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AI Data Center Network Design and Technologies Designing the Networks that Power the AI Revolution Artificial intelligence is transforming the modern data center. Training large-scale machine learning models requires infrastructure that can move massive datasets at lightning speed-far beyond the capabilities of traditional architectures. AI Data Center Network Design and Technologies is the first comprehensive, vendor-neutral guide to building and optimizing networks purpose-built for AI workloads. Written by leading experts in AI data center design, this book bridges the gap between network engineering and AI infrastructure-helping you understand how to design, scale, and future-proof high-performance environments for training and inference. What You'll Learn Architect for scale: Build high-radix network fabrics to support GPU, TPU, and xPU-based AI clusters Optimize data movement: Integrate lossless Ethernet/IP fabrics for high-throughput, low-latency communication Design with purpose: Align network design to AI/ML workload patterns and server architectures Plan for the physical layer: Address cooling, power, and interconnect challenges at AI scale Stay ahead of innovation: Explore emerging standards from the Ultra Ethernet Consortium (UEC) Validate performance: Apply proven deployment, testing, and measurement best practices Why Read This Book AI is redefining what data centers can-and must-do. Whether you're a network engineer, architect, or technology leader, this book provides the technical foundation and forward-looking insights you need to design next-generation networks optimized for AI-scale computing. .

In today’s conversation, host Kirk Offel sits down with Gauri Potdar, the dynamic co-founder and Chief Commercial Officer of GPC Infrastructure. Gauri shares her fascinating journey—from growing up in India to building a career at the intersection of energy, sustainability, and technology in Texas. Together, they dive into the intricacies of natural gas infrastructure for data centers, the evolving challenges and opportunities around energy and water in West Texas, and what it means to truly innovate in a rapidly shifting digital landscape.

For more about us: https://linktr.ee/overwatchmissioncritical

Hello data speakers and crawling Pythons!

The 32nd Prague PyData meetup will be hosted at Apify offices right in the heart of Prague's city center (see below). The talks will start at 18:30 and we encourage you to come as soon as 18:00 to enjoy the opportunity to socialise and refresh yourselves (which you can continue doing during the break and after the talks).

By attending, you agree that you will abide by the relevant parts of Apify Event Terms and Conditions and that you will provide your true identity for registration at the venue entrance.

🤗 Our main goal is to build the community around Python and data and make it welcoming to people of various skills and experience levels.

⚡ If you are interested in giving a lightning talk (up to 5 minutes to present an idea, tool or results related at least to some degree to Python and/or data), please contact us before or during the event.

📢 Jan Kislinger: Forged in Rust, Spoken in Python

Python has long been the go-to language for data science and rapid experimentation, but when our models and algorithms start to hit performance limits, we naturally look toward something closer to the metal. In recent years, Rust has become a powerful partner: a language that offers high speed, strong safety guarantees, and a surprisingly pleasant developer experience. With tools like pyo3 and maturin, we can implement performance-critical components in Rust while keeping the flexible, expressive Python interface we love. This talk explores how the evolving Python–Rust ecosystem is gently reshaping the balance between productivity and performance. What new capabilities do we unlock by going lower level, and what, if anything, do we leave behind?

📢 Vladimír Dušek: Dealing with today's web scraping challenges in Python

Web data powers today's AI revolution, but accessing it is becoming increasingly complex as websites grow more sophisticated. Modern web scraping and automation face challenges such as IP and geographical blocking, JavaScript-based content rendering, device and browser fingerprinting, CAPTCHAs, anti-scraping HTTP headers, and more.

In this talk, you'll learn how to beat these challenges using Crawlee—a modern open-source Python library for web scraping and automation that we built from scratch at Apify.

Refreshments will be available, thanks to our generous sponsors at Apify.

How to get there? 1. Go to the Lucerna passage from Vodičkova street. 2. On the left-hand side (opposite Lucerna Music Bar)\, you'll see a glass door and gold bells. 3. Ring the "Apify" bell\, then go to the 7th floor - not more than 4 people in the lift !!!

Please, RSVP here. See you soon, PyData Prague team

AI agents need seamless access to enterprise data to deliver real value. DataHub's new MCP server creates the universal bridge that connects any AI agent to your entire data infrastructure through a single interface.

This session demonstrates how organizations are breaking down data silos by enabling AI agents to intelligently discover and interact with data across Snowflake, Databricks, BigQuery, and other platforms. See live examples of AI-powered data discovery, real-time incident response, and automated impact analysis.

Learn how forward-thinking data leaders are positioning their organizations at the center of the AI revolution by implementing universal data access strategies that scale across their entire ecosystem.

The structured data that powers business decisions is more complex than the sequences processed by traditional AI models. Enterprise databases with their interconnected tables of customers, products, and transactions form intricate graphs that contain valuable predictive signals. But how can we effectively extract insights from these complex relationships without extensive manual feature engineering? Graph transformers are revolutionizing this space by treating databases as networks and learning directly from raw data. What if you could build models in hours instead of months while achieving better accuracy? How might this technology change the role of data scientists, allowing them to focus on business impact rather than data preparation? Could this be the missing piece that brings the AI revolution to predictive modeling? Jure Leskovec is a Professor of Computer Science at Stanford University, where he is affiliated with the Stanford AI Lab, the Machine Learning Group, and the Center for Research on Foundation Models. Previously, he served as Chief Scientist at Pinterest and held a research role at the Chan Zuckerberg Biohub. He is also a co-founder of Kumo.AI, a machine learning startup. Leskovec has contributed significantly to the development of Graph Neural Networks and co-authored PyG, a widely-used library in the field. Research from his lab has supported public health efforts during the COVID-19 pandemic and informed product development at companies including Facebook, Pinterest, Uber, YouTube, and Amazon. His work has received several recognitions, including the Microsoft Research Faculty Fellowship (2011), the Okawa Research Award (2012), the Alfred P. Sloan Fellowship (2012), the Lagrange Prize (2015), and the ICDM Research Contributions Award (2019). His research spans social networks, machine learning, data mining, and computational biomedicine, with a focus on drug discovery. He has received 12 best paper awards and five 10-year Test of Time awards at leading academic conferences. In the episode, Richie and Jure explore the need for a foundation model for enterprise data, the limitations of current AI models in predictive tasks, the potential of graph transformers for business data, and the transformative impact of relational foundation models on machine learning workflows, and much more. Links Mentioned in the Show: Jure’s PublicationsKumo AIConnect with JureCourse - Transformer Models with PyTorchRelated Episode: High Performance Generative AI Applications with Ram Sriharsha, CTO at PineconeRewatch RADAR AI  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