Design software pioneer Autodesk is transforming computer-aided design (CAD) by harnessing generative AI and Amazon Web Services (AWS). The company is developing advanced AI foundation models, like "Project Bernini," which can generate precise 2D and 3D geometric designs based on physical principles.

By utilizing AWS technologies such as Amazon DynamoDB, Elastic MapReduce (EMR), Amazon SageMaker, and Elastic Fabric Adapter, Autodesk has significantly enhanced its AI development process. These innovations have halved foundation model development time and increased AI productivity by 30%.

Learn more about AWS events: https://go.aws/events

Subscribe: More AWS videos: http://bit.ly/2O3zS75 More AWS events videos: http://bit.ly/316g9t4

ABOUT AWS Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts. AWS is the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

reInvent2024 #AWSreInvent2024 #AWSEvents

Help us become the #1 Data Podcast by leaving a rating & review! We are 67 reviews away! Cole Nussbaumer Knaflic, author of 'Storytelling with Data' and 'Daphne Draws Data,' shares her journey from studying mathematics to becoming a leading figure in data visualization. Cole discusses her career path, the importance of clear communication in data visualization, and tips on how to make complex data understandable. 💌 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 00:51 Cole's Background and Career 06:25 The Importance of Effective Data Communication 13:07 Tailoring Data Presentations to Different Audiences 16:06 Practical Tips for Data Visualization 20:23 Advice for Aspiring Data Professionals 26:36 Introducing Her New Book (Daphne Draws Data)  🔗 CONNECT WITH  COLE KNAFLIC 🤝 LinkedIn: https://www.linkedin.com/in/colenussbaumer 📕 Storytelling with Data by Cole Knafflic: https://amzn.to/3ZYHhsG 📒 Daphne Draws Data: https://amzn.to/4fJkIOt 📖 Books: https://www.storytellingwithdata.com/books 🔗 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

Today, we’re joined by Rich Kahn, Co-Founder and CEO of Anura, an ad fraud solution designed to improve campaign performance by accurately exposing bots, malware, and human fraud. We talk about:  Why digital marketing is a hot spot for fraudstersThe numerous benefits of reducing fraudHow to increase Return on Ad Spend (ROAS)Who is taking better advantage of AI: fraudsters or those battling fraud?

AI is not just about writing code; it's about improving the entire software development process. From generating documentation to automating code reviews, AI tools are becoming indispensable. But how do you ensure the quality of AI-generated code? What strategies can you employ to maintain high standards while leveraging AI's capabilities? These are the questions developers must consider as they incorporate AI into their workflows. Eran Yahav is an associate professor at the Computer Science Department at the Technion – Israel Institute of Technology and co-founder and CTO of Tabnine (formerly Codota). Prior to that, he was a research staff member at the IBM T.J. Watson Research Center in New York (2004-2010). He received his Ph.D. from Tel Aviv University (2005) and his B.Sc. from the Technion in 1996. His research interests include program analysis, program synthesis, and program verification. Eran is a recipient of the prestigious Alon Fellowship for Outstanding Young Researchers, the Andre Deloro Career Advancement Chair in Engineering, the 2020 Robin Milner Young Researcher Award (POPL talk here), the ERC Consolidator Grant as well as multiple best paper awards at various conferences. In the episode, Richie and Eran explore AI's role in software development, the balance between AI assistance and manual coding, the impact of generative AI on code review and documentation, the evolution of developer tools, and the future of AI-driven workflows, and much more. Links Mentioned in the Show: TabnineConnect with EranCourse: Working with the OpenAI APIRelated Episode: Getting Generative AI Into Production with Lin Qiao, CEO and Co-Founder of Fireworks AIRewatch 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

A number of elements of our high-for-long rate narrative will be tested by data and policy guidance this quarter. We will receive greater clarity on the direction of US policy where we expect the new administration to eschew extremes on trade and immigration policy while moving forward quickly on regulatory relief. Our expectation for a lift in global industry and firming in goods prices is already being challenged by a disappointing global mfg. PMI.  On inflation we do not see a repeat of the past two year’s front-loaded price increases, but look for the persistence of sticky global core CPI gains.

Speakers:

Bruce Kasman

Joseph Lupton

This podcast was recorded on 3 January 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.

It's 2025! We made it! ;)

In this podcast, I rant about why data modeling matters more than ever, AI, and why humans will seek out "human" things in 2025 and beyond.

❤️ Your support means a lot. Please like and rate this podcast on your favorite podcast platform.

🤓 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/

Welcome to Data Unchained, where we explore the decentralization of data and the cutting-edge technologies shaping the future of AI and HPC. Recorded live from Supercomputing 24 in Atlanta, Georgia, this episode features an in-depth conversation with Gary Grider, a leading technologist at Los Alamos National Laboratory, and host Molly Presley. Episode Highlights: - The evolution of storage systems: From early file systems to groundbreaking innovations like Lustre, HPSS, and NFS. - Overcoming storage challenges in massive-scale HPC and AI environments. - Insights into Los Alamos’ role in virtual nuclear testing and managing petabyte-scale simulations. - How Hammerspace Tier 0 technology is transforming local storage in compute nodes. - The convergence of AI and HPC: A look into standardizing infrastructure to support modern workloads. Gary shares his decades-long journey in storage innovation, the importance of standardized protocols like NFS, and the revolutionary impact of integrating compute and storage technologies to streamline workflows for industries beyond HPC.

DataUnchained #Supercomputing24 #HPC #AIWorkflows #DataStorage #DecentralizedData #NFS #LosAlamos #GaryGrider #BigData #ParallelComputing #Tier0Storage #AIInfrastructure #TechPodcast #Innovation #CloudComputing #MachineLearning #HybridCloud #MultiCloud #Supercomputing #TechInnovation #ArtificialIntelligence #HighPerformanceComputing #DataScience #ComputePower

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.

Summary In this episode of the Data Engineering Podcast Dan Bruckner, co-founder and CTO of Tamr, talks about the application of machine learning (ML) and artificial intelligence (AI) in master data management (MDM). Dan shares his journey from working at CERN to becoming a data expert and discusses the challenges of reconciling large-scale organizational data. He explains how data silos arise from independent teams and highlights the importance of combining traditional techniques with modern AI to address the nuances of data reconciliation. Dan emphasizes the transformative potential of large language models (LLMs) in creating more natural user experiences, improving trust in AI-driven data solutions, and simplifying complex data management processes. He also discusses the balance between using AI for complex data problems and the necessity of human oversight to ensure accuracy and trust.

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data managementData migrations are brutal. They drag on for months—sometimes years—burning through resources and crushing team morale. Datafold's AI-powered Migration Agent changes all that. Their unique combination of AI code translation and automated data validation has helped companies complete migrations up to 10 times faster than manual approaches. And they're so confident in their solution, they'll actually guarantee your timeline in writing. Ready to turn your year-long migration into weeks? Visit dataengineeringpodcast.com/datafold today for the details. As a listener of the Data Engineering Podcast you clearly care about data and how it affects your organization and the world. For even more perspective on the ways that data impacts everything around us don't miss Data Citizens® Dialogues, the forward-thinking podcast brought to you by Collibra. You'll get further insights from industry leaders, innovators, and executives in the world's largest companies on the topics that are top of mind for everyone. In every episode of Data Citizens® Dialogues, industry leaders unpack data’s impact on the world; like in their episode “The Secret Sauce Behind McDonald’s Data Strategy”, which digs into how AI-driven tools can be used to support crew efficiency and customer interactions. In particular I appreciate the ability to hear about the challenges that enterprise scale businesses are tackling in this fast-moving field. The Data Citizens Dialogues podcast is bringing the data conversation to you, so start listening now! Follow Data Citizens Dialogues on Apple, Spotify, YouTube, or wherever you get your podcasts.Your host is Tobias Macey and today I'm interviewing Dan Bruckner about the application of ML and AI techniques to the challenge of reconciling data at the scale of businessInterview IntroductionHow did you get involved in the area of data management?Can you start by giving an overview of the different ways that organizational data becomes unwieldy and needs to be consolidated and reconciled?How does that reconciliation relate to the practice of "master data management"What are the scaling challenges with the current set of practices for reconciling data?ML has been applied to data cleaning for a long time in the form of entity resolution, etc. How has the landscape evolved or matured in recent years?What (if any) transformative capabilities do LLMs introduce?What are the missing pieces/improvements that are necessary to make current AI systems usable out-of-the-box for data cleaning?What are the strategic decisions that need to be addressed when implementing ML/AI techniques in the data cleaning/reconciliation process?What are the risks involved in bringing ML to bear on data cleaning for inexperienced teams?What are the most interesting, innovative, or unexpected ways that you have seen ML techniques used in data resolution?What are the most interesting, unexpected, or challenging lessons that you have learned while working on using ML/AI in master data management?When is ML/AI the wrong choice for data cleaning/reconciliation?What are your hopes/predictions for the future of ML/AI applications in MDM and data cleaning?Contact Info LinkedInParting Question From your perspective, what is the biggest gap in the tooling or technology for data management today?Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.init covers the Python language, its community, and the innovative ways it is being used. The AI Engineering Podcast is your guide to the fast-moving world of building AI systems.Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.If you've learned something or tried out a project from the show then tell us about it! Email [email protected] with your story.Links TamrMaster Data ManagementCERNLHCMichael StonebrakerConway's LawExpert SystemsInformation RetrievalActive LearningThe intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

Learn the Julia programming language as quickly as possible. This book is a must-have reference guide that presents the essential Julia syntax in a well-organized format, updated with the latest features of Julia’s APIs, libraries, and packages. This book provides an introduction that reveals basic Julia structures and syntax; discusses data types, control flow, functions, input/output, exceptions, metaprogramming, performance, and more. Additionally, you'll learn to interface Julia with other programming languages such as R for statistics or Python. At a more applied level, you will learn how to use Julia packages for data analysis, numerical optimization, symbolic computation, and machine learning, and how to present your results in dynamic documents. The Second Edition delves deeper into modules, environments, and parallelism in Julia. It covers random numbers, reproducibility in stochastic computations, and adds a section on probabilistic analysis. Finally, it provides forward-thinking introductions to AI and machine learning workflows using BetaML, including regression, classification, clustering, and more, with practical exercises and solutions for self-learners. What You Will Learn Work with Julia types and the different containers for rapid development Use vectorized, classical loop-based code, logical operators, and blocks Explore Julia functions: arguments, return values, polymorphism, parameters, anonymous functions, and broadcasts Build custom structures in Julia Use C/C++, Python or R libraries in Julia and embed Julia in other code. Optimize performance with GPU programming, profiling and more. Manage, prepare, analyse and visualise your data with DataFrames and Plots Implement complete ML workflows with BetaML, from data coding to model evaluation, and more. Who This Book Is For Experienced programmers who are new to Julia, as well as data scientists who want to improve their analysis or try out machine learning algorithms with Julia.

AI features and products are the hottest area of software development. Creating high quality AI software is both essential and challenging for many businesses. In this episode, we look at retrieval augmented generation, an important technique for improving text generation quality in AI applications. Beyond technical measures, we look at the broader quality problem for AI applications. How do you ensure your AI applications are effective and secure? What steps should you take to integrate AI into your existing data governance frameworks? And how do you measure the success of these AI-driven solutions? Theresa Parker is the Director of Product Management at Rocket Software. She has 25 years of experience as a technology executive with a focus on software development processes, consultancy, and business development. Her recent work in content management focuses on the use of AI and RAG to improve content discoverability. Sudhi Balan is the Chief Technology Officer for AI & Cloud. He leads the AI and data teams for data modernization, driving AI adoption of Rocket's structured and unstructured data products. He also shapes AI strategy for Rocket’s infrastructure and app portfolio. He has earned patents for safe and scalable applications of transformational technology. Previously, he led digital transformation and hybrid cloud strategy for Rocket’s unstructured data business and was Senior Director of Product Development at ASG. In the episode, Richie, Theresa, and Sudhi explore retrieval-augmented generation, its applications in customer support and loan processing, the importance of data governance and privacy, the role of testing and guardrails in AI, cost management strategies, and the potential of AI to transform customer experiences, and much more. Links Mentioned in the Show: Rocket SoftwareConnect with Theresa and SudhiCourse: Retrieval Augmented Generation (RAG) with LangChainRelated Episode: Getting Generative AI Into Production with Lin Qiao, CEO and Co-Founder of Fireworks AIRewatch 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

Day 0: Foundations of AI Agents, self paced

It's December 31, 2024. Gordon Wong and I wrap up 2024 and chat about what we're excited about in 2025 in data and otherwise.

❤️ If you like my podcasts, please like and rate it on your favorite podcast platform.

🤓 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/

As we look back at 2024, we're highlighting some of our favourite episodes of the year, and with 100 of them to choose from, it wasn't easy! The four guests we'll be recapping with are: Lea Pica - A celebrity in the data storytelling and visualisation space. Richie and Lea cover the full picture of data presentation, how to understand your audience, how to leverage hollywood storytelling and more. Out December 19.Alex Banks - Founder of Sunday Signal. Adel and Alex cover Alex’s journey into AI and what led him to create Sunday Signal, the potential of AI, prompt engineering at its most basic level, chain of thought prompting, the future of LLMs and more. Out December 23.Don Chamberlin - The renowned co-inventor of SQL. Richie and Don explore the early development of SQL, how it became standardized, the future of SQL through NoSQL and SQL++ and more. Out December 26.Tom Tunguz - general Partner at Theory Ventures, a $235m VC firm. Richie and Tom explore trends in generative AI, cloud+local hybrid workflows, data security, the future of business intelligence and data analytics, AI in the corporate sector and more. Out December 30. Rapid change seems to be the new norm within the data and AI space, and due to the ecosystem constantly changing, it can be tricky to keep up. Fortunately, any self-respecting venture capitalist looking into data and AI will stay on top of what’s changing and where the next big breakthroughs are likely to come from. We all want to know which important trends are emerging and how we can take advantage of them, so why not learn from a leading VC.  Tomasz Tunguz is a General Partner at Theory Ventures, a $235m early-stage venture capital firm. He blogs sat tomtunguz.com & co-authored Winning with Data. He has worked or works with Looker, Kustomer, Monte Carlo, Dremio, Omni, Hex, Spot, Arbitrum, Sui & many others. He was previously the product manager for Google's social media monetization team, including the Google-MySpace partnership, and managed the launches of AdSense into six new markets in Europe and Asia. Before Google, Tunguz developed systems for the Department of Homeland Security at Appian Corporation.  In the episode, Richie and Tom explore trends in generative AI, the impact of AI on professional fields, cloud+local hybrid workflows, data security, and changes in data warehousing through the use of integrated AI tools, the future of business intelligence and data analytics, the challenges and opportunities surrounding AI in the corporate sector. You'll also get to discover Tom's picks for the hottest new data startups. Links Mentioned in the Show: Tom’s BlogTheory VenturesArticle: What Air Canada Lost In ‘Remarkable’ Lying AI Chatbot Case[Course] Implementing AI Solutions in BusinessRelated Episode: Making Better Decisions using Data & AI with Cassie Kozyrkov, Google's First Chief Decision ScientistSign up to RADAR: AI...

Help us become the #1 Data Podcast by leaving a rating & review! We are 67 reviews away! Starting a career in data can be tough, but it doesn’t have to be a guessing game. Learn how to combine skills, projects, and connections to create real opportunities. 💌 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 00:18 The SPN Method 00:42 Understanding the Importance of Skills 02:46 The Role of Projects in Landing a Data Job 08:20 Networking: The Key to Success 11:11 Final Thoughts and Resources 🔗 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

Matt Housley and I have a LONG chat about working in consulting, leaving your job, AI, the job market, our thoughts on what's coming in 2025, and much more.

❤️ If you like my podcasts, please like and rate it on your favorite podcast platform.

🤓 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/

Welcome to Data Unchained, the podcast where we delve into the evolving world of decentralized data and workflows. Hosted by Molly Presley, this episode features a thought-provoking discussion with Matthew Shaxted, Co-Founder and CEO of Parallel Works, about the challenges and opportunities in hybrid and multi-cloud environments. Key Highlights: - The journey of Parallel Works: From HPC simulations to democratizing large-scale computing resources. - The convergence of HPC and AI infrastructure—how organizations are adapting to GPU-heavy workflows. - Overcoming decentralized data challenges: Solutions for application portability and cost-efficient workload management. The evolution of AI-driven task placement for seamless resource optimization. - Real-world insights into managing hybrid and multi-cloud workloads with cost controls and global namespaces. - Matthew also introduces ACTIVATE, Parallel Works' next-gen hybrid multi-cloud platform, and shares exciting announcements for the future, including advancements in Kubernetes integration and benchmarking AI task placement. Learn more about Parallel Works: https://parallel.works @parallel-works

dataunchained #DecentralizedData #HybridCloud #MultiCloud #HPC #AIWorkflows #ParallelWorks #DataManagement #CloudComputing #ArtificialIntelligence #DataInnovation #TechPodcast #BigData #MachineLearning #futureofai

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.

If you're early in your data career or still trying to break in, you've probably got questions about the path ahead and how you can advance to more senior roles.

In this episode, you'll hear from industry veteran Andrew Madson who will share his best advice to help you navigate your career path. 

You'll leave with a better understanding of the road that lies ahead, and some concrete and actionable tips you can use to help accelerate your career. What You'll Learn: What you can expect from a career in data How promotion decisions are made and how you can position yourself well Strategies for building your brand, network, and skills to accelerate your career   This session was part of our OPEN CAMPUS week in October, which included 6 days of live expert sessions.   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   About our guest: Andrew Madson is a Data Analytics, Data Science, and AI Evangelist at Dremio, with deep expertise in leveraging data to drive innovation. With a strong background in analytics, machine learning, and education, he empowers organizations and individuals to unlock the full potential of their data. Insights x Design Podcast Follow Andrew on LinkedIn

Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

As we look back at 2024, we're highlighting some of our favourite episodes of the year, and with 100 of them to choose from, it wasn't easy! The four guests we'll be recapping with are: Lea Pica - A celebrity in the data storytelling and visualisation space. Richie and Lea cover the full picture of data presentation, how to understand your audience, how to leverage hollywood storytelling and more. Out December 19.Alex Banks - Founder of Sunday Signal. Adel and Alex cover Alex’s journey into AI and what led him to create Sunday Signal, the potential of AI, prompt engineering at its most basic level, chain of thought prompting, the future of LLMs and more. Out December 23.Don Chamberlin - The renowned co-inventor of SQL. Richie and Don explore the early development of SQL, how it became standardized, the future of SQL through NoSQL and SQL++ and more. Out December 26.Tom Tunguz - general Partner at Theory Ventures, a $235m VC firm. Richie and Tom explore trends in generative AI, cloud+local hybrid workflows, data security, the future of business intelligence and data analytics, AI in the corporate sector and more. Out December 30. For our 200th episode, we bring you a special guest and taking a walk down memory lane—to the creation and development of one of the most popular programming languages in the world. Don Chamberlin is renowned as the co-inventor of SQL (Structured Query Language), the predominant database language globally, which he developed with Raymond Boyce in the mid-1970s. Chamberlin's professional career began at IBM Research in Yorktown Heights, New York, following a summer internship there during his academic years. His work on IBM's System R project led to the first SQL implementation and significantly advanced IBM’s relational database technology. His contributions were recognized when he was made an IBM Fellow in 2003 and later a Fellow of the Computer History Museum in 2009 for his pioneering work on SQL and database architectures. Chamberlin also contributed to the development of XQuery, an XML query language, as part of the W3C, which became a W3C Recommendation in January 2007. Additionally, he holds fellowships with ACM and IEEE and is a member of the National Academy of Engineering. In the episode, Richie and Don explore his early career at IBM and the development of his interest in databases alongside Ray Boyce, the database task group (DBTG), the transition to relational databases and the early development of SQL, the commercialization and adoption of SQL, how it became standardized, how it evolved and spread via open source, the future of SQL through NoSQL and SQL++ and much more.  Links Mentioned in the Show: The first-ever journal paper on SQL. SEQUEL: A Structured English Query LanguageDon’s Book: SQL++ for SQL Users: A TutorialSystem R: Relational approach to database managementSQL CoursesSQL Articles, Tutorials and Code-AlongsRelated Episode: Scaling Enterprise Analytics with...

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. Dive into conversations that flow as smoothly as your morning coffee (but don't), where industry insights meet laid-back banter. Whether you're a data aficionado or just someone curious about the digital age, pull up a chair, relax, and let's get into the heart of data, unplugged style! In this episode, we wrap up the Rootsconf mini-series with a thrilling finale with Sophie De Coppel and Warre Dreesen's workshop from our internal knowledge-sharing event: AI Hunger Games: A showdown between AI language models like GPT-4, Claude, and Gemini. Who aced coding, games, and social interactions?Human vs. Machine: Fun experiments like “Find the Human” and “The Chameleon Game” highlight where humans and AI shine—and stumble.Model Personalities Explored: Discover why some models seem nerdy, others boastful, and how creativity plays a role in performance.Engineering Insights: Behind-the-scenes on implementing and testing AI models in competitive scenarios, from advent-of-code puzzles to group chat debates.Join the fun as hosts and guests break down the playful and thought-provoking ways we’re pushing AI to its limits. Let the games begin!

The first time I met Amr Awadallah, he struck me as a rare person genuinely curious about the world and how technology and AI impact it.

We discuss his early roots as an entrepreneur, the founding of Cloudera and Vectara, the challenges of AI in enterprises, what makes humans unique, and much more.