Nora Szentivanyi is joined by Greg Fuzesi and Michael Hanson to discuss the key takeaways from our latest Global Inflation Monitor and inflation risks stemming from higher tariffs . While there are reasons to fade elements of the January upside inflation surprise, global core inflation remains stuck at a 3% pace and we have nudged our 1Q25 forecast upward to 3.4%ar. Moreover, headline inflation has firmed to a 3.7%ar over the past three months after a slide to 2.6%ar over the prior six months. Tariffs are likely to add to inflation in the near-term, but medium-term inflation pressures should tilt lower due to the associated drags on sentiment.  Euro area underlying inflation remains on track to moderate to 2% as weak demand looks to be weighing on corporate pricing power, while declining wage inflation fades cost pressures. US inflation appears moderately more sticky and a recent pop in some measures of inflation expectations point to a more gradual pace of disinflation. 

This podcast was recorded on March 04, 2025.

This communication is provided for information purposes only.  Institutional clients can view the related report at https://www.jpmm.com/research/content/GPS-4920790-0 ,  https://www.jpmm.com/research/content/GPS-4921610-0 , https://www.jpmm.com/research/content/GPS-4925120-0 for more information; please visit www.jpmm.com/research/disclosures for important disclosures.

© 2025 JPMorgan Chase & Co. All rights reserved. This material or any portion hereof may not be reprinted, sold or redistributed without the written consent of J.P. Morgan. It is strictly prohibited to use or share without prior written consent from J.P. Morgan any research material received from J.P. Morgan or an authorized third-party (“J.P. Morgan Data”) in any third-party artificial intelligence (“AI”) systems or models when such J.P. Morgan Data is accessible by a third-party. It is permissible to use J.P. Morgan Data for internal business purposes only in an AI system or model that protects the confidentiality of J.P. Morgan Data so as to prevent any and all access to or use of such J.P. Morgan Data by any third-party.

A powerful discussion with AI experts on how to thrive in the AI industry, upskill, and build impactful careers.

My semi-regular co-host and bestie Carly Taylor joins me once again. This time we chat about the true cost of replacing engineers with AI. We explore the implications of mass layoffs, the importance of company culture, and the potential for burnout among tech workers.

The rapid expansion of data centers is reshaping the industry, requiring new approaches to design, safety, and leadership. 

We’re excited to have Doug Mouton, former Senior Eng Lead, Datacenter Design Engineering and Construction at Meta, as a guest on this latest episode of the “Data Center Revolution” podcast. Doug joins us with key insights into leadership, adaptability, and the evolution of hyperscale data-center construction. He also shares his journey from military service to leading large-scale infrastructure projects in the data center industry, highlighting key transferable skills along the way. 

Key Takeaways:

(07:54) Military mindset builds strong leaders. (14:25) Veterans thrive in high-pressure environments. (25:32) Katrina exposed disaster preparedness gaps. (35:16) Microsoft shifted to cost-effective data center designs. (43:56) Data centers face growing energy challenges. (54:26) Safety-first culture boosts efficiency and morale. (01:21:43) Data centers must transition to hybrid cooling solutions. (01:42:09) AI needs ethical guardrails.

Resources Mentioned:

Fidelis New Energy | Website - https://www.fidelisinfra.com

Microsoft Azure - https://azure.microsoft.com/en-us/

Meta - https://about.meta.com/

Jacobs - https://www.jacobs.com/

National Guard - https://nationalguard.com/

Jones Lang LaSalle - https://www.us.jll.com/

Thank you for listening to “Data Center Revolution.” Don’t forget to leave us a review and subscribe so you don’t miss an episode.   To learn more about Overwatch, visit us at https://linktr.ee/overwatchmissioncritical 

DataCenterIndustry #NuclearEnergy #FutureOfDataCenters #AI

In this episode, I uncover the nine biggest LIES about landing a data job. Maybe what's stopping you from pursuing a data career is just a big lie. No College Degree As A Data Analyst YT Playlist: https://www.youtube.com/playlist?list=PLo0oTKi2fPNjHi6iXT3Pu68kUmiT-xDWs Don’t Learn Python as a Data Analyst (Learn This Instead): https://www.youtube.com/watch?v=VVhURHXMSlA 💌 Join 10k+ aspiring data analysts & get my tips in your inbox weekly 👉 https://www.datacareerjumpstart.com/newsletter 🆘 Feeling stuck in your data journey? Come to my next free "How to Land Your First Data Job" training 👉 https://www.datacareerjumpstart.com/training 👩‍💻 Want to land a data job in less than 90 days? 👉 https://www.datacareerjumpstart.com/daa 👔 Ace The Interview with Confidence 👉 https://www.datacareerjumpstart.com/interviewsimulator ⌚ TIMESTAMPS 00:00 Introduction 00:05 You Need a Computer Science or Math Degree 01:20 You Have to Be Good at Math and Statistics 03:00 You Must Know Everything About Data Analytics 04:27 Certifications Matter 05:35 Skills Are Enough 07:20 AI Will Take Your Job 09:24 You'll Spend 80% of Your Time Cleaning Data 10:08 Data Titles 11:44 There Are Lots of Remote Jobs 13:17 The "Self-Taught" Data Analyst 🔗 CONNECT WITH AVERY 🎥 YouTube Channel: https://www.youtube.com/@averysmith 🤝 LinkedIn: https://www.linkedin.com/in/averyjsmith/ 📸 Instagram: https://instagram.com/datacareerjumpstart 🎵 TikTok: https://www.tiktok.com/@verydata 💻 Website: https://www.datacareerjumpstart.com/ Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!

To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more

If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.

👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa

In celebration of International Women's Day, this episode of Analytics Power Hour features an all-female crew discussing the challenges and opportunities in AI projects. Moe Kiss, Julie Hoyer and Val Kroll, dive into this AI topic with guest expert, Kathleen Walch, who co-developed the CPMAI methodology and the seven patterns of AI (super helpful for your AI use cases!). Kathleen has helpful frameworks and colorful examples to illustrate the importance of setting expectations upfront with all stakeholders and clearly defining what problem you are trying to solve. Her stories are born from the painful experiences of AI projects being run like application development projects instead of the data projects that they are! Tune in to hear her advice for getting your organization to adopt a data-centric methodology for running your AI projects—you'll be happier than a camera spotting wolves in the snow! 🐺❄️🎥 For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Michael Hanson and Murat Tasci, of the US Economics team, discuss their latest Research Note on the challenges for meeting the many disparate objectives of the Trump tariffs, and what that might mean for tariff revenues.

Speakers:

Michael Hanson, Senior US and Canadian Economist Murat Tasci, Senior US Economist

This podcast was recorded on March 3, 2025.

This communication is provided for information purposes only. Institutional clients can view the related report at https://www.jpmm.com/research/content/GPS-4921610-0 for more information; please visit www.jpmm.com/research/disclosures for important disclosures. © 2025 JPMorgan Chase & Co. All rights reserved. This material or any portion hereof may not be reprinted, sold or redistributed without the written consent of J.P. Morgan. It is strictly prohibited to use or share without prior written consent from J.P. Morgan any research material received from J.P. Morgan or an authorized third-party (“J.P. Morgan Data”) in any third-party artificial intelligence (“AI”) systems or models when such J.P. Morgan Data is accessible by a third-party. It is permissible to use J.P. Morgan Data for internal business purposes only in an AI system or model that protects the confidentiality of J.P. Morgan Data so as to prevent any and all access to or use of such J.P. Morgan Data by any third-party.

Generative AI has transformed the financial services sector, sparking interest at all organizational levels. As AI becomes more accessible, professionals are exploring its potential to enhance their work. How can AI tools improve personalization and fraud detection? What efficiencies can be gained in product development and internal processes? These are the questions driving the adoption of AI as companies strive to innovate responsibly while maximizing value. Andrew serves as the Chief Data Officer for Mastercard, leading the organization’s data strategy and innovation efforts while navigating current and future data risks. Andrews's prior roles at Mastercard include Senior Vice President, Data Management, in which he was responsible for the quality, collection, and use of data for Mastercard’s information services and advisory business, and Mastercard’s Deputy Chief Privacy Officer, in which he was responsible for privacy and data protection issues globally for Mastercard. Andrew also spent many years as a Privacy & Intellectual Property Council advising direct marketing services, interactive advertising, and industrial chemicals industries. Andrew holds Juris Doctor from Columbia University School of Law and has his bachelor’s degree, cum laude, in Chemical Engineering from the University of Delaware. Andrew is a retired member of the State Bar of New York. In the episode, Adel and Andrew explore GenAI's transformative impact on financial services, the democratization of AI tools, efficiency gains in product development, the importance of AI governance and data quality, the cultural shifts and regulatory landscapes shaping AI's future, and much more. Links Mentioned in the Show: MastercardConnect with AndrewSkill Track: Artificial Intelligence (AI) LeadershipRelated Episode: How Generative AI is Changing Leadership with Christie Smith, Founder of the Humanity Institute and Kelly Monahan, Managing Director, Research InstituteSign up to attend RADAR: Skills Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

We see more momentum loss in the data and question how much is noise and how much is signal; we also question what that signal is if any. This then sets the foundation for assessing the risks related to the multitude of US policy risks on the horizon.

Speakers:

Bruce Kasman

Joseph Lupton

This podcast was recorded on 28 February 2025.

This communication is provided for information purposes only. Institutional clients please visit www.jpmm.com/research/disclosures for important disclosures. © 2025 JPMorgan Chase & Co. All rights reserved. This material or any portion hereof may not be reprinted, sold or redistributed without the written consent of J.P. Morgan. It is strictly prohibited to use or share without prior written consent from J.P. Morgan any research material received from J.P. Morgan or an authorized third-party (“J.P. Morgan Data”) in any third-party artificial intelligence (“AI”) systems or models when such J.P. Morgan Data is accessible by a third-party. It is permissible to use J.P. Morgan Data for internal business purposes only in an AI system or model that protects the confidentiality of J.P. Morgan Data so as to prevent any and all access to or use of such J.P. Morgan Data by any third-party.

How can businesses align AI with their values? How does decentralized data impact industries from healthcare to autonomous driving? In this episode of Data Unchained we sit down with Michael Hemenway, a Data Science Consultant, to discuss AI ethics, governance, and the future of responsible technology adoption.

AI #EthicalAI #DataScience #MachineLearning #ArtificialIntelligence #DataUnchained #TechPodcast #CIO #CTO #DecentralizedData #Governance #DeepLearning #BusinessStrategy #FutureTech

Cyberpunk by jiglr | https://soundcloud.com/jiglrmusic Music promoted by https://www.free-stock-music.com Creative Commons Attribution 3.0 Unported License https://creativecommons.org/licenses/by/3.0/deed.en_US Hosted on Acast. See acast.com/privacy for more information.

In this episode, we explore how microgravity affects muscle structure and function, using Caenorhabditis elegans as a model organism. Spaceflight-induced muscle atrophy is a major challenge for astronauts, and understanding the molecular and genetic mechanisms behind these changes is key to developing countermeasures.

This discussion is based on the review article: “Advancing Insights into Microgravity-Induced Muscle Changes Using Caenorhabditis elegans as a Model Organism” Beckett LJ, Williams PM, Toh LS, Hessel V, Gerstweiler L, Fisk I, Toronjo-Urquiza L, Chauhan VM. Published in npj Microgravity (2024). 📖 Read the full paper: ⁠https://doi.org/10.1038/s41526-024-00418-z⁠

🔬 Learn how C. elegans provides unique insights into metabolic changes, gene expression, and protein regulation during spaceflight, offering potential strategies to counteract muscle degradation.

🌍 Follow for more research-based discussions on nematodes, space biology, and biomedical science.

This podcast is generated with artificial intelligence and curated by Veeren. If you’d like your publication featured on the show, please get in touch.

📩 More info: 🔗 www.veerenchauhan.com 📧 [email protected]

Send us a text Welcome to the cozy corner of the tech world where ones and zeros mingle with casual chit-chat. Datatopics Unplugged is your go-to spot for relaxed discussions around tech, news, data, and society. This week, we dive into the latest in AI-assisted coding, software quality, and the ongoing debate on whether LLMs will replace developers—or just make their lives easier: My LLM Codegen workflow atm: A deep dive into using LLMs for coding, including structured workflows, tool recommendations, and the fine line between automation and chaos.Cline & Cursor: Exploring VSCode extensions and AI-powered coding tools that aim to supercharge development—but are they game-changers or just fancy autocomplete?To avoid being replaced by LLMs, do what they can’t: A thought-provoking take on the future of programming, the value of human intuition, and how to stay ahead in an AI-driven world.The wired brain: Why we should stop using glowing-brain stock images to talk about AI—and what that says about how we understand machine intelligence.A year of uv: Reflecting on a year of UV, the rising star of Python package managers. Should you switch? Maybe. Probably.Posting: A look at a fun GitHub project that makes sharing online a little more structured.Software Quality: AI may generate code, but does it generate good code? A discussion on testing, maintainability, and avoiding spaghetti.movingWithTheTimes: A bit of programmer humor to lighten the mood—because tech discussions need memes too.

As businesses collect more data than ever, the question arises: is bigger always better? Companies are beginning to question whether massive datasets and complex infrastructures are truly delivering results or just adding unnecessary costs. How can you align your data strategy with your actual needs? Could focusing on smaller, more manageable datasets improve efficiency and save resources while still delivering valuable insights? Dr. Madelaine Daianu is the Head of Data & AI at Credit Karma, Inc. Before joining the company in June 2023, she served as Head of Data and Pricing at Belong Home, Inc. Earlier in her career, Daianu has held numerous senior roles in data science and machine learning at The RealReal, Facebook, and Intuit. Daianu earned a Bachelor of Applied Science in Bioengineering and Mathematics from the University of Illinois at Chicago and a Ph.D. in Bioengineering and Biomedical Engineering from the University of California, Los Angeles. In the episode, Richie and Madelaine explore generative AI applications at Credit Karma, the importance of data infrastructure, the role of explainability in fintech, strategies for scaling AI processes, and much more. Links Mentioned in the Show: Credit KarmaConnect with MaddieSkill Track: AI Business FundamentalsRelated Episode: Effective Product Management for AI with Marily Nika, Gen AI Product Lead at Google AssistantSign up to attend RADAR: Skills Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Nicolaie, Katie, Gbolahan and Steven debate exposures across EM Edge from policy actions taken by the Trump administration around FDI, trade and aid flows. In addition, they discuss an impending review of US membership to international organizations, which could encompass the World Bank and IMF, and how that could impact the EM Edge.

Speakers: Katherine Marney, Emerging Markets Economic and Policy Research  Nicolaie Alexandru, EM, Economic and Policy Research Steven Palacio, EM, Economics Research Gbolahan S Taiwo, EM, Economic and Policy Research

This podcast was recorded on 26 February 2025.

This communication is provided for information purposes only. Institutional clients can view the related report at https://www.jpmm.com/research/content/GPS-4910014-0, https://www.jpmm.com/research/content/GPS-4906578-0, https://www.jpmm.com/research/content/GPS-4910054-0, https://www.jpmm.com/research/content/GPS-4920549-0 for more information; please visit www.jpmm.com/research/disclosures for important disclosures. © 2025 JPMorgan Chase & Co. All rights reserved. This material or any portion hereof may not be reprinted, sold or redistributed without the written consent of J.P. Morgan. It is strictly prohibited to use or share without prior written consent from J.P. Morgan any research material received from J.P. Morgan or an authorized third-party (“J.P. Morgan Data”) in any third-party artificial intelligence (“AI”) systems or models when such J.P. Morgan Data is accessible by a third-party. It is permissible to use J.P. Morgan Data for internal business purposes only in an AI system or model that protects the confidentiality of J.P. Morgan Data so as to prevent any and all access to or use of such J.P. Morgan Data by any third-party.

Supported by Our Partners • WorkOS — The modern identity platform for B2B SaaS. • Graphite — The AI developer productivity platform.  • Formation — Level up your career and compensation with Formation. — In today’s episode of The Pragmatic Engineer, I am joined by a senior software engineer and cartoonist, Manu Cornet. Manu spent over a decade at Google, doing both backend and frontend development. He also spent a year and a half at Twitter before Elon Musk purchased it and rebranded it to X. But what Manu is most known for are his hilarious internet comics about the tech world, including his famous org chart comic from 2011 about Facebook, Apple, Amazon, and Microsoft. In today’s conversation, we explore many of his comics, discuss the meaning behind them, and talk about the following topics:  • The viral org chart comic that captured the structure of Big Tech companies • Why Google is notorious for confusing product names • The comic that ended up on every door at Google • How Google’s 20% time fostered innovation—and what projects came from it • How one of Manu’s comics predicted Google Stadia’s failure—and the reasons behind it • The value of connecting to users directly  • Twitter’s climate before and after Elon Musk’s acquisition and the mass layoffs that followed • And more! — Timestamps (00:00) Intro (02:01) Manu’s org structure comic  (07:10) Manu’s “Who Sues Who” comic (09:15) Google vs. Amazon comic (14:10) Confusing names at Google (20:00) Different approaches to sharing information within companies (22:20) The two ways of doing things at Google (25:15) Manu’s code reviews comic (27:45) The comic that was printed on every single door of Google (30:55) An explanation of 20% at Google (36:00) Gmail Labs and Google Stadia (41:36) Manu’s time at Twitter and the threat of Elon Musk buying (47:07) How Manu helped Gergely with a bug on Twitter (49:05) Musk’s acquirement of Twitter and the resulting layoffs (59:00) Manu’s comic about his disillusionment with Twitter and Google (1:02:37) Rapid fire round — The Pragmatic Engineer deepdives relevant for this episode: • How Manu creates comics • Consolidating technologies • Is Big Tech becoming more cutthroat? — See the transcript and other references from the episode at ⁠⁠https://newsletter.pragmaticengineer.com/podcast⁠⁠ — Production and marketing by ⁠⁠⁠⁠⁠⁠⁠⁠https://penname.co/⁠⁠⁠⁠⁠⁠⁠⁠. For inquiries about sponsoring the podcast, email [email protected].

Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe

Está no ar, o Data Hackers News !! Os assuntos mais quentes da semana, com as principais notícias da área de Dados, IA e Tecnologia, que você também encontra na nossa Newsletter semanal, agora no Podcast do Data Hackers !! Aperte o play e ouça agora, o Data Hackers News dessa semana ! Para saber tudo sobre o que está acontecendo na área de dados, se inscreva na Newsletter semanal: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.datahackers.news/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Conheça nossos comentaristas do Data Hackers News: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Monique Femme⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Paulo Vasconcellos ⁠Matérias/assuntos comentados: Meta cria IA capaz de ler a mente; Spotify vai permitir audiobooks narrados por IA Demais canais do Data Hackers: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Site⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Linkedin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tik Tok⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠You Tube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Send us a text In this special replay episode of Making Data Simple, Al Martin sits down with Matt Cowell, CEO of QuantHub, to dive deep into data literacy, upskilling, and solving learning challenges. Matt shares his expertise on defining data fluency, the best ways to learn, and how organizations can close the data skill gap. From client use cases to leadership insights, this episode is packed with valuable takeaways for businesses and individuals navigating the data-driven world. Show Notes & Chapter Markers: ⏳ 2:25 – From SVP of Products to Data Learning Business 📊 3:48 – Defining Data Literacy 🎓 5:50 – Teaching the Products 🚧 7:36 – What’s Out of Scope? 🏢 12:50 – Client Use Case 💡 18:07 – Solving Learning Problems 📖 21:14 – What Does a Learning Plan Look Like? 🔍 25:08 – Defining Micro 🧠 30:20 – Best Ways to Learn 📈 33:14 – Measuring Success 💰 34:47 – Venture Capital Funding 🌟 36:10 – Fundamental Leadership Belief 🔑 38:24 – The Most Valuable Leadership Skill 🔗 Connect & Resources: QuantHubMatt Cowell on LinkedInBooks Mentioned: Monetizing Innovation, Ultra LearningConnect with the Team:🎤 Host: Al Martin🎬 Producers: Kate Mayne📩 Want to be a guest? Reach out to [email protected] and tell us why you should be next! 📢 Hashtags:

MakingDataSimple #DataLiteracy #Upskilling #AI #BigData #TechPodcast #Leadership #LearnData #QuantHub

Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.