In this episode, I speak with Wolf Vollprecht  Co-founder of Prefix.dev and to key player in the condo forge ecosystem. We discuss the critical role of open source infrastructure, like PyPi aAnd the monthly cost associated with it emphasizing the importance of sustained investment for infrastructure.

Wolf shares his journey from studying mechanical engineering and falling in love with open source to contributing, to Conda forge and creating Mamba and pixi, a fast package manager. We dive into the capabilities of pixie a Rust  based package management tool designed to be faster and more efficient than Conda. Pixie integrates well with both conda forge and PyPi environments and addresses the dependency and reproducibility issues, and supports cross-platform package management.  Wolf also talks about the open-core business model supported by VC funding and grants, aiming to build a sustainable and enhanced packaging management ecosystem. 

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This episode describes an interview with Teddy, the creator of the YouTube channel Branch Education. Which focuses on deep diving into engineering and technology topics using animation. Teddy started the channel in 2018, after working in the semiconductor industry, particularly on iron implanters. This episode outlines, how he makes his videos, including the extensive research and 3D modeling and blender and discusses the future of brunch education, hoping to create a high school. Engineering curriculum.

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In this podcast, Abel  discusses his transition from academia and Brazil to becoming a research software engineer in the Netherlands. He emphasizes his reasons for choosing Julia such as its package ecosystem and speed.  Abel  details, his involvement with the Netherlands eScience Center, where he collaborates with researchers to develop software solutions.  He also covers his background in applied mathematics and his early adoption and advocacy of Julia. The conversation touches on Julia Smooth Optimizers its utility and optimizing non-linear problems. And the importance of benchmarking for development. Abel shares insights into maintaining multiple interdependent packages in the Julia. And underscores the role of automation in testing and documentation. You also mentioned his contributions to the Juliet community through YouTube. And expresses openness to collaborating and supporting both academic and industrial projects involving Julia.

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Embark on a journey of innovation. As we explore the world of zero emission vessels powered by hydrogen cells. Dive into the educational background of Franziska and automation engineer at Future Proof Shipping. As she shares insights on retrofitting vessels for zero emissions, the dynamics of hydrogen fuel cells and the pivotal role of data analysis in the transforming maritime transport for a sustainable future.

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In this episode of Inspiring Computing, we delve into the world of Julia and the Genie with Adrian Salceanu,CEO of Genie Frameworks. Adrian shares insights into the advantages of using Julia for web development, including its high performance, distributed computing capabilities, and ease of scaling. He discusses his professional journey from a web designer in Bucharest to founding Genie in Barcelona, and explores the open-source Genie framework which offers a powerful ecosystem for building web applications. The conversation also touches on the integration of Julia with existing technologies, the roadmap for Genie, and the supportive community that surrounds it.

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This podcast, delves into innovative research, leveraging data science to enhance public transit access to suburban areas, based on a paper written by Alma Liezenga.  The episode  explores the intersection of urban transportation, social impact, and sustainable solutions emphasizing the importance of equitable access to jobs and services. The conversation portrays the significance of using data analysis and technology to improve transit efficiency while considering social implications and urban planning challenges.

See her paper here.

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Join the conversation with William Thielicke, the developer of PIVlab, as he shares insights into the world of particle image velocimetery (PIV) and its applications. Discover how PIV accurately measures fluid velocities, non invasively revolutionising research across the industries. Delve into the development journey of PI lab, including collaborations, key features and future advancements for aerodynamic studies, explore the advanced hardware setups camera technologies, and educational prospects offered by PIVlab, for enhanced fluid velocity measurements. If you are interested in the hardware he speaks of check out the company:  Optolution.

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In this episode, we dive into the fascinating world of scientific computing with Mark Kittisopikul, who has a background in computational biology. He shares insight into his career journey. And the critical role of scientific computing and modern research. Scientific computing involves leveraging computers to analyze interpret experimental data, bridging the gap between theoretical models and real world outcomes. Despite his non-computer science background, Mark helps his colleagues in biology. And other fields with computational tasks emphasizing the importance of data interpretation. He takes us through his journey, experimenting with various programming languages before discovering Julia. Which he now prefers for sufficiency in ease of use, especially in scientific applications.



Mark illustrates the benefits of Julia with the specific challenge he faced managing data from 10 cameras in a very specific microscope. Showcasing how Julia provided the solution by being able to parse gigabytes of data per second. We also explored the vibrant community around Julia and the upcoming JuliaCon conference highlighting the inclusive nature of the community and the opportunities for calibration and growth. So join us as we uncover the pivotal role of scientific computing in modern research and the advantages of using Julia for computational tasks in biology and beyond.

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In this episode, Albert recounts his journey from Nakhodka  Russia to the CEO of a Dutch company Lazy Dynamics.  He describes his academic trajectory from studying in St. Petersburg. To earning scholarship and master programs in Kyoto, Japan. There he focused on , developing driving aids for elderly drivers, but face challenges with system performances, leading him to pursue a PhD in Bayesian Inference. Albert explains Bayesian inference as a method for updating beliefs, about uncertain quantities based on new evidence. He discusses its applications and addressing uncertainty in complex systems like personalized. Just hearing it, the conversation touches on the differences between patient AI and reinforcement learning,  I'll but also introduces RxInfer and for an open source toolbox programmed in Julia designed to automate Bayesian Inference through reactive message passing. He emphasizes RxInfer and its efficiency in handling computational resources by processing information only when necessary.

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This episode (recorded late 2023) of Inspiring Computing features Nikki, a tech lead in machine learning at a company called Adyen.  She discusses her journey into AI and our role at adjunct. Nikki initially studied econometrics, but found it lacking in practical application. She then delved into programming, building apps and websites, and eventually combined her love for mathematics and programming. 

She worked at KLM as a software engineer, primarily on C++ plus before transitioning to ING. Was she, when she began working on extensively with Python and data related projects.  At Adyen Nikki explains that the company facilitates payment processes for various businesses, ensuring integration with different payment methods for companies like streaming services and eclipse Cromer's platforms. She elaborates on the, behind the scenes process of payments, including the risk checks authentication. Emphasizing agent's role as a payment. Gateway and its banking license, which allows for same day payment processing. 

Nikki discusses the complexity of payment optimization due to different messaging protocols and the rules across banks, particularly. With visa and MasterCard edge and maintain standards and smooth transition of these protocols. Leveraging machine learning models, trained on past data to adapt, to changes and ensures seamless payment processing across various banks and regions. They experiment different models per region, per group, and companies to optimize this performance. 

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