My First Million + Starter Story Vector Database MCP1,040 episodes processed broken down to these categories, Free MCP hook it up to any capable AI and get distribution strategies that are tried and true.That is why I made it, to figure out the best distribution strategies.A vector database (embeddings of 6,702 chunks from 1,040 episodes) A semantic search layer on top of that (finds meaning, not just keywords) An MCP server that exposes that search to any compatible AI client 📦 What's Inside Each Episode Every episode was processed into 8 structured categories tailored to each show's format. 🎙️ My First Million — 8 Categories # Category What's Extracted 1 💡 Business Ideas & Opportunities Specific ideas discussed, target customer, market size, validation signals 2 📈 Trends & Emerging Markets Macro trends, industries gaining momentum, timing signals 3 🚀 Growth & Marketing Tactics SEO, cold outreach, partnerships, what's working now, overrated vs underrated 4 💰 Revenue Models & Monetization How businesses make money, pricing strategies, revenue numbers, creative angles 5 🤝 Acquisition & Deal Structures Acquisition targets, deal terms, multiples, roll-up strategies 6 📣 Content & Audience Building Newsletter/podcast/YouTube growth, audience monetization, platform tactics 7 🧩 Frameworks & Mental Models Repeating frameworks, decision heuristics, rules of thumb 8 👤 Key People & Companies Referenced Name-drops, case studies, books/resources, specific stats cited 🎙️ Starter Story — 8 Categories # Category What's Extracted 1 📣 Distribution / Marketing Primary channels, first customers, paid vs organic, what worked 2 💼 Business Model How they make money, pricing structure, revenue streams, deal size 3 🌱 Origin Story / Unfair Advantage What gave them their edge, how they found the idea, what they did before 4 ⚙️ Operations & Tools (Tech Stack) Software used, automation, team size, delegation 5 📈 Revenue Milestones & Timeline When they hit $1K/$10K/$100K months, how long it took, inflection points

📝 TL;DR Nvidia just launched a new “Space Computing” push aimed at bringing serious AI power into orbit. The vision is wild but clear, instead of sending all space data back to Earth first, satellites and orbital platforms process it in space, in real time, with AI. 🧠 Overview Nvidia is expanding beyond Earth with a new set of computing platforms built for space. The goal is to make satellites, orbital data centers, and autonomous spacecraft smart enough to process data where it is created, instead of waiting to beam everything back down to Earth. That matters because modern space systems generate huge amounts of imagery, sensor data, and communications traffic. If AI can handle more of that work in orbit, missions can react faster, use less bandwidth, and become much more autonomous. 📜 The Announcement Nvidia announced a new space computing effort focused on three main areas, orbital data centers, geospatial intelligence, and autonomous space operations. The company says its platforms are designed for the harsh constraints of space, where size, weight, and power use matter far more than they do in a normal data center. It also revealed a new Space-1 Vera Rubin Module for future space based AI computing, alongside existing IGX Thor and Jetson Orin platforms for on-orbit edge AI. On the ground, Nvidia is also pushing its RTX PRO 6000 Blackwell Server Edition GPU for faster processing of massive geospatial image archives. ⚙️ How It Works • AI compute in orbit - Instead of sending raw space data back to Earth for processing, spacecraft can run AI directly onboard and make faster decisions.• Space-1 Vera Rubin Module - Nvidia says this future module is built for orbital environments and is meant to bring data center class AI performance into space systems.• Edge AI for spacecraft - IGX Thor and Jetson Orin are designed to process sensor data, navigation, imagery, and autonomous operations locally in compact, power efficient hardware.• Faster ground processing too - Nvidia’s ground side systems can accelerate geospatial analysis dramatically, helping governments and companies process huge imagery archives much faster.• One platform from ground to orbit - Nvidia is pitching a connected AI stack where satellites, orbital systems, and Earth based data centers all work together.