Synthetic Data, Robotics & AI:
How NASA, Warehouses & LLMs Are Shaping the Future

Synthetic data is rapidly becoming one of the most important building blocks in AI — from training autonomous vehicles to powering robotics on Mars. In this episode, we sit down with Brian Geisel, Founder of Symage from Geisel Software, to explore how synthetic data, robotics, machine learning, and large language models (LLMs) are reshaping AI infrastructure. We cover: 🚀 How NASA trained Mars rovers using synthetic environments 🤖 Why humanoid robots may not be the future 📦 How robotics is transforming warehouse automation and micro-fulfillment centers 🧠 Why foundation models must rely on synthetic data going forward 📊 The hidden storage challenges behind AI training 🔐 How synthetic data solves PII and regulated industry problems ⚡ The balance between real-world data and AI-generated data Brian explains why synthetic data isn’t just about generating more data — it’s about generating better, targeted data that improves model performance while reducing waste. We also dive into: • AI model training strategies • GPU vs object storage considerations • High-throughput data movement • Robotics + physical AI • The future of multimodal synthetic generation If you’re building AI systems, training models, managing data infrastructure, or investing in AI and robotics, this conversation is packed with insights. Explore more content like this at datastorage.com Learn more about Symage: https://geisel.software/synthetic-dat…