Katie, Nicolaie and Steven debate exposures across EM Edge to the potential policy shifts of a second Trump administration. EM Edge would seem the most exposed given their low diversification, high funding needs, openness to trade and shallower local capital markets. Yet, starting points are generally more favorable than compared to past global shocks as fundamentals have improved. Reliance on volatile market funding is also less and FX reserves are higher. While Edge economies, as with most global economies, would be exposed, there are relative points of pressure and other economies that could benefit. The podcast debates three channels through which Edge economies could be exposed to policy changes in the US: trade, immigration and funding conditions.

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

This podcast was recorded on 20 November 2024.

This communication is provided for information purposes only. Institutional clients can view the related report at https://www.jpmm.com/research/content/GPS-4837413-0, https://www.jpmm.com/research/content/GPS-4844291-0 for more information; please visit www.jpmm.com/research/disclosures for important disclosures. © 2024 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.

Lightning talk by Andy Foley from Nationwide Building Society on sustainable value from AI and cloud computing.

Lightning talk by Dan Rickards from Telefonica Tech on sustainable AI and cloud computing.

Lightning talk by Greg Homes from Apptio on sustainable AI and cloud computing.

Lightning talk by James Hall from Greenpixie on sustainable AI and cloud computing.

Lightning talk by Mark Butcher from Posetiv on sustainable AI and cloud computing.

Introducing SQL database in Fabric: Discover the future of data management and unlock new scenarios that drive your business forward. Join us as we showcase the first fully SaaS database experience in Microsoft Fabric. Experience the simplicity of an integrated development environment that empowers you to quickly harness the power of an AI-driven analytics platform. Learn how to access both transactional and analytical data in one place without compromising application performance.

𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Panos/Panagiotis Antonopoulos * Anna Hoffman * Asad Khan

𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This is one of many sessions from the Microsoft Ignite 2024 event. View even more sessions on-demand and learn about Microsoft Ignite at https://ignite.microsoft.com

BRK196 | English (US) | Data

MSIgnite

Data is the fuel for innovation, driving the development of transformative applications and artificial intelligence (AI). This session will explore how harnessing the power of data across the Azure databases portfolio can lead to groundbreaking advancements that enhance operational efficiency, deliver personalized user experiences, and revolutionize the way we interact with technology.

𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Shireesh Thota * Arun Ulagaratchagan * James Codella * Charles Feddersen * Aditi Gupta * Bob Ward

𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This is one of many sessions from the Microsoft Ignite 2024 event. View even more sessions on-demand and learn about Microsoft Ignite at https://ignite.microsoft.com

BRK188 | English (US) | Data

MSIgnite

AI is driving a reinvention across your apps and powering new use cases across your business. Join us to learn how Azure AI Foundry is unlocking this AI revolution across all your apps and solutions.

𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Asha Sharma

𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This is one of many sessions from the Microsoft Ignite 2024 event. View even more sessions on-demand and learn about Microsoft Ignite at https://ignite.microsoft.com

BRK103 | English (US) | AI

MSIgnite

Begin Ignite 2024 with a deep dive into Azure OpenAI Service’s latest product launches and capabilities. Steve Sweetman and Yina Arenas will lead a live demonstration, showcasing the power of Azure OpenAI Service in real-world applications. This session will provide attendees with a comprehensive understanding of how Azure OpenAI Service is revolutionizing industries and will feature a technical product leader from the NBA to join the speakers on stage, followed by a Q&A.

𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Yina Arenas * Charlie Rohlf * Steve Sweetman

𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This is one of many sessions from the Microsoft Ignite 2024 event. View even more sessions on-demand and learn about Microsoft Ignite at https://ignite.microsoft.com

BRK100 | English (US) | AI

MSIgnite

The Data Product Management In Action podcast, brought to you by Soda and executive producer Scott Hirleman, is a platform for data product management practitioners to share insights and experiences.  In Episode 24 of Data Product Management in Action, our host Nick Zervoudis is joined byTefi Trabuchi, Data Platform Product Manager at SumUp, to discuss her experience transforming a reactive data platform team into a user-focused, strategy-driven powerhouse. Tefi shares how she tackled challenges like burnout, prioritization struggles, and resistance to product practices such as user research and OKRs. She highlights the pivotal role of user interviews in shifting mindsets and the delicate balance between reducing risk, ensuring compliance, and driving innovation. Tefi also emphasizes the value of clear communication and curiosity when working in highly technical domains. This episode offers practical insights for product managers navigating the complexities of data, AI, and machine learning. About our host Nick Zervoudis: Nick is Head of Product at CKDelta, an AI software business within the CKHutchison Holdings group. Nick oversees a portfolio of data products and works with sister companies to uncover new opportunities to innovate using data,analytics, and machine learning.Nick's career has revolved around data and advanced analytics from day one,having worked as an analyst, consultant, product manager, and instructor for startups, SMEs, and enterprises including PepsiCo, Sainsbury's, Lloyds BankingGroup, IKEA, Capgemini Invent, BrainStation, QuantSpark, and Hg Capital. Nick is also the co-host ofLondon's Data Product Management meetup, andspeaks & writes regularly about data & AI product management. Connect with Nick on LinkedIn. About our guest Tefi Trabuchi:Tefi is a Data Platform Product Manager at SumUp, where she focuses on making sure our data tools are not only secure and efficient but also provide a smooth user experience for our internal teams. Before this, she led the development of an in-house Data Observability tool at Glovo, introducing governance rules and SLAs for key datasets. Tefi enjoys working closely with teams to create practical solutions that make accessing and using data easier and more intuitive, so everyone can make more informed decisions faster. Connect with Tefi on LinkedIn. All views and opinions expressed are those of the individuals and do not necessarily reflect their employers or anyone else.  Join the conversation on LinkedIn.  Apply to be a guest or nominate someone that you know.  Do you love what you're listening to? Please rate and review the podcast, and share it with fellow practitioners you know. Your support helps us reach more listeners and continue providing valuable insights!              

In this captivating episode of Data and AI with Mukundan, we unravel the mysteries of Neurosymbolic AI—a powerful combination of neural networks and symbolic reasoning. This hybrid approach is revolutionizing artificial intelligence, tackling the challenges of explainability, adaptability, and reasoning. Learn why Neurosymbolic AI is more than just a technological innovation—it's a potential game-changer for industries ranging from healthcare to autonomous vehicles. Discover how this blend of brain-inspired learning and logic-driven analysis can solve some of AI's toughest problems, such as ethical decision-making and trustworthiness. Dive into real-world applications, breakthrough cases, and the challenges that researchers face as they push this cutting-edge technology toward its full potential. Episode Chapters: [00:00] Introduction Host Mukundan Sankar welcomes listeners and previews the episode's focus on Neurosymbolic AI—what it is and why it matters.[00:41] What Is Neurosymbolic AI? An exploration of the concept, blending neural networks' pattern recognition with symbolic AI's logic and reasoning.[01:11] The Cold War of AI: Neural vs. Symbolic A breakdown of the strengths and weaknesses of neural networks and symbolic AI, and why each is incomplete on its own.[02:07] Enter Neurosymbolic AI: A Peace Treaty How Neurosymbolic AI bridges the gap, creating a hybrid system that's intuitive yet logical.[02:49] Standalone AI's Weaknesses Examples of where standalone neural or symbolic systems fall short, including face recognition and logical reasoning.[03:14] Real-World ApplicationsMedical Imaging: Detecting tumors and explaining the findings.Fraud Detection: Spotting anomalies and reasoning about patterns.Autonomous Driving: Recognizing pedestrians and predicting their actions.Multimodal AI: Combining text, images, and logic to solve practical problems.[05:43] The Future of AI The potential of Neurosymbolic AI to address ethical decision-making, trustworthiness, and even general intelligence.[06:24] Challenges and Opportunities Can Neurosymbolic AI scale to solve the hardest problems, or will it remain a niche solution?[06:46] Closing Thoughts Mukundan reflects on the promise of Neurosymbolic AI and invites listeners to share their thoughts on its potential.

Send us a text Ben Lowe, Founder and CEO of Lighthouse Technology, shares insights into building a successful entrepreneurial journey, the creation of Lighthouse, and the transformative potential of Agentic AI for enterprises. Packed with career advice and strategies for innovation, this episode is a must-listen for tech enthusiasts and aspiring entrepreneurs. #Entrepreneurship #AgenticAI #TechLeadership #Innovation #BusinessGrowth #CareerAdvice #AIForEnterprise #StartupJourney

01:34 Finding a Entrepreneurial Partner04:43 The Creation of Lighthouse08:10 Becoming the CEO09:34 The Biggest Challenge of Entrepreneurship11:30 Lighthouse Technology19:07 Agentic AI20:16 The Lighthouse Trajectory22:12 The GTM31:39 Reseller versus Innovator36:53 AI for the Enterprise41:35 The 2-Min Pitch43:30 What's True? Linkedin: https://www.linkedin.com/in/lowebenjamin/?originalSubdomain=uk

Website: https://lighthousetechnology.ai/

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

Episode Description: In this episode, we dive deep into the world of fine-tuning pre-trained AI models. Starting with the basics of pre-trained models like BERT, GPT, and ResNet, we explore how fine-tuning transforms them from generalists into task-specific experts. We discuss real-world examples, from improving sentiment analysis accuracy by 15% to enhancing tumor detection rates by 25%, and even boosting translation precision by 20% for specialized language pairs. Learn how fine-tuning not only sharpens AI's skills but also saves time, resources, and makes AI applications more sustainable. Wrapping up with best practices for fine-tuning, you'll get actionable tips to ensure success in your AI projects. Whether you're an AI enthusiast or just curious about how these systems get smarter, this episode is packed with insights. Don't forget to check the show notes for the blog link and subscribe for more AI mysteries decoded!

Episode Chapters [00:00 - 02:34] Introduction to Pre-Trained Models Understanding the basics of pre-trained AI models and why they often need fine-tuning to meet specific requirements. [02:35 - 02:55] Cracking Sarcasm in Text Exploring how fine-tuning helps AI understand nuances like sarcasm and slang, improving sentiment analysis. [02:56 - 04:25] Enhancing Image Models for Niche Tasks Discover how fine-tuning image models like ResNet improves accuracy in medical imaging and other specialized tasks. [04:26 - 04:59] Efficiency Through Fine-Tuning How fine-tuning reduces training time by 50%, making it an eco-friendly and resourceful approach. [05:00 - 05:17] Best Practices for Fine-Tuning Key tips for successful fine-tuning, including managing learning rates and avoiding overfitting. [05:18 - 05:56] Conclusion: Smarter, Not Harder A summary of how fine-tuning transforms AI into a sharper, more efficient tool for solving real-world problems. Additional Links: Blog Post that talks about this: https://medium.com/ai-in-plain-english/fine-tuning-pre-trained-models-how-to-make-ai-work-smarter-not-harder-7cf10b5d05f1 Stay tuned for the next episode and check the show notes for more resources!

Dive into the intelligence that powers artificial intelligence Artificial intelligence is swiftly moving from a sci-fi future to a modern reality. This edition of Artificial Intelligence For Dummies keeps pace with the lighting-fast expansion of AI tools that are overhauling every corner of reality. This book demystifies how artificial intelligence systems operate, giving you a look at the inner workings of AI and explaining the important role of data in creating intelligence. You'll get a primer on using AI in everyday life, and you'll also get a glimpse into possible AI-driven futures. What's next for humanity in the age of AI? How will your job and your life change as AI continue to evolve? How can you take advantage of AI today to make your live easier? This jargon-free Dummies guide answers all your most pressing questions about the world of artificial intelligence. Learn the basics of AI hardware and software, and how intelligence is created from code Get up to date with the latest AI trends and disruptions across industries Wrap your mind around what the AI revolution means for humanity, and for you Discover tips on using generative AI ethically and effectively Artificial Intelligence For Dummies is the ideal starting point for anyone seeking a deeper technological understanding of how artificial intelligence works and what promise it holds for the future.

Exploration des modèles IA les plus avancés pour un réalisme époustouflant. Jusqu’où peut-on aller dans le contrôle des détails, et sommes-nous capables de faire la différence entre la réalité et l’IA ?

Introduction aux principaux défis et opportunités que l'intelligence artificielle soulève dans le domaine juridique.

A Fireside Chat with Hugo Bowne-Anderson and Alex Filipchik (Head of Infrastructure, Cloud Kitchens) on how machine learning (ML) and AI are evolving from niche specializations into essential engineering disciplines. Topics include engineering ML and AI at scale, the shift from specialist roles to core engineering, practical infrastructure decisions, generative AI use cases, simplifying ML adoption for engineers, and the future of data and ML engineering.

Help us become the #1 Data Podcast by leaving a rating & review! We are 67 reviews away! No fluff, no jargon; just the essentials to kick-start your data analyst career in 2025 with a strategy built for success. 💌 Join 30k+ 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 00:16 Understanding Different Data Roles 01:48 Essential Data Skills and Tools 04:36 Building Projects to Showcase Skills 08:13 Creating a Portfolio for Your Projects 09:06 Optimizing LinkedIn and Resume 10:46 Applying for Jobs and Networking 12:38 Preparing for Interviews 14:25 Conclusion and Final Tips Join the Bootcamp: Data Career Jumpstart Browse Data Jobs: Find a Data Job Must-Learn Skills for Aspiring Analysts: Watch on YouTube Find Free Datasets for Practice: Watch on YouTube Stratascratch for SQL Practice: Visit Stratascratch Prepare for Interviews: Interview Simulator 🔗 CONNECT WITH AVERY 🎥 YouTube Channel 🤝 LinkedIn 📸 Instagram 🎵 TikTok 💻 Website 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

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We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here. We’re often caught chasing the dream of “self-serve” data—a place where data empowers stakeholders to answer their questions without a data expert at every turn. But what does it take to reach that point? How do you shape tools that empower teams to explore and act on data without the usual bottlenecks? And with the growing presence of natural language tools and AI, is true self-service within reach, or is there still more to the journey? Sameer Al-Sakran is the CEO at Metabase, a low-code self-service analytics company. Sameer has a background in both data science and data engineering so he's got a practitioner's perspective as well as executive insight. Previously, he was CTO at Expa and Blackjet, and the founder of SimpleHadoop and Adopilot. In the episode, Richie and Sameer explore self-serve analytics, the evolution of data tools, GenAI vs AI agents, semantic layers, the challenges of implementing self-serve analytics, the problem with data-driven culture, encouraging efficiency in data teams, the parallels between UX and data projects, exciting trends in analytics, and much more. Links Mentioned in the Show: MetabaseConnect with SameerArticles from Metabase on jargon, information budgets, analytics mistakes, and data model mistakesCourse: Introduction to Data CultureRelated Episode: Towards Self-Service Data Engineering with Taylor Brown, Co-Founder and COO at FivetranRewatch Sessions from RADAR: Forward 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