I've seen a TON of horror stories with tech debt and code migrations. It's estimated that 15% to 60% of every dollar in IT spend goes toward tech debt (that's a big range, I know). Regardless, most of this tech debt will not be paid down without a radical change in how we do things. Might AI be the Hail Mary we need to pay down tech debt? I don't see why not...

My works:

📕Fundamentals of Data Engineering: https://www.oreilly.com/library/view/fundamentals-of-data/9781098108298/

🎥 Deeplearning.ai Data Engineering Certificate: https://www.coursera.org/professional-certificates/data-engineering

🔥Practical Data Modeling: https://practicaldatamodeling.substack.com/

🤓 My SubStack: https://joereis.substack.com/

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.

In this episode, we dive into the world of data storytelling with special guest Angelica Lo Duca, a professor, researcher, and author. Pull up a chair as we explore her journey from programming to teaching, and dive into the principles of turning raw data into compelling stories.

Key topics include:

Angelica’s background: From researcher to professor and published author

Why write a book?: The motivation, process, and why she chooses books over blogs

About the book: Data Storytelling with Altair and Generative AI

Overview of the book: Who it’s for and the key insights it offers

What is data storytelling and how it differs from traditional dashboards and reports

Why Altair? Exploring Altair and Vega-Lite for effective visualizations

Generative AI’s role: How tools like ChatGPT and DALL-E fit into the data storytelling process, and potential risks like bias in AI-generated images

DIKW Pyramid: Moving from raw data to actionable wisdom using the Data-Information-Knowledge-Wisdom framework

Where to buy her books: https://www.amazon.com/stores/Angelica-Lo-Duca/author/B0B5BHD5VF https://www.amazon.com/Become-Great-Data-Storyteller-Change/dp/1394283318 https://www.amazon.com/Data-Storytelling-Altair-Angelica-Duca/dp/1633437922/

Snippet: https://livebook.manning.com/book/data-storytelling-with-altair-and-ai/chapter-10/16

Connect with Angelica on Medium for more articles and insights: https://medium.com/@alod83/about

Nora Szentivanyi and Raphael Brun-Aguerre discuss their takeaways from the September CPI reports and how the incoming data are shaping the outlook for global inflation and monetary policy. Global headline inflation eased further to 2.7%oya, aided by falling energy prices––a decline that has supported consumer purchasing power. But core inflation is proving to be sticky around 3% after stepping down from 3.4%ar in 1H24. Services inflation globally continues to run above pre-pandemic norms, even as goods prices have returned to their pre-pandemic inflation rate. However, persistent divergences in both domestic demand and supply are now starting to drive greater variation in inflation outcomes. 

This podcast was recorded on October 24, 2024.

This communication is provided for information purposes only.  Institutional clients can view the related report at https://www.jpmm.com/research/content/GPS-4824594-0 , https://www.jpmm.com/research/content/GPS-4820478-0 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.

Generative AI and data are more interconnected than ever. If you want quality in your AI product, you need to be connected to a database with high quality data. But with so many database options and new AI tools emerging, how do you ensure you’re making the right choices for your organization? Whether it’s enhancing customer experiences or improving operational efficiency, understanding the role of your databases in powering AI is crucial.  Andi Gutmans is the General Manager and Vice President for Databases at Google. Andi’s focus is on building, managing, and scaling the most innovative database services to deliver the industry’s leading data platform for businesses. Prior to joining Google, Andi was VP Analytics at AWS running services such as Amazon Redshift. Prior to his tenure at AWS, Andi served as CEO and co-founder of Zend Technologies, the commercial backer of open-source PHP. Andi has over 20 years of experience as an open source contributor and leader. He co-authored open source PHP. He is an emeritus member of the Apache Software Foundation and served on the Eclipse Foundation’s board of directors. He holds a bachelor’s degree in computer science from the Technion, Israel Institute of Technology. In the episode, Richie and Andi explore databases and their relationship with AI and GenAI, key features needed in databases for AI, GCP database services, AlloyDB, federated queries in Google Cloud, vector databases, graph databases, practical use cases of AI in databases and much more.  Links Mentioned in the Show: GCPConnect with AndiAlloyDB for PostgreSQLCourse: Responsible AI Data ManagementRelated Episode: The Power of Vector Databases and Semantic Search with Elan Dekel, VP of Product at PineconeSign up to 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

Brought to you by: • The Enterprise Ready Conference on October 30th — For B2B leaders building enterprise SaaS. • DX — DX is an engineering intelligence platform designed by leading researchers.  • ByteByteGo — Ace your next system design interview. — You may not be familiar with Bending Spoons, but I guarantee you’ve encountered some of their well-known products, like Evernote and Meetup. In today’s episode of The Pragmatic Engineer, we sit down with three key figures from the Italy-based startup: cofounder and CEO Luca Ferrari, CTO Francesco Mancone, and Evernote product lead Federico Simionato. Bending Spoons has been profitable from day one, and there's plenty we can learn from their unique culture, organizational structure, engineering processes, and hiring practices. In today’s conversation, we cover the following topics: • The controversial acquisitions approach of Bending Spoons • How Bending Spoons spent more than $1 billion in buying tech companies • How the Evernote acquisition happened • How Bending Spoons operates and how it organizes product and platform teams • Why engineering processes are different across different products • How ‘radical simplicity’ is baked into everything from engineering processes to pay structure. • And much more! — The Pragmatic Engineer deepdives relevant for this episode: • Good attrition, bad attrition for software engineers: https://newsletter.pragmaticengineer.com/p/attrition  • Healthy oncall practices: https://newsletter.pragmaticengineer.com/p/healthy-oncall-practices • Shipping to production: https://newsletter.pragmaticengineer.com/p/shipping-to-production • QA across the tech industry: https://newsletter.pragmaticengineer.com/p/qa-across-tech — In this episode, we cover: (2:09) Welcome, Luca, Francesco, and Federico from Bending Spoons (03:15) An overview of the well-known apps and products owned by Bending Spoons (06:38) The elephant in the room: how Bending Spoons really acquires companies (09:46) Layoffs: Bending Spoons’ philosophy on this (14:10) Controversial principles (17:16) Revenue, team size, and products (19:35) How Bending Spoons runs AI products and allocates GPUs (23:05) History of the company (27:04) The Evernote acquisition (29:50) Modernizing Evernote’s infrastructure (32:44) “Radical simplicity” and why they try for zero on calls (36:13) More on changes made to the Evernote systems (41:13) How Bending Spoons prioritizes and ships fast  (49:40) What’s new and what’s coming for Bending Spoons (51:08) Organizational structure at the company (54:07) Engineering practices (57:03) Testing approaches (58:53) Platform teams (1:01:52) Bending Spoons tech stack and popular frameworks (1:05:55) Why Bending Spoons hires new grads and less experienced engineers (1:08:09) The structure of careers and titles at Bending Spoons (1:09:50) Traits they look for when hiring  (1:12:50) Why there aren’t many companies doing what Bending Spoons does  — Where to find Luca Ferrari: • X: https://x.com/luke10ferrari • LinkedIn: https://www.linkedin.com/in/luca-ferrari-12418318 Where to find  Francesco Mancone: • LinkedIn: https://www.linkedin.com/in/francesco-mancone Where to find Federico Simionato: • X: https://x.com/fedesimio • LinkedIn: https://www.linkedin.com/in/federicosimionato Where to find Gergely: • Newsletter: https://www.pragmaticengineer.com/ • YouTube: https://www.youtube.com/c/mrgergelyorosz • LinkedIn: https://www.linkedin.com/in/gergelyorosz/ • X: https://x.com/GergelyOrosz — References and Transcripts: 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

Closing the Responsible AI Talent Gap: Building AI Literacy, Training, and the Workforce of the Future?

Responsible AI Adoption: Bridging Strategy and Implementation for Impact

Designing secure systems for a responsible AI future.

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:

⁠TikTok vai substituir funcionários por IA;

Meta demite funcionário por causa do vale-alimentação:

⁠OpenAI e Microsoft estariam revendo parceria;

Participe da Live - Potfólio de Dados

Envie seu portifólio para ser analisado ao vivo

Baixe o relatório completo do State of Data Brazil e os highlights da pesquisa :

Demais canais do Data Hackers:

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In-depth discussion on emotional intelligence in AI as a cornerstone of responsible AI.

AI Risks, Compliance and Global Regulations

Send us a text Part 2 with Mr. Ian Smith, the most interesting man alive… Serial Entrepreneurial and Co-founder of Lighthouse Technology, accelerating AI in the data center to optimize IT, Cloud and Data environments. 00:50 Lighthouse Technology02:23 A Closed, Free AI Model?? How is it Monetized?08:17 Back to the Data Center10:44 The Edge11:51 Lighthouse GTM19:29 The Future21:12 Reaching Lighthouse21:43 Rapid Fire- Hardest Part of Entrepreneurship- Easiest Part of EntrepreneurshipLinkedin: linkedin.com/in/ian-smith-a803701 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 TechnicalSales, IBM, where we explore trending technologies, business innovation,and leadership ... 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.

Keynote discussions on the future of AI governance, global regulatory frameworks, and compliance strategies for managing AI risks effectively.

Today, we’re joined by Vineet Jain, Co-Founder & CEO of Egnyte, the #1 cloud content governance platform. We talk about:  The generative AI hype cycleStartups focusing on creating value versus increasing their valuationBiggest challenges to implementing an enterprise content management systemHow to boost user adoption of a new content management systemWill on-prem infrastructure eventually disappear?

Help us become the #1 Data Podcast by leaving a rating & review! We are 67 reviews away! Elijah Butler shares his journey from data analyst to senior roles. We talk about the key skills and strategies that can help you advance while staying true to your career goals. 💌 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 00:54 Differences Between Data Analyst and Senior Data Analyst 02:31 Elijah's Journey to Senior Data Analyst 09:16 The Importance of Soft Skills and Continuous Learning 12:42 Networking and Internal Promotions 16:47 Advice for Aspiring Senior Analysts 🔗 CONNECT WITH ELIJAH BUTLER: 🤝 LinkedIn: https://www.linkedin.com/in/elijahbutler 🎥 YouTube Channel: https://www.youtube.com/@ImElijahButler_ 🎵 TikTok: https://www.tiktok.com/@imelijahbutler 🔗 CONNECT WITH AVERY: 🔗 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

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

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 21 of Data Product Management in Action, Frannie Helforoush interviews Lucca Kazan, a senior AI product manager about Navigating AI in Data Product Management. Luca shares insights from his work on innovative data products. He shares insights about search and personalization engines, facial recognition systems, and anti-fraud solutions. He’ll explore the relationship between AI and data product management and challenges in the discovery phase and the importance of stakeholder management. Tune in to discover how understanding AI technology can enhance user-focused product development! About our host Frannie Helforoush: Frannie's journey began as a software engineer and evolved into a strategic product manager. Now, as a data product manager, she leverages her expertise in both fields to create impactful solutions. Frannie thrives on making data accessible and actionable, driving product innovation, and ensuring product thinking is integral to data management. Connect with Frannie on LinkedIn. About our guest Lucca Kazan: Seasoned Artificial Intelligence Product Manager, with over 9 years of experience in product strategy and 5 years in AI development. By leveraging AI aligned with business goals Lucca has been able to increase EBITDA by 7 digits (USD/ year) for the biggest food delivery app in Latin America, reduce user drop-off by 83% for the biggest facial recognition company in Brazil and reduced frau by 87% (8 digits in monthly savings) for the biggest food delivery app in Brazil! Connect with Lucca 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!              

The "LLM Engineer's Handbook" is your comprehensive guide to mastering Large Language Models from concept to deployment. Written by leading experts, it combines theoretical foundations with practical examples to help you build, refine, and deploy LLM-powered solutions that solve real-world problems effectively and efficiently. What this Book will help me do Understand the principles and approaches for training and fine-tuning Large Language Models (LLMs). Apply MLOps practices to design, deploy, and monitor your LLM applications effectively. Implement advanced techniques such as retrieval-augmented generation (RAG) and preference alignment. Optimize inference for high performance, addressing low-latency and high availability for production systems. Develop robust data pipelines and scalable architectures for building modular LLM systems. Author(s) Paul Iusztin and Maxime Labonne are experienced AI professionals specializing in natural language processing and machine learning. With years of industry and academic experience, they are dedicated to making complex AI concepts accessible and actionable. Their collaborative authorship ensures a blend of theoretical rigor and practical insights tailored for modern AI practitioners. Who is it for? This book is tailored for AI engineers, NLP professionals, and LLM practitioners who wish to deepen their understanding of Large Language Models. Ideal readers possess some familiarity with Python, AWS, and general AI concepts. If you aim to apply LLMs to real-world scenarios or enhance your expertise in AI-driven systems, this handbook is designed for you.

Mastering the technical side of data and AI is one thing, but communicating those insights effectively is a whole different challenge. How do you make sure your data is understood, acted upon, and influences decisions? It’s not just about presenting the right numbers—it’s about framing them in a way that resonates with different audiences. But how do you tailor your communication to different stakeholders and ensure your message cuts through? What strategies can you use to make your insights truly impactful? Wes Kao is an entrepreneur, marketer, coach, and advisor who writes at newsletter.weskao.com. She is co-founder of Maven, an edtech company that raised $25M from First Round and Andreessen Horowitz. Previously, she co-founded the altMBA with bestselling author Seth Godin. In the episode, Richie and Wes explore communication skills, tailoring to your audience, persuasion vs information, feedback and behavioral change, intellectual honesty, judgement and analytical thinking, management and ownership, dealing with mistakes, conflict management, career advice for data practitioners and much more.  Links Mentioned in the Show: Wes’ WebsiteConnect with Wes10,000 Hours Concept by Malcolm GladwellCourse: Data Communication ConceptsRelated Episode: Making Better Decisions using Data & AI with Cassie Kozyrkov, Google's First Chief Decision ScientistSign up to 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

Summary: In this episode, we dive into the world of pet health and AI with a focus on an innovative AI-powered pet health chatbot. Inspired by the real-life experience of pet owners, this project tackles the late-night panic every pet parent knows all too well—when your pet gets into something they shouldn’t and you're left searching for answers online. Using the cutting-edge capabilities of GPT-3.5, this chatbot cross-references trusted sources like the ASPCA and AVMA to provide clear, reliable advice on common pet health concerns. While it’s not a replacement for a vet, it’s an invaluable tool for empowering pet owners to take charge of their pet’s health, reducing stress, and improving early detection of potential issues. Join us as we explore how this technology can make a real difference, not just for individual pet owners, but for the entire field of veterinary medicine. Key Takeaways: * The inspiration behind developing an AI-powered pet health chatbot for everyday pet owners. * How GPT-3.5 compares to a human "genius" (think Mike Ross from Suits). * Why trustworthy sources like the ASPCA and AVMA are crucial for providing reliable pet health advice. * A breakdown of how the chatbot works and what it can do for you (or your pet-loving friends). * The future potential of AI in pet health and how it could change the landscape of veterinary care. How do you think having an AI-powered tool like this at your fingertips would change the way we approach pet health? Share your thoughts in the comments or reach out on mukundansankar.substack.com! Links: How I Built an AI-based Chatbot for Diagnosing Pet Health - Blog ASPCA AVMA This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit mukundansankar.substack.com