Data Centers 101: Where AI lives and where its going

AISPIRATION: (AI + Inspiration) An ideation session of practical AI use cases

In our season two finale, we’re talking all things AISPIRATION: (AI + Inspiration) the AI tools, automations, and workflows helping us work smarter, create faster, and make life a little less manual. From streamlining podcast production and prepping for high-stakes presentations to building custom Notion automations, organizing shopping decisions, cleaning up chaotic inboxes, and using AI as a real tool for self-improvement, this episode is one big brainstorm on how to make AI actually useful in everyday life.

Data Centers 101: Where AI lives and where its going

This week I'm diving into one of the most fascinating infrastructure stories happening right now — data centers. We're going full 101 on what they actually are, how they work, and why AI has completely broken everything the industry thought it knew. We cover the four pillars every data center is built on, why a random suburb in Northern Virginia became the backbone of the global internet, and what happened when drone strikes took out three AWS data centers in the Middle East earlier this year — and what that means for how we think about digital infrastructure as a target of war. Then we get into the AI shift — why a single Nvidia GPU rack draws 42 times the power of a standard server rack, why Meta scrapped two years of construction mid-build because their facility was already obsolete, and why Google, Microsoft, and Amazon are all racing to secure nuclear power plants just to keep the lights on. And then we go to the frontier. Space-based data centers — and why the cooling problem doesn't disappear just because you're in orbit. The moon — and why 14 days of complete darkness makes it nearly impossible. And the ocean floor off the coast of Denmark — which is actually working right now. Sources & further reading: * Middle East AWS attack highlights data center vulnerabilities — TechTarget: https://www.techtarget.com/searchcio/feature/Middle-East-AWS-attack-highlights-data-center-vulnerabilities [https://www.techtarget.com/searchcio/feature/Middle-East-AWS-attack-highlights-data-center-vulnerabilities] * Space-based data centers — Real Engineering: https://www.youtube.com/watch?v=osMooAvpSSs [https://www.youtube.com/watch?v=osMooAvpSSs] * Underwater data centers — Denmark / North Sea: https://www.youtube.com/watch?v=eyklsgOClJA [https://www.youtube.com/watch?v=eyklsgOClJA] * Equinix data center infrastructure: https://www.youtube.com/watch?v=v477fvbj3rk [https://www.youtube.com/watch?v=v477fvbj3rk]

What are Claude Skills? And How to Use Them to Boost Your Productivity

If you've ever copy-pasted the same giant prompt into Claude over and over again... this episode is for you. Eden breaks down Claude Skills: what they are, how they work, and how to set them up. Whether you're a developer or someone just trying to get more out of AI in your everyday life, Skills are one of those things that once you get it, you can't go back. We cover: * Why LLMs are stateless (and why that matters more than you think) * What a Claude Skill actually is * The brain aka SKILL.md * How to build your first skill in 5 steps * How to refine skills over time to avoid bloating them with tokens * Where to find inspiration / pre-built skills you can download and use today → clawhub.ai [https://clawhub.ai/] If you're new here or want to go deeper, check out these two episodes Eden referenced: 🎙️ Agentic Systems: Details for the Developers [https://open.spotify.com/episode/0rAL31TuOLiXqUbY9vPCAV?si=IVykNssHQ1iRbPPcXl6_kw] — the technical patterns behind how agentic AI actually works. You can use these principles to write better SKILL.md files. 🎙️ AI Basics for the Baddies [https://open.spotify.com/episode/390PUpk02QmQAsm2ohIDj0?si=VCzQObLxSNSnBDEqrFi2QQ] — the foundational episode on how LLMs work under the hood

Four Tech Startups You Need To Know: Runway, Fauna Robotics, Daydream, and Neko Health

This week, we're covering four companies sitting at the bleeding edge of AI and robotics. We start with Runway, the $5.3B NYC startup quietly reshaping Hollywood from the inside out. Founded by three NYU art students, Runway's text-to-video tools are already in Oscar-winning films and our very own episode promos ;) Their bet on world models could put them at the center of enterprise AI in ways nobody expected. From there, we get into Fauna Robotics and their robot Sprout, a 3.5-foot foam-covered humanoid that is Ellen's new obsession and might be the most interesting developer platform in robotics. Sprout is a safe, expressive platform designed to live next to people. Then we look at Daydream, the fashion AI agent built by the woman who launched Nordstrom.com and scaled Stitch Fix to a billion in revenue. It's ad-free, hyper-personalized, and asking a hard question: can a vertical AI shopping layer become a durable business before Amazon or Google absorbs the idea? We close with Neko Health, Spotify Founder Daniel Ek's proactive health company that puts you in a chamber of 70 sensors and hands you a clinical picture of your body. Same day, no MRI, no radiation… for $370. In their first year alone, 1% of people scanned received potentially life-saving interventions for conditions they had no idea they had. Sit with us as we chat through four companies with four very different bets on what comes next.

Databricks Deep Dive

In this solo episode of That’s Girl Code, Ellen breaks down Databricks: why it exists, what problem it solved, and how data actually flows through it. She explains how companies got stuck between messy data lakes and expensive data warehouses, and how Databricks’ lakehouse approach keeps data in object storage like S3 while adding reliability and performance through Delta Lake (Parquet files plus a transaction log), powered by Spark for scale and Unity Catalog for governance and lineage. Then she maps real-world ingestion into three patterns—files landing in storage (Auto Loader), SaaS and apps pulling via connectors/APIs, and real-time streams like Kafka/Kinesis (Structured Streaming)—all landing first as Bronze Delta tables, before being cleaned and joined into Silver tables and shaped into Gold tables for dashboards or machine learning. She closes with two concrete examples: a near-real-time retail dashboard combining foot-traffic sensors, transactions, and store metadata, and a customer-segmentation ML workflow using feature engineering, Feature Store, MLflow model tracking, and even vector search to turn clusters into meaningful segment descriptions for marketing.