Hacking AI at the Edge of the Indian Ocean

What happens when you have terabytes of 8K video, a team of marine biologists, and zero bars of internet? You build a “far-edge” data center in the middle of a research vessel. In this session, we recount the high-stakes engineering of a deep-sea hackathon aboard the OceanXplorer. We’ll strip away the gloss and dive into the architecture required to run VLLMs (Large Language Models) and Streamlit app locally in a metal hull surrounded by salt water. We will explore: The Offline Stack: Running local inference on massive video files when the nearest cloud region is 3,000 miles and a satellite link away. The Transition to Scale: How we moved from local “survival mode” to the cloud, utilizing Claude and Cortex AI to enable automation of biodiversity tagging that previously took human scientists weeks. The “Contextual” Search: Using AI agents to bridge the gap between raw sensor data (salinity, depth) and unstructured media, creating a conversational interface for the ocean floor.

See It In Action: A live demo of asking questions in natural language and getting answers from expedition data.