungerar, och om du har råd med den stora risken för att förlora dina pengar.

Reclining Seats on Westjet Airlines will soon cost extra...but there are other perks. Survey: 28% say they love watching scary movies...even though watching them makes people afraid of dark. What's your favorite scary movie? CFD...Helton from Nokesville. Sold his text books to pay for date.

I veckans avsnitt av IG Börssnack dyker vi in i tre heta ämnen som formar marknaden just nu.Vi startar med Verisures uppmärksammade börsnotering – var det verkligen "gratispengar" att teckna sig? Sedan pratar vi om den extremt volatila Intellego och ger våra bästa tips inför rapportperioden.Veckans spaning handlar om kvantdatorer – framtidens teknologi eller bara hype? Vi tittar närmare på IonQ, Rigetti och D-Wave Quantum. Avslutningsvis tar vi ett djupdyk i AI-revolutionen. Från hårdvarujättar som Nvidia och ASML till de galna affärerna vi sett den senaste tiden – bygger vi verkligen en lånabubbla? Vi spanar in Bloom Energy, Brookfield och Marvell Technology.Plus: marknadskommentarer om USA:s nedstängning och spänningar mellan USA och Kina.IG: ⁠www.ig.com/se⁠Prenumerera på Morgonrapporten: ⁠https://www.ig.com/se/morgonrapport⁠Optioner är komplexa finansiella instrument. Handel med dessa instrument medför en hög risk för snabb förlust av pengar.CFD-kontrakt är komplexa instrument som innebär stor risk för snabba förluster på grund av hävstången. 71 % av alla icke-professionella kunder förlorar pengar på CFD-handel hos den här leverantören. Du bör tänka efter om du förstår hur CFD-kontrakt fungerar, och om du har råd med den stora risken för att förlora dina pengar.

Börssnack är tillbaka - nu som podcast! Vi drar igång med att djupdyka i elbilsindustrin där vi tittar på Tesla, konkurrenterna och underleverantörerna. Kan bitcoin fortsätta upp nu? Och ska man köpa Klarna-Sebbes Flat Capital efter raset? Det är några av sakerna vi går igenom i veckans avsnitt!IG: www.ig.com/sePrenumerera på Morgonrapporten: https://www.ig.com/se/morgonrapportOptioner är komplexa finansiella instrument. Handel med dessa instrument medför en hög risk för snabb förlust av pengar.CFD-kontrakt är komplexa instrument som innebär stor risk för snabba förluster på grund av hävstången. 71 % av alla icke-professionella kunder förlorar pengar på CFD-handel hos den här leverantören. Du bör tänka efter om du förstår hur CFD-kontrakt fungerar, och om du har råd med den stora risken för att förlora dina pengar.

Send me a messageIn this week's episode of the Sustainable Supply Chain Podcast, I sat down with Ollie Taylor, Founder & Director of Marine Futures, to talk about one of the toughest nuts to crack in sustainability, decarbonising the marine industry. Boats, big or small, don't often top climate discussions, yet their materials, manufacturing, and fuel use carry a hefty footprint.Ollie explains how Lifecycle Assessment (LCA) can reveal the true environmental cost of marine products, from resin to recycling, and why so many “green” designs turn out to be anything but. We unpack how his platform, Marine Shift 360, is helping designers and builders make data-led choices early in the design phase, where up to 80% of a product's total impact is decided.We also dive into the data problem: how poor visibility, outdated datasets, and supplier secrecy distort sustainability claims. Ollie argues that transparency, education, and automation are key to bringing LCA into the mainstream, making it as essential as CAD or CFD in engineering.Other highlights include the promise of circular design to stabilise volatile supply chains, the limits of regulation versus commercial pressure, and why profitability and sustainability must align for real progress.If you care about data-driven design, circularity, and cutting emissions at the source, this episode is worth your time.

Which game show do you think you could clean up on? Woman made history on Wheel of Fortune winning over million dollars this week. Some people are doing the "try before you buy" thing with new homes. We discuss. 75% of people rely on "therapist surrogates". Who/What do YOU turn to for emotional support? CFD...Diane from Middle River...her date took her to a place that creeped her out so bad, she asked him to take her home immediately.

In this episode, Professor Brian Launder (Professor at the University of Manchester and Fellow of the Royal Society and Royal Academy of Engineers) shares his remarkable journey through academia, detailing his early fascination with heat transfer, his transition to MIT, and his significant contributions to turbulence modeling and computational fluid dynamics (CFD). We touch upon the key role that Professor Brian Spalding had on his career as well as work that led to the breakthrough k-epilson turbulence model as well as the pioneering work on second-moment closure model. Prof Launder highlights the key role of collaborators and ex students such as Professors Hector Iacovides, Tim Craft, Bill Jones, Kemal Hanjalić and many more. He ends with advice for early-stage researchers and reflections on more than 50 years worth of academic research.Chapters00:30 Introduction05:00 Early Academic Journey10:06 Transition to MIT and Research Focus16:21 Return to Imperial College and Early Career21:06 Research Projects and PhD Students27:46 Development of the k-epilson model33:18 CHAM and Career Changes36:24 Move to UC Davis and New Research Directions44:05 Challenges and Opportunities in Research47:07 The Interview Experience51:14 Transition to Manchester University52:23 Research Innovations in Turbulence Modeling57:45 The Development of the TCL Model01:03:15 Nonlinear Eddy Viscosity Models01:05:58 Advanced Wall Functions and Their Applications01:10:09 Reflections on Career and Contributions01:15:49 Legacy and Impact on Turbulence ModelingTop Turbulence Modelling contributions (https://scholar.google.com/citations?user=Y3JbAK8AAAAJ&hl=en) 

CALLS...a third of Americans choose to return to the same vacation spot year after year. Where is your repeat vacay spot and why? It's National One Hit Wonder Day. AI Artist Signs Million-Dollar Record Deal. Would you pay for AI generated art? CFD...Meghan (Lynchburg) went to a Sabrina Carpenter concert with a guy who acted like a manchild.

On Monday, President Donald Trump, Department of Health and Human Services (HHS) Secretary Robert F. Kennedy Jr., and other Trump administration officials announced a pair of actions the Food and Drug Administration (FDA) will take to address the increase in autism spectrum disorder (ASD) in children. First, the FDA will update the warning labels for acetaminophen — the active ingredient in pain relievers like Tylenol — to note a potential association between the ingredient and neurological conditions — such as ASD and attention-deficit/hyperactivity disorder (ADHD) — in children (though it also emphasized that no causal link has been established). Second, the agency has initiated the approval of leucovorin calcium tablets for patients with cerebral folate deficiency (CFD). Ad-free podcasts are here!To listen to this podcast ad-free, and to enjoy our subscriber only premium content, go to ReadTangle.com to sign up!You can read today's podcast⁠ ⁠⁠here⁠⁠⁠, our “Under the Radar” story ⁠here and today's “Have a nice day” story ⁠here⁠.You can subscribe to Tangle by clicking here or drop something in our tip jar by clicking here. Take the survey: What do you think about the HHS announcement, autism, and Tylenol? Let us know.Disagree? That's okay. My opinion is just one of many. Write in and let us know why, and we'll consider publishing your feedback.Our Executive Editor and Founder is Isaac Saul. Our Executive Producer is Jon Lall.This podcast was written by Ari Weitzman and edited and engineered by Dewey Thomas. Music for the podcast was produced by Diet 75.Our newsletter is edited by Managing Editor Ari Weitzman, Senior Editor Will Kaback, Lindsey Knuth, Kendall White, Bailey Saul, and Audrey Moorehead. Hosted on Acast. See acast.com/privacy for more information.

Im Gespräch mit François Bloch – Einsichten eines Schweizer Finanzexperten

New trend..baby showers for grandmas. 25% of people don't know what their partner's favorite flower is. We call Chilli's husband. Kidd's uber driver was watching YouTube while driving. What's the craziest thing your rideshare driver did? CFD...Don in Leesburg went on a date to a haunted house. Her reaction left him traumatized. CALLS about rideshare drivers.

What age did you let your kids walk to/from school alone? Crash's son is doing it for the first time this year. Listener Dylan sent email wanting advice about how to convince his parents to support his decision to quit job. CFD...Cathy in Woodbridge into a car accident with a guy who ended up being a felon. CALLERS with advice for Dylan.

0:00 - Remembering Charlie Kirk 36:58 - James A. Gagliano, retired FBI supervisory special agent and a doctoral candidate in homeland security at St. John’s University, looks at culture issues on college campuses - "They claim to be liberals but they don't want to hear your side" 57:38 - Reaction from the Left 01:18:25 - Patrick Maloney, Chicago FD Special Operations Chief – retired – shares his experience as one of the many CFD members who deployed to Ground Zero on September 12, 2001 01:31:11 - "There was no security" 01:35:40 - Ian Rowe, founder of Vertex Partnership Academies and senior fellow at AEI, on the dehumanizing narratives in schools that brand dissenting views as evil. Ian is also the author of Agency: The Four Point Plan (F.R.E.E.) for ALL Children to Overcome the Victimhood Narrative and Discover Their Pathway to Power 01:54:42 - RealClearPolitics’ Susan Crabtree on security for the president, vice president, and conservative figures — and whether the Secret Service is up to the task. Susan is also the author of Fool’s Gold: The Radicals, Con Artists, and Traitors Who Killed the California Dream and Now Threaten Us All 02:13:00 - Retired FBI Special Agent & Criminal Profiler from the Unabomber case, James Fitzgerald, breaks down the FBI investigation into Charlie Kirk's shooter. James is also the author of the book series A Journey to the Center of the Mind 02:25:22 - Sage Steele remembers KirkSee omnystudio.com/listener for privacy information.

Explore shonDynamics: https://shondynamics.deConnect with Martin on LinkedIn: https://www.linkedin.com/in/martin-sonntag-7081a6127/From its early beginnings to a global presence, join CTO of shonDynamics, Martin Sonntag as he shares the story of how shonDynamics was built and scaled over the past years. In this conversation, we explore the company's growth journey, the rapidly evolving EV market in China, and how AI is poised to transform CFD—enabling faster, smarter, and more reliable engineering decisions.

Explore Siemens Simcenter: https://plm.sw.siemens.com/en-US/simcenterConnect with Stephan on LinkedIn: https://www.linkedin.com/in/s-gross/In this episode, Stephan Groß, Technical Marketing Engineer at Siemens, shares his unique journey from working on race car aerodynamics to becoming one of the leading voices in CFD visualization. He explains why scientific visualization is so important for engineers, how storytelling turns raw numbers into powerful insights, and what common mistakes to avoid in post-processing. We also discuss what the future of CFD visualization might bring, including the role of AI, cinematic rendering, and VR in making simulations more accessible and impactful!

Listening toa specific song while eating chocolate makes it taste better. Chilli talks about her in-home sleep study...versus one in clinic. Study finds that Americans borrow $52 billion from friends and family...and leads to strained relationships.CFD...Mariano went on an international first date thru zoom.

CFD sends crew to Outer Banks; local TV station ownership buys out another; CMS prepares for new year with lots of questions

Episode 295: In this episode Vonda and Lori share their takeaways from the SAF Convention—highlighting programs, conversations, and connections that sparked inspiration. From co-presenting alongside industry leader Tim Farrell AIFD, PFCI, AAF, CFD on growing sympathy profits with intention, to navigating questions about grief, empathy, and how to confidently guide families in honoring loved ones, this episode blends heartfelt reflection with practical business strategies. Plus, hear stories from behind the scenes, reminders about the proven emotional power of flowers, and why sharing that message boldly matters more than ever.Sponsored by: Flower CliqueFlower Clique Prep SchoolReal Life Retail Florist

In this conversation, Neil Ashton interviews Prof. Johannes Brandstetter, a physicist turned machine learning expert, about his journey from academia to industry, focusing on the application of machine learning in engineering and computational fluid dynamics (CFD). They discuss the Aurora project, the challenges of integrating machine learning with engineering, and the importance of data in training models. Johannes shares insights on the use of transformers in modeling, the significance of resolution independence, and the role of open-source practices in advancing the field. The conversation also touches on the challenges of founding a startup and the need for multidisciplinary collaboration in tackling complex engineering problems.Links: Github: https://brandstetter-johannes.github.ioEmmi AI: https://www.emmi.aiGoogle scholar: https://scholar.google.com/citations?user=KiRvOHcAAAAJ&hl=deAB-UPT transform paper: https://arxiv.org/abs/2502.09692Chapters00:00 Introduction to Johannes Brandstetter07:10 The Aurora Project and Key Learnings11:15 Machine Learning in Engineering and CFD17:19 Challenges with Mesh Graph Networks20:16 Transformers in Physics Modeling31:14 Tokenization in CFD with Transformers39:58 Challenges in High-Dimensional Meshes41:08 Inference Time and Mesh Generation41:36 Neural Operators and CAD Geometry45:59 Anchor Tokens and Scaling in CFD48:40 Data Dependency and Multi-Fidelity Models50:32 The Role of Physics in Machine Learning54:28 Temporal Modeling in Engineering Simulations56:58 Learning from Temporal Dynamics1:00:58 Stability in Rollout Predictions1:03:48 Multidisciplinary Approaches in Engineering1:05:18 The Startup Journey and Lessons Learned

传统金融世界，正迎来资产代币化和链上时代的变革。2025年7月，传统交易平台Robinhood在欧洲推出股票代币化产品，而加密交易所Kraken也与XStocks合作上线链上股票交易，全球最大的资产管理公司贝莱德（Blackrock）去年已将部分美国国债基金迁移至区块链。在全球资产呈现跨体系、跨时区、跨监管的多方直接竞争态势下，未来资产的定价权与流动性将由谁主导？ 本期《硅谷101》，我们聚焦Robinhood。它打通了股票二级市场与风投一级市场，将传统资产与数字资产纳入同一交易入口。Robinhood的商业模式有何逻辑？股票代币化是金融创新还是监管套利？而万物上链将如何影响全球金融格局，又将往何处去？ 本期节目为《硅谷101 (https://www.xiaoyuzhoufm.com/podcast/5e5c52c9418a84a04625e6cc)》与《Web3 101》串台节目。 【赞助商】 本期节目由开源硬件钱包OneKey赞助播出。硬件钱包是保护加密资产最有效的方式之一。加密世界是黑暗森林，每个人都该为自己的资产负责。物理隔离的硬件钱包，能更好保护助记词不被盗窃。 访问OneKey官网 (https://shop.onekey.so/discount/web3101)购买开源硬件钱包，使用折扣码「web3101」可享受95折优惠。 【主播】 刘锋，Web3 101主理人，BODL Ventures 合伙人，前链闻总编辑 泓君Jane，硅谷101 (https://www.xiaoyuzhoufm.com/podcast/5e5c52c9418a84a04625e6cc)创始人，播客主理人 【嘉宾】 郑迪，前沿科技投资人（知识星球：22136749） 【你将听到】 Robinhood欧洲布局：以CFD切入股票代币化 04:01 两种路径：Robinhood vs XStocks 04:58 证券衍生品：立陶宛MiFID II+收购BitStamp MTF双牌照监管 08:21 “镜像”而非“映射”：类似CFD差价合约，模拟分红收益而非真实股东权益 10:49 代币化股票不可铸造和赎回，不具备稳定币式1:1映射特性 11:26 Arbitrum链上记账：具体信息未披露，为未来1:1映射铺路 卖订单流盈利：加密返点远超股票期权 13:02 “零佣金”Robinhood的核心盈利模式：卖客户订单流（PFOF） 13:35 返点差异巨大：股票0.8BP，期权8BP，加密高达55BP（约股票45倍） 14:23 加密暴利模型：单笔55BP收入=返点+滑点+路由溢价 16:05 战略转型动因：加密交易降温倒逼Robinhood探索股票上链 17:01 Robinhood野心：万物上链后，全资产按加密返点逻辑盈利 监管灰色地带、Robinhood盈利模式与风险 17:57 股票订单流返现多国已禁：欧美等市场对PFOF管控严格，加密仍无监管 20:17 Robinhood风险：一旦暗收费模式纳入监管，加密收入将受冲击 22:06 商业模式的秘密：零佣金表面优惠，但通过买卖价差暗中获利 24:49 PFOF的类投行模式：Robinhood销售+Citadel交易模式 26:25 其他券商模式：Coinbase撮合、eToro对手盘、盈透以利息收入为主 27:22 违反公平，欧盟、英国、新加坡、加拿大、澳大利亚禁止PFOF模式 29:29 PFOF：民主党反对，共和党默许，中期选举决定下一步战略 31:58 山寨币做市商通过返点和滑点，每日“抽血”约480万美元 37:22 二阶段布局：1:1映射代币+链上抵押借贷，但技术和合规细节仍待落实 38:39 为何说xStocks合规风险大 万物上链的金融战争：美国链上霸权的阳谋 43:23 Robinhood或冲击美股交易和传统金融 44:59 美国化债：第一步稳定币，第二步万物上链 47:18 若美国主导链上KYC和白名单，其他国家税源将严重流失 51:42 CFD→STO过渡障碍：主要是合规门槛，而非技术问题 53:15 SEC主席：券法的100多年只有四个项目使用Reg.A发行 垫资池危机：从T+2到实时清结算 54:36 WSB事件回顾：Robinhood因账期与保证金危机被迫暂停交易 57:19 Trump Coin Moonshot危机事件：10亿+美元资金缺口，靠紧急支援化解 59:21 从T+2到链上清算体系引发的交易危机 01:02:53 链上7×24小时交易效率跃升，但多层架构仍限制完全实时 一级半市场重塑定价与风投格局 01:03:33 未上市公司代币化：OpenAI、SpaceX等CFD衍生品可能影响估值与定价 01:06:29 IPO革命：充分流动的一级半市场剥夺投行定价权 01:09:44 风投或受挤压？或被迫转战早期或学习二级博弈 【节目中提到的相关术语】 播客中提到的公司 •Kraken •XStocks •Robinhood •Bybit •Solana •Coinbase •BlackRock •Ondo Finance 交易与监管术语 •PFOF（Payment for Order Flow） •CEX（Centralized Exchange） •DEX（Decentralized Exchange） 国际中央证券托管机构（ICSD） •Euroclear（欧洲清算系统） •Clearstream（清算银行） *【监制】 * 泓君 【后期】 AMEI 【运营】 陈思扬、王梓沁 *【BGM】 * Mumbai - Ooyy Elephanti - Osoku 【在这里找到我们】 收听渠道：Apple Podcast｜Spotify｜YouTube｜小宇宙 联系我们：podcast@sv101.net 【风险声明】 本期节目不构成任何投资建议，投资有风险，入市需谨慎。 本期节目参与者也均不持有Robinhood股票。

In this week's episode of Energy Transition Today, we unpack a turbulent period for offshore wind and renewable energy policy across the world.We begin with Orsted's plan to raise nearly €8 billion to fund its US offshore wind projects after investor pullback and a 30% share price drop, as the company signals plans to scale back in the US.In Estonia, Sumitomo has withdrawn from a joint offshore wind venture in Estonia, citing unclear government support, which casts uncertainty over the project's future.The Dutch government has also reshaped the 2 GW IJmuiden Ver Beta project, delaying its green hydrogen phase and splitting delivery into two stages.There's better news from Romania, where the latest CfD auction awarded 2.75GW of onshore wind and solar with 15-year support.But in Poland, a presidential veto threat could block reforms to ease onshore wind restrictions.We close with France's ongoing delay to its multi-annual energy program, which is stalling major offshore auctions.Across the board, renewable investment is increasingly caught in political crossfire, with shifting policies and investor caution shaping the sector's trajectory.Hosted by:Maya Chavvakula – Head of NewsMathilde Dorbessan – ReporterDan Burge – Commercial Reports LeadReach out to us at: podcasts@inspiratia.comFind all of our latest news and analysis by subscribing to inspiratiaListen to all our episodes on Apple Podcasts, Spotify, and other providers.Music credit: NDA/Show You instrumental/Tribe of NoiseSend us a textReach out to us at: podcasts@inspiratia.comFind all of our latest news and analysis by subscribing to inspiratiaListen to all our episodes on Apple Podcasts, Spotify, and other providers. Music credit: NDA/Show You instrumental/Tribe of Noise©2025 inspiratia. All rights reserved.This content is protected by copyright. Please respect the author's rights and do not copy or reproduce it without permission.

Allen, Joel and Phil discuss Germany's failed offshore wind auction, India's new regulations for domestic wind turbine components, and the need for renewable energy in the US to meet AI data center demands. They also highlight Ohio's efforts to plug abandoned oil and gas wells and feature Quebec's Rivière-du-Moulin as the Wind Farm of the Week. Sign up now for Uptime Tech News, our weekly email update on all things wind technology. This episode is sponsored by Weather Guard Lightning Tech. Learn more about Weather Guard's StrikeTape Wind Turbine LPS retrofit. Follow the show on Facebook, YouTube, Twitter, Linkedin and visit Weather Guard on the web. And subscribe to Rosemary Barnes' YouTube channel here. Have a question we can answer on the show? Email us! You are listening to the Uptime Wind Energy Podcast brought to you by build turbines.com. Learn, train, and be a part of the Clean Energy Revolution. Visit build turbines.com today. Now here's your hosts, Allen Hall, Joel Saxon, Phil Totaro, and Rosemary Barnes.  Allen Hall: Well, welcome to the Uptime Wind Energy Podcast. I'm Allen Hall from the Queen City, Charlotte, North Carolina. Joel Saxum is down in Texas, and Phil Totaro of IntelStor is in Cali. Phil, you had a tsunami alert just recently. Did you see any waves in your neighborhood?  Phil Totaro: No 'cause it didn't actually amount to anything. And that's good, right?  Phil Totaro: It it, have you had tsunami warnings like that in the past? Y yes. And actually more serious ones from earthquakes that are smaller than the 8.8 that was in Russia that caused this one. [00:01:00] Um, but we've had earthquakes off the coast of. California where, you know, they're like four point something or five something, and that actually triggers a tsunami warning that's potentially more serious because of the close proximity. Uh, so we actually developed, uh, in California an early detection and warning system that is triggered, um, you know, mobile phone, uh, alerts and updates based on the, the detection of the P waves from an earthquake.  Allen Hall: What's a P wave? Joel Saxum: P Wave is down, ShearWave is left and right. So sheer wave would be moving this way. P wave would be moving up and down.  Phil Totaro: The P waves, um, are the first indication on, you know, like for the US geological survey, they've got those things that, you know, monitor the, the, um, vibration of the earth or whatever it is that they're monitoring. Um, a P wave will be the first thing triggered when there's an actual earthquake. [00:02:00] That's the thing that happens fast, like super fast, and they can detect it. Anyway, so we've de we've developed an early warning system when, when we have issues and inclusive of, uh, you know, tsunami warnings. But I'm, I'm kind of, you know, 300 feet up, so I have less to worry about.  Allen Hall: It's a good place to be. Well, there's some offshore warnings off the coast of Germany because, uh, they held their latest offshore wind auction. And it was for about two and a half gigawatts of capacity in about 180 square kilometers of water. And they didn't have any bidders at all. Zero bidders and the industry from wind Europe to the, uh, German Offshore Wind Association or, or saying like, yeah, no one's gonna bid on these things because there's too much risk and there's negative bidding, quote unquote negative bidding, which means that you have to. Pay money for the rights [00:03:00] to build out the wind farm and everybody in at least Germany. And when Europe is saying that CFD contract for difference is, is the way to go. And until Germany switches over to a CFD model, you're gonna continue to have no bidders. Now Phil, this is a big problem because Germany is planning to develop a, a. Significant amount of offshore wind gigawatts worth many gigawatts worth by 2030. Is there gonna be a change into the German auction system? Will they move to A 

In this episode of the Neil Ashton podcast, Professor Russell Cummings shares his extensive journey through the fields of aerodynamics, computational fluid dynamics and hypersonics. He discusses his early inspirations, his early days at University and the Hughes Aircraft Company - a key time during this life. He also talks about  the cyclical nature of hypersonics research, and the challenges faced in computational fluid dynamics (CFD). Prof. Cummings emphasizes the importance of perseverance in engineering careers and the need for collaboration between experimental and computational methods. He also shares insights on the role of AI in hypersonics and offers valuable advice for aspiring engineers.Prof. Russ Cummings graduated from California Polytechnic State University (Cal Poly) with a B.S. and M.S. in Aeronautical Engineering, before receiving his Ph.D. in Aerospace Engineering from the University of Southern California; he also received a B.A. in music from Cal Poly. He is currently Professor of Aeronautics at the U.S. Air Force Academy and Director of the Hypersonic Vehicle Simulation Institute. Prior to this he was Professor of Aerospace Engineering at Cal Poly, where he also served as department chairman for four years. He also worked at Hughes Aircraft Company, and completed a National Research Council postdoctoral research fellowship at NASA Ames Research Center, working on the computation of high angle-of-attack flowfields. He is a Fellow of the Royal Aeronautical Society and the American Institute of Aeronautics and Astronautics.Distribution Statement A: approved for public release, PA# USAFA-DF-2025-652. The views expressed in this interview are those of the author and do not necessarily reflect the official policy or position of the United States Air Force Academy, the Air Force, the Department of Defense, or the U.S. Government.LinksAerodynamics for engineers: https://www.cambridge.org/us/universitypress/subjects/engineering/aerospace-engineering/aerodynamics-engineers-7th-edition?format=HB&isbn=9781009501309RAeS Lanchester Named Lecture 2024: Frederick W. Lanchester and 'Aerodynamics' https://www.youtube.com/watch?app=desktop&v=lApNzYaZOmk&t=884s NASA at 50 (Prof Cummings is in the picture): https://images.nasa.gov/details/ARC-1989-AC89-0276-6 Chapters00:00 Introduction to the Podcast and Guest04:56 Professor Russell Cummings: A Journey Through Engineering31:14 The Evolution of Hypersonics Research58:26 The Role of AI in Hypersonics and CFD01:37:55 Advice for Aspiring Engineers

CFD and wind tunnel testing are the backbone of high-performance engineering — but how do they complement each other, and what are the biggest challenges engineers face?In this episode, we sit down with Adrian Villar Collazo, Managing Director at VFluid Advanced Technologies and CTO at Deflect Inc, to explore the aerodynamic simulations, motorsports engineering, and real-world CFD applications. With experience in Formula 1, automotive design, and regulatory consulting for the FIA, Adrian shares insider insights on how precision engineering, data-driven simulations, and experimental validation push performance to the limits.We discuss why wind tunnel testing is still essential despite advances in CFD, how motorsports innovation drives improvements in road car aerodynamics, and what engineers need to consider when optimizing race car performance. Adrian also breaks down common CFD workflow bottlenecks, the challenges of regulation and homologation in competitive motorsports, and how teams can leverage simulation-driven design to gain an edge.VFluid: https://www.vfluid.techAdrian on LinkedIn: https://www.linkedin.com/in/adrian-villar-collazo/

My fellow pro-growth/progress/abundance Up Wingers,The innovation landscape is facing a difficult paradox: Even as R&D investment has increased, productivity per dollar invested is in decline. In his recent co-authored paper, The next innovation revolution—powered by AI, Michael Chui explores AI as a possible solution to this dilemma.Today on Faster, Please! — The Podcast, Chui and I explore the vast potential for AI-augmented research and the challenges and opportunities that come with applying it to the real-world.Chui is a senior fellow at QuantumBlack, McKinsey's AI unit, where he leads McKinsey research in AI, automation, and the future of work.In This Episode* The R&D productivity problem (01:21)* The AI solution (6:13)* The business-adoption bottleneck (11:55)* The man-machine team (18:06)* Are we ready? (19:33)Below is a lightly edited transcript of our conversation. The R&D productivity problem (01:21)All the easy stuff, we already figured out. So the low-hanging fruit has been picked, things are getting harder and harder.Pethokoukis: Do we understand what explains this phenomenon where we seem to be doing lots of science, and we're spending lots of money on R&D, but the actual productivity of that R&D is declining? Do we have a good explanation for that?I don't know if we have just one good explanation. The folks that we both know have been both working on what are the causes of this, as well as what are some of the potential solutions, but I think it's a bit of a hidden problem. I don't think everyone understands that there are a set of people who have looked at this — quite notably Nick Bloom at Stanford who published this somewhat famous paper that some people are familiar with. But it is surprising in some sense.At one level, it's amazing what science and engineering has been able to do. We continue to see these incredible advances, whether it's in AI, or biotechnology, or whatever; but also, what Nick and other researchers have discovered is that we are producing less for every dollar we spend in R&D. That's this little bit of a paradox, or this challenge, that we see. What some of the research we've been trying to do is understand, can AI try to contribute to bending those curves?. . . I'm a computer scientist by training. I love this idea of Moore's Law: Every couple of years you can double the number of transistors you can put on a chip, or whatever, for the same amount of money. There's something called “Eroom's Law,” which is Moore spelled backwards, and basically it said: For decades in the pharmaceutical industry, the number of compounds or drugs you would produce for every billion dollars of R&D would get cut in half every nine years. That's obviously moving in the wrong direction. That challenge, I don't think everyone is aware of, but one that we need to address.I suppose, in a way, it does make sense that as we tackle harder problems, and we climb the tree of knowledge, that it's going to take more time, maybe more researchers, the researchers themselves may have to spend more time in school, so it may be a bit of a hidden problem, but it makes some intuitive sense to me.I think there's a way to think about it that way, which is: All the easy stuff, we already figured out. So the low-hanging fruit has been picked, things are getting harder and harder. It's amazing. You could look at some of the early papers in any field and it have a handful of authors, right? The DNA paper, three authors — although it probably should have included Rosalyn Franklin . . . Now you look at a physics paper or a computer science paper — the author list just goes on sometimes for pages. These problems are harder. They require more and more effort, whether it's people's talents, or whether it's computing power, or large-scale experiments, things are getting harder to do. I think there's ways in which that makes sense. Are there other ways in which we could improve processes? Probably, too.We could invest more in research, make it more efficient, and encourage more people to become researchers. To me, what's more exciting than automating different customer service processes is accelerating scientific discovery. I think that's what makes AI so compelling.That is exactly right. Now, by the way, I think we need to continue to invest in basic research and in science and engineering, I think that's absolutely important, but —That's worth noting, because I'm not sure everybody thinks that, so I'm glad you highlighted that.I don't think AI means that everything becomes cheaper and we don't need to invest in both human talent as well as in research. That's number one.Number two, as you said, we spend a lot of time, and appropriately so, talking about how AI can improve productivity, make things more efficient, do the things that we do already cheaper and faster. I think that's absolutely true. But we had the opportunity to look over history, and what has actually improved the human condition, what has been one of the things that has been necessary to improve the human condition over decades, and centuries, and millennia, is, in fact, discovering new ideas, having scientific breakthroughs, turning those scientific breakthroughs into engineering that turn into products and services, that do everything from expand our lifespans to be able to provide us with food, more energy. All those sorts of things require innovation, require R&D, and what we've discovered is the potential for AI, not only to make things more efficient, but to produce more innovation, more ideas that hopefully will lead to breakthroughs that help us all.The AI solution (6:13)I think that's one of the other potentials of using AI, that it could both absorb some of the experience that people have, as well as stretch the bounds of what might be possible.I've heard described as an “IMI,” it's an invention that makes more invention. It's an invention of a method of invention. That sounds great — how's it going to do that?There are a couple of ways. We looked at three different channels through which AI could improve this process of innovation and R&D. The first one is just increasing the volume, velocity, and variety of different candidates. One way you could think about innovation is you create a whole bunch of candidates and then you filter them down to the ones that might be most effective. Number one, you can just fill that funnel faster, better, and with greater variety. That's number one.The candidates could be a molecule, it could be a drug, it could be a new alloy, it could be lots of things.Absolutely, or a design for a physical product. One of the interesting things is, this quote-unquote “modern AI” — AI's been around for 70 years — is based on foundation models, these large artificial neural networks trained on huge amounts of data, and they produce unstructured outputs. In many cases, language, we talk about LLMs.The interesting thing is, you can train these foundation models not just to generate language, but you can generate a protein, or a drug candidate, as you were saying. You can imagine the prompt being, “Please produce 10 drug candidates that address this condition, but without the following side effects.” That's not exactly how it works, but roughly speaking, that's the potential to generate these things, or generate an electrical circuit, or a design for an air foil or an airframe that has these characteristics. Being able to just generate those.The interesting thing is, not only can you generate them faster, but there's this idea that you can create more variety. We're usefully proud as humans about our creativity, but also, that judgment or that training that we have, that experience sometimes constrains it. The famous example was some folks created this machine called AlphaGo which was meant to compete against the world champion in this game called Go, a very complex strategic game. Famously, it beat the world champion, but one of the things it did is this famous Move 37, this move that everyone who was an expert at Go said, “That is nuts. Why would you possibly do that?” Because the machine was a little bit more unconstrained, actually came up with what you might describe as a creative idea. I think that's one of the other potentials of using AI, that it could both absorb some of the experience that people have, as well as stretch the bounds of what might be possible.So you come up with the design, and then a variety of options, and then AI can help model and test them.Exactly. So you generate a broader and more voluminous set of potential designs, candidates, whether it's molecules, or chemicals, or what have you. Now you need to narrow that down. Traditionally you would narrow it down either one, through physical testing — so put something into a wind tunnel or run it through the water if you're looking at a boat design, or something like that, or put it in an electromagnetic chamber and see how the antenna operates. You'd either test it physically, and then, of course, lots of people figured out how to use physics, mathematical equations, in order to create “digital twins.” So you have these long acronyms like CFD for computational fluid dynamics, basically a virtual wind tunnel, or what have you. Or you have finite element analysis, another way to model how a structure might perform, or computational electromagnetic modeling. All these ways that you can use physics to simulate things, and that's been terrific.But some of those models actually take hours, sometimes days, to run these models. It might be faster than building the physical prototype and then modeling it — again, sometimes you just wait until something breaks, you're doing failure testing. Then you could do that in a computer using these models. But sometimes they take a really long time, and one of the really interesting discoveries in “AI” is you can use that same neural network that we've used to simulate cognition or intelligence, but now you use it to simulate physical systems. So in some ways it's not AI, because you're not creating an artificial intelligence, you're creating an artificial wind tunnel. It's just a different way to model physics. Sometimes these problems get even more complicated . . . If you're trying to put an antenna on an airplane, you need to know how the airflow is going to go over it, but you need to know whether or not the radio frequency stuff works out too, all that RF stuff.So these multiphysics models, the complexity is even higher, and you can train these neural nets . . . even faster than these physics-based models. So we have these things called AI surrogate models. They're sort of surrogates. It's two steps removed, in some ways, from actual physical testing . . . Literally we've seen models that can run in minutes rather than hours, or an hour rather than a few days. That can accelerate things. We see this in weather forecasting in a number of different ways in which this can happen. If you can generate more candidates and then test them faster, you can imagine the whole R&D process really accelerating.The business-adoption bottleneck (11:55)We know that companies are using AI surrogates, deep learning surrogates, already, but is it being applied as many places as possible? No, it isn't.Does achieving your estimated productivity increases depend more on further technological advances or does it depend more on how companies adopt and implement the technology? Is the bottleneck still in the tech itself, or is it more about business adaptation?Mostly number two. The technology is going to continue to advance. As a technologist, I love all that stuff, but as usual, a lot of the challenges here are organizational challenges. We know that companies are using AI surrogates, deep learning surrogates, already, but is it being applied as many places as possible? No, it isn't. A lot of these things are organizational. Does it match your strategy, for instance? Do you have the right talent and organization in place?Let me just give one very specific example. In a lot of R&D organizations we know, there's a separate organization for physical testing and a separate organization for simulations. Simulation, in many cases, us physics-based, but you add these deep-learning surrogates as well. That doesn't make sense at some level. I'm not saying physical testing goes away, but you need to figure out when you should physically test, when you should use which simulation methods, when you should use deep-learning surrogates or AI techniques, et cetera, and that's just one organizational difference that you could make if you were in an organization that was actually taking this whole testing regime seriously, where you're actually parsing out when the optimal amount of physical testing is versus simulation, et cetera. There's a number of things where that's true.Even before AI, historically, there was a gap between novel, new technologies, what they can do in lab settings, and then how they're applied in real-world research or in business environments. That gap, I would guess, probably requires companies to rewire how they operate, which takes time.It is indeed, and it's funny that you use the word “rewiring.” My colleagues wrote a book entitled Rewired, which literally is about the different ways, together, that you need to, as you say, rewire or change the way an organization operates. Only one of those six chapters is around the tech stack. It's still absolutely important. You've got to get all that stuff right. But it is mostly all of the other things surrounding how you change and what organization operates in order to bring the full value of this together to reach scale.We also talk about pilot purgatory: “We did this cool experiment . . .” but when is it good enough that the CFOs talks about it at the quarterly earnings report? That requires the organization to change the way it operates. That's the learning we've seen all the time.We've been serving thousands of executives on their use of AI for seven years now. Nearly 80 percent of organizations say they're regularly using AI someplace in the business, but in a separate survey, only one percent say they're mature in that usage. There's this giant gap between just using AI and then actually having the value be created. And by the way, organizations that are creating that value are accelerating their performance difference. If you have a much more productive R&D organization that churns out products that are successful in the market, you're going to be ahead of your competitors, and that's what we're seeing too.Is there a specific problem that comes up over and over again with companies, either in their implementation of AI, maybe they don't trust it, they may not know how to use it? What do you think is the problem?Unfortunately, I don't think there's just one thing. My colleagues who do this work on Rewired, for instance — you kind of have to do all those things. You do have to have the right talent and organization in place. You have to figure out scaling, for instance. You have to figure out change management. All of those things together are what underpins outsized performance, so all those things have to be done.So if companies are successful, what is the productivity impact you see? We're talking about basically the current technology level, give or take. We're not talking about human-level AI, superintelligence, we're talking about AI more or less as it exists today. Everybody wants to accelerate productivity: governments around the world, companies. So give me a feel for that.There are different measures of productivity, but here what we're talking about is basically: How many new products, successful products, can you put out in the market? Our modeling says, depending on your industry, you could double your productivity, in other words, of R&D. In other words, you could put out double the amount of products and services — new products and services — that you have been previously.Now, that's not true for every industry. By the way, the impact of that is different for different industries because for some industries you are dependent — In pharmaceuticals, the majority of your value comes from producing new products and services over time because eventually the patent runs out or whatever. There are other industries, we talk about science-based industries like chemicals, for instance. The new-product development process in chemicals is very, very close to the science of chemistry. So these levers that I just talked about — producing more candidates, being able to evaluate them more quickly, and all the other things that LLMs can do, in general, we could see potential doubling in the pace of which innovation happens.On the other hand, the chemicals industry — let's leave out specialty chemicals, but the commodity chemicals — they'll still produce ethylene, right? So to a certain extent, while the R&D process can be accelerated a great deal, the EBIT [Earnings Before Interest and Taxes] impact on the industry might be lower than it is for pharmaceuticals, for instance. But still, it's valuable. And then, again, if you're in specialty chem, it means a lot to you. So depending on where you sit in your position in the market, it can vary, but the potential is really high.The man-machine team (18:06)At least for the medium term, we're not going to be able to get rid of all the people. The people are going to be absolutely important to the process.Will future R&D look more like researchers augmented by AI or AI systems assisted by researchers? Who's the assistant in this equation? Who's working for who?It's “all of the above” and it depends on how you decide to use these technologies, but we even write in our paper that we need to be thoughtful about where you put the human in the loop. Every study, the conditions matter, but there are lots of studies where you say, look, the combination of machines and humans — so AI and researchers — is the most powerful combination. Each brings their respective strengths to it, but the funny thing is that sometimes the human biases actually decrease the performance of the overall system, and so, oh, maybe we should just go with machines. At least for the medium term, we're not going to be able to get rid of all the people. The people are going to be absolutely important to the process.When is it that people either are necessary to the process or can be helpful? In many cases, it is around things like, when is it that you need to make a decision that's a safety-critical decision, a regulatory decision where you just have to have a person look at it? That's the sort of necessity argument for people in the loop. But also, there are things that machines just don't do well enough yet, and there's a little bit of that.Are we ready? (19:33). . . AI is one of those things that can produce potentially more of those ideas that can underpin, hopefully, an improved quality of life for us and our children.If we can get more productive R&D, and then businesses get better at incorporating this into their processes and they could potentially generate more products and services, do we have a government ready for that world of accelerated R&D? Can we handle that flow? My bias says probably not, but please correct me if I'm wrong.I think one of the interesting things is people talk about AI regulation. In many of these industries, the regulations already exist. We have regulations for what goes out in pharmaceuticals, for instance. We have regulations in the aviation industry, we have regulations in the automobile industry, and in many ways, AI in the R&D process doesn't change that — maybe it should, people talk about, can you actually accelerate the process of approving a drug, for instance, but that wasn't the thing that we studied. In some ways, those processes are applied now, already, so that's something that doesn't necessarily have to changeThat said, are some of these potential innovations gated by approval processes or clinical trials processes? Absolutely. In some of those cases, the clinical trials process gait is not necessarily a regulation, but we know there's a big problem just finding enough potential subjects in order to do clinical trials. That's not a regulatory problem, that's a problem of finding people who are good candidates for actually testing these drugs.So yes, in some cases, even if we were able to double the amount of candidates that can go through the funnel on a number of these things, there will be these exogenous issues that would constrain society's ability to bring these to market. So that just says, you squeeze the balloon here and it opens up there, but let's go solve each of these problems, and one of the problems that we said that AI can help solve is increasing the number of things that you could potentially put into market if it can get past the other necessities.For a general public where so much of what they're hearing about AI tends to be about job loss, or are they stealing copyrighted material, or, yeah, people talk about these huge advances, but they're not seeing them yet. What is your elevator optimistic pitch why you may be worried about the impact of AI, but here's why I'm excited about it? Why are you excited by it?By the way, I think all those things are really important. All of those concerns, and how do we reskill the workforce, all those things, and we've done work on that as well. But the thing that I'm excited about is we need innovation, we need new ideas, we need scientific advancements, and engineering that turns them into products in order for us to improve their human condition, whether it's living longer lives, or living higher quality life, whether it's having the energy, whether it's to be able to support that in a way that doesn't cause other problems. All of those things, we need to have them, and what we've discovered is AI is one of those things that can produce potentially more of those ideas that can underpin, hopefully, an improved quality of life for us and our children.On sale everywhere The Conservative Futurist: How To Create the Sci-Fi World We Were PromisedMicro Reads▶ Economics* The Tariffs Kicked In. The Sky Didn't Fall. Were the Economists Wrong? - NYT Opinion* AI Disruption Is Coming for These 7 Jobs, Microsoft Says - Barron's* One Way to Ease the US Debt Crisis? Productivity - Bberg Opinion* So far, only one-third of Americans have ever used AI for work - Ars▶ Business* Meta and Microsoft Keep Their License to Spend - WSJ* Meta Pivots on AI Under the Cover of a Superb Quarter - Bberg Opinion* Will Mark Zuckerberg's secret, multibillion-dollar AI plan win over Wall Street? - FT* The AI Company Capitalizing on Our Obsession With Excel - WSJ* $15 billion in NIH funding frozen, then thawed Tuesday in ongoing power war - Ars* Mark Zuckerberg promises you can trust him with superintelligent AI - The Verge* AI Finance App Ramp Is Valued at $22.5 Billion in Funding Round - WSJ▶ Policy/Politics* Trump's Tariff Authority Is Tested in Court as Deadline on Trade Deals Looms - WSJ* China is betting on a real-world use of AI to challenge U.S. control - Wapo▶ AI/Digital* ‘Superintelligence' Will Create a New Era of Empowerment, Mark Zuckerberg Says - NYT* How Exposed Are UK Jobs to Generative AI? Developing and Applying a Novel Task-Based Index - Arxiv* Mark Zuckerberg Details Meta's Plan for Self-Improving, Superintelligent AI - Wired* A Catholic AI app promises answers for the faithful. Can it succeed? - Wapo* Power Hungry: How Ai Will Drive Energy Demand - SSRN* The two people shaping the future of OpenAI's research - MIT* Task-based returns to generative AI: Evidence from a central bank - CEPR▶ Biotech/Health* How to detect consciousness in people, animals and maybe even AI - Nature* Why living in a volatile age may make our brains truly innovative - NS▶ Clean Energy/Climate* The US must return to its roots as a nation of doers - FT* How Trump Rocked EV Charging Startups - Heatmap* Countries Promise Trump to Buy U.S. Gas, and Leave the Details for Later - NYT* Startup begins work on novel US fusion power plant. Yes, fusion. - E&E* Scientists Say New Government Climate Report Twists Their Work - Wired▶ Robotics/Drones/AVs* The grand challenges of learning medical robot autonomy - Science* Coal-Powered AI Robots Are a Dirty Fantasy - Bberg Opinion▶ Up Wing/Down Wing* A Revolutionary Reflection - WSJ Opinion* Why Did the Two Koreas Diverge? - SSRN* The best new science fiction books of August 2025 - NS* As measles spreads, old vaccination canards do too - FT Faster, Please! is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit fasterplease.substack.com/subscribe

Bienvenidos a un nuevo episodio de Desde el Paddock! Esta semana estuvimos en vivo con público para hablar de todo lo que dejó la semana en Formula 1, la previa al GP de Bélgica, la recta final de la temporada en Formula E, lo mejor de NASCAR… y por supuesto, dinámicas con nuestros invitados en el simulador.Gracias a Aeroméxico Rewards por hacer posible este capítulo. Nos emociona anunciar que estarán de regreso con nosotros durante septiembre y octubre para el Gran Premio de México.En las noticias más relevantes de Formula 1, se resetea la escala de testing aerodinámico para el segundo tramo del año. Esto redefine el número de pruebas en túnel de viento y simulaciones CFD para cada equipo. Alpine será uno de los más beneficiados, mientras que Williams sufrirá una fuerte reducción. Pero el debate es más profundo: ¿qué impacto tiene esto realmente cuando todos ya están desarrollando el auto para 2026?Hablamos también del difícil momento de Franco Colapinto con Alpine. El A525 ha sido inconsistente, y su falta de ritmo en carrera lo tiene bajo presión. Mientras medios argentinos aseguran que terminará la temporada, otros ya hablan de una posible sustitución. A esto se suma el problema estructural del motor Alpine, el más débil de la parrilla.Además, analizamos las nuevas llantas de Pirelli para 2026, que se están desarrollando sin un auto físico definitivo. El reto será enorme: simular rendimiento real usando autos "mula" y coordinarse con los equipos para lograr datos confiables de simulador a pista.Antes del GP de Bélgica, platicamos por qué Spa-Francorchamps es la favorita del paddock. Con neumáticos C1, C3 y C4, y condiciones siempre impredecibles, el circuito se convierte en una prueba de gestión, valentía y precisión. Como cada semana, hicimos nuestras predicciones, repasamos datos clave del trazado y enfrentamos al público en dinámicas del simulador.En Formula E, Oliver Rowland se coronó campeón con Nissan dos fechas antes del cierre. Pero la pelea por el subcampeonato está más abierta que nunca entre Pascal Wehrlein, Taylor Barnard, da Costa y Nick Cassidy. A nivel constructores, Porsche lidera con apenas 23 puntos sobre Nissan. Las últimas dos rondas en Londres definirán todo.En NASCAR, Denny Hamlin firmó su cuarta victoria del año en Dover, liderando un doble overtime caótico. Resistió la presión de Chase Briscoe, defendió con neumáticos más gastados y consolidó su lugar como el piloto con más triunfos en la temporada. La lluvia alteró todo: bandera roja de casi una hora, dos reinicios y giros extra que cambiaron el rumbo del campeonato.Chase Elliott, quien lideró la mayor parte de la carrera, terminó sexto pero le bastó para tomar el liderato general, aprovechando el mal día de William Byron. Ty Gibbs cerró el top 5 y se metió a la final del In-Season Challenge. El Monster Mile entregó uno de los capítulos más dramáticos del año.Además, tuvimos dinámicas con el público, enfrentamientos en el simulador y muchas sorpresas más con los mejores fans del automovilismo.¡Agradecemos a todos por participar y asistir a otro capítulo más!Sigue interactuando con nosotros para aparecer en la sección de #PreguntaleAMemo donde tus preguntas serán respondidas por nuestros hosts con análisis directo, claro y al grano.Gracias por ser parte de Desde el Paddock. Recuerda seguirnos en todas nuestras redes para no perderte dinámicas exclusivas, anuncios y contenido que solo compartimos con nuestra comunidad.

In this episode of the Neil Ashton podcast, Professor Mike Giles shares his extensive journey through the fields of computational fluid dynamics (CFD), computational finance and HPC. He discusses his early academic influences, his early days at Cambridge, internships at Rolls-Royce, his transition to MIT and Oxford where he made significant contributions to high-performance computing and numerical analysis. The conversation highlights his hands-on approach to research and teaching, as well as his pioneering work in Monte Carlo methods and GPU computing. This conversation explores the journey of a mathematician and engineer from MIT to Rolls-Royce and then to Oxford, highlighting the evolution of computational engineering, the development of the Hydra code, and the transition from CFD to financial applications.  In this conversation, the speaker reflects on their journey through burnout, career transitions, and the evolution of their work in computational finance and numerical analysis. They discuss the challenges of managing large software projects, the shift from Hydra code development to finance, and the integration of advanced methodologies in their work. The conversation also touches on the role of high-performance computing, the impact of AI on research, and advice for the next generation of students pursuing careers in mathematics and programming.Links:https://people.maths.ox.ac.uk/gilesm/Chapters00:00 Introduction 06:25 Professor Mike Giles: A Journey Through CFD and Finance17:30 Early Academic Influences and Career Path29:34 Transition to MIT and Early Research40:01 High-Performance Computing and Its Impact41:30 Navigating Between MIT and Rolls-Royce44:54 The Evolution of Research at MIT48:47 Transitioning to Oxford and the Role of Rolls-Royce51:07 The Genesis of the Hydra Code01:00:47 The Role of Conferences in Engineering01:10:58 The Shift from CFD to Financial Applications01:21:30 Navigating Burnout and Career Transitions01:24:04 Shifting Focus: From Hydrocode to Computational Finance01:29:30 Bridging Mathematics and Finance: Methodologies and Techniques01:35:09 The Role of High-Performance Computing in Modern Research01:39:20 AI's Impact on Research and Future Directions01:54:00 Advice for the Next Generation: Pursuing Passion and Skills

Stocks Trading Prop Firm: Tips From The Founde In episode 515 of the Desire To Trade Podcast, Etienne sits down with Michael Katz from TradeThePool to discuss how their platform is changing the game for stock traders. Michael shares insights on limited-risk trading, the advantages of prop firms over traditional brokers, and why their approach helps traders succeed without risking personal capital. They dive into scaling strategies, the psychology of trading, and why stocks offer unique opportunities compared to Forex or futures. If you've ever wondered how to trade with more confidence and less risk, this conversation is packed with practical takeaways. The video is also available for you to watch on YouTube. >> Watch the video recording! >Get funded to trade stocks (by Trade The Pool) Topics Covered In This Episode 00:30 Who is Michael Katz and what is @tradethepool 01:30 Why stock trading prop firms are rare and TradeThePool's edge 02:31 The difference between CFD and direct Stocks Trading 03:35 What funded traders do different to failing traders 05:24 Why "No Time Limit" evaluations benefit traders 06:59 Flex vs. Max accounts: Which one suits your trading style? 08:15 Transitioning from Forex to stocks: Education and opportunities 09:38 Why you should also trade stocks as a Forex Trader 11:01 Scaling funded accounts and managing multiple strategies 14:04 Risk management: How to avoid blowing evaluation accounts 16:46 What type of strategies get funded more often 17:35 Average time to pass evaluations and trader success stories 18:39 The future of TradeThePool and the prop trading industry 21:30 How should prop firms differentiate for success 22:57 Where to connect with Michael and try TradeThePool (Link Below) What did you like best in this podcast episode? Let's talk in the comments below, or join me in the Facebook group! Desire To Trade's Top Resources DesireToTRADE Forex Trader Community (free group!) Complete Price Action Strategy Checklist One-Page Trading Plan (free template) Recommended brokers: EightCap (preferred Crypto and FX Broker) AxiTrader (use our link to get a special bonus) Desire To TRADE Academy Get a copy of Prop Trading Secrets (Author: Kathy Lien & Etienne Crete) About The Desire To Trade Podcast Subscribe via iTunes (take 2 seconds and leave the podcast a review!) Subscribe via Stitcher Subscribe via TuneIn Subscribe via Google Play See all podcast episodes What one thing will you implement after listening to this podcast episode? Leave a comment below, or join me in the Facebook group! How to find Michael Katz Get funded to trade stocks (by Trade The Pool) Email Michael What one thing will you implement after listening to this podcast episode? Leave a comment below, or join me in the Facebook group!

Welcome to The Chopping Block – where crypto insiders Haseeb Qureshi, Tom Schmidt, Tarun Chitra, and Robert Leshner chop it up about the latest in crypto. This week, we're joined by Jon Charbonneau and Ryan Watkins to unpack the bombshell news of Robinhood Chain—an Arbitrum-based network debuting tokenized U.S. stocks, 3× crypto perps, and that head-scratching $500 K liquidity cap. From riffing on whether proof-of-stake yields are just “money in a box,” to debating Solana's first U.S. staked ETF, to sizing up the looming perp wars between Robinhood and Coinbase, the crew maps a common thread: corporate chains and regulatory work-arounds are colliding with crypto's decentralization ideals, forcing builders, traders, and even ETF hawks to rethink where real security, fairness, and opportunity will live next. Show highlights

You can go a long way with club-level aero — and this is how to do it.On this week's episode of Tuned In, ex-Mercedes F1 aerodynamicist and brand new HPA tutor Kyle Forster helps you find big gains in performance by adding aero.

"Certainly an exciting time for data centers, private and public alike, isn't it?" This opening remark from Tom Croll of Lionfish Tech Advisors set the stage for a compelling discussion with Ryan Mallory, President and COO of Flexential, on the recent episode of the Tech Transformed podcast. The speakers discuss the current AI scenario's impact on data centers, high-density computing, and cloud infrastructure. This is where Flexential comes in. Mallory stresses the importance of trust and verification in AI deployment, especially regarding security and data privacy, which Flexential has established a reputation for.“How to adapt to the AI boom?” is one question everyone's asking, Mallory says. From a service provider perspective, it's a "proverbial gold rush" for powered land. This is essential for building the relevant AI infrastructure that will serve as early entry points. Flexential's survey reveals that a staggering "90% of people surveyed are contemplating an AI strategy." The number spotlights the widespread interest and impending demand. “This isn't a short-term trend,” says Mallory. He also projects a "12-year" development cycle for AI infrastructure, emphasizing the long-term commitment required from the industry.Scaling Up for AIThe unprecedented growth in AI demands specialized infrastructure, especially concerning the sustainable use of AI and running data centers, and strong strategies for scalability, reliability, and cost-effectiveness. Flexential is uniquely positioned to meet this challenge. "We've been developing high-performance compute facilities for over 10 years," he states. Their "Gen 4 and Gen 5 sites can cool 50 kilowatts per cabinet air-cooled." This information has allowed them to readily support the requirements of H100 and H200 type deployments, not just for service providers, but also for ramping deployments in the healthcare and financial sectors.Looking ahead, the data center industry is preparing for even higher-density racks and the widespread adoption of liquid cooling. While "all of our sites are liquid-cooled ready," Mallory says, thorough airflow studies and CFD analysis show liquid cooling is genuinely necessary. Flexential's air-cooled solutions are already handling "high-dense pods for some of the companies that have recently gone public and other companies that are out there that you hear about in this AI service provider realm,” Mallory added. Takeaways90% of surveyed companies are considering an AI strategy.The AI industry is experiencing a gold rush for infrastructure.Data centers must adapt to high-density computing demands.Liquid cooling is essential for high-performance AI deployments.AI regulations are shaping how data centers operate.Trust but verify is crucial for AI deployment.AI democratization is vital for businesses of all sizes.Flexential is focused on providing scalable AI infrastructure.Security policies are essential for protecting sensitive data.AI can enhance productivity, but it requires human oversight.Chapters00:00 The Impact of AI on Data Centers02:51 Infrastructure Challenges and Solutions05:59 Navigating AI Regulations and Security08:59 Democratization of AI for...

Send us a textOccamsracers.com ... where you need to go to find the actual report we talked about in this podcast... Mario Korf joins me to talk about the process, content, and the wind tunnel/CFD relationship in this episode! If you like what you hear... share the podcast or go to buymeacoffee.com/theblindapexpodcastSupport the show

Gary Booysen from Rand Swiss on choosing a CFD broker amid a major broker's exit from SA. Keith McLachlan of Element Investment Managers discusses Santova's results and acquisitions. Zikona Poswayo from Standard Bank introduces two new structured products focused on China and gold miners.

We often chase engine and tuning upgrades first, but could a front splitter and rear wing be a smarter starting point for our race cars?We caught up with Kyle Forster from JKF Aero to break down how aerodynamics work in practice and how to make effective improvements at every level of motorsport. From the priorities of downforce vs drag, to choosing the right aero balance for your car's drivetrain layout, this conversation covers everything from tuft testing a club racer to CFD and F1-style development cycles, noting Kyle was an aerodynamicist for the Mercedes Formula 1 team during their hybrid era peak.Use ‘PODCAST75' for $75 off your first HPA course here: https://hpcdmy.co/hpa-tuned-inKyle explains key tuning strategies using splitters, wings, rake, and gurney flaps, plus the difference between 2D and 3D wing profiles and how things like swan neck mounts and dual elements can drastically improve efficiency and downforce. He also clarifies some common misconceptions about turbulent flow, stalling, and the practical implications of end plate design, big and small.Practical advice is given for grassroots racers, including the use of tufts or strong coast-down testing, and why stopwatch and driver feedback still matter. At the professional level, Kyle explains how CFD, wind tunnel testing, and track validation work together in a continuous development loop for professional motorsport including Formula 1 car development.So, where are the biggest gains to be had for a club racer? As you might have guessed, front splitters and rear wings. Get them on the car and develop over time from there, forgetting about flat floors and rear diffusers until further down the line is Kyles advice.Whether you're trying to gain lap time at your local time attack event or you're part of a pro-level development team, this video gives valuable insight into how to build aero that works. To see more of Kyle's work, check out JKF Aero at jkfaero.com or his YouTube channel ‪@KYLEENGINEERS‬.

The machine powering the transformation of German surfing is an Endless Surf 34 caisson wave pool, or ES34 to those in the know. To bring this beast to life, much of the heavy design and programming was done by the talented hands of Clément Ginestet and Axel Terradillos. WavePoolMag wanted to know how the dynamic duo dealt with the stress of bringing a multi-million dollar project to life, as well as how the process of designing a wave pool works. We know that engineers live and breathe CFD models, but what about those little cosmic surprises that occur when the randomness of the universe shows up unexpectedly? In this conversation, Clem and Axel allow us a unique view into the nailbiting debut of the first Endless Surf wave pool.

In this mailbag episode, Brad and Rachael dive deep into strategies for efficiently withdrawing money from taxable brokerage and retirement accounts. With a focus on understanding the different tax treatments associated with these accounts, listeners gain crucial insights into managing tax liabilities for retirement. Key Takeaways Different Types of Accounts: Taxable brokerage accounts versus traditional IRAs and 401ks have distinct tax consequences affecting retirees. Tax Treatment: Withdrawals from traditional retirement accounts are taxed as ordinary income, while long-term capital gains from taxable accounts are taxed at a lower rate. Strategic Tax Planning: Employing strategies such as Roth conversions and tax gain harvesting can significantly minimize tax impacts during retirement. Investment Placement: It's vital to manage tax-efficient placements for investments, especially during retirement. Timestamps 00:00:00 - Podcast Intro: Introduction to the episode topic. 00:04:36 - Taxable Brokerage Accounts vs Traditional Accounts: Discussion on the terminology and tax implications. 00:09:59 - Tax Strategies and Opportunities: How to minimize taxes in retirement using investments. 00:23:10 - Roth Conversions Explained: Understanding the benefits of converting retirement accounts. 00:48:13 - Conclusion and Future Topics: Wrap up and upcoming episode topics. Key Insights Tax Treatment of Withdrawals: Withdrawals from a traditional IRA are taxed as ordinary income. (00:04:36) Understanding Taxable Brokerage Accounts: "Taxable brokerage accounts" may be better understood as your basic savings or investment accounts. (00:05:07) Investment Strategies: Use tax-advantaged accounts to defer taxes on income. (00:09:59) Minimize taxes with proper investment placements and strategies like tax gain harvesting. (00:23:10) Roth Conversions: Roth conversions allow you to transfer pre-tax retirement accounts into a Roth IRA and pay taxes on the converted amount, providing tax benefits later. (00:26:56) Actionable Takeaways Understand Account Types: Familiarize yourself with the differences in tax treatment between taxable brokerage accounts and traditional retirement accounts. (00:04:36) Maximize Tax Efficiency: Consider implementing Roth conversions to streamline taxes during retirement. (00:26:56) Tax-Efficient Investments: Be strategic about investment placements—opt for tax-efficient funds to minimize taxable income. (00:23:10) Related Resources Kitcis Article on IRA Strategies: Read here (00:52:55)   Rachael Camp   Please note: Rachael Camp offers advisory Services through Creative Financial Designs, Inc., a Registered Investment Adviser, and Securities are offered through cfd Investments, Inc., a Registered Broker/Dealer, Member FINRA & SIPC, 2704 S. Goyer Rd., Kokomo, IN 46902. 765-453-9600. Camp Wealth is not affiliated with the CFD companies.

Welcome back to another episode of Crawfordsville Connection! This week we are joined by Crawfordsville Fire Department Captain Bryan Shaw to talk about CFD's Whole Blood Program an its importance in saving lives in our community. One way to support this program's success is by donating blood!  Sign up to donate blood here: https://donateblood.versiti.org/donor/schedules/zip  Yodel Community Calendar & News Feed: https://events.yodel.today/crawfordsville  To ask any questions about this podcast or to submit topic ideas, please email Sarah Sommer at ssommer@crawfordsville-in.gov