# AI, autonomy, and the future of naval warfare with Captain Jon Haase, United States Navy

Page: https://stenobird.com/podcast/gradient-dissent/ai-autonomy-and-the-future-of-naval-warfare-with-captain-jon-haase-united-states-navy
Text version: https://stenobird.com/podcast/gradient-dissent/ai-autonomy-and-the-future-of-naval-warfare-with-captain-jon-haase-united-states-navy.md
Podcast: [Gradient Dissent: Conversations on AI](https://stenobird.com/podcast/gradient-dissent)
Published: 2025-03-25T12:00:00+00:00
Episode link: https://wandb.ai/site/resources/podcast
Audio file: https://podcasts.captivate.fm/media/8b41a549-bdea-44b2-9826-623b56af1fd4/GD030-pod.mp3
Processing state: processed
JSON: https://stenobird.com/v1/public/podcasts/gradient-dissent/episodes/ai-autonomy-and-the-future-of-naval-warfare-with-captain-jon-haase-united-states-navy
Duration seconds: 3692

## Resource

Captain Jon Haase explains how the U.S. Navy integrates deep learning into unmanned underwater vehicles for automated target recognition. The discussion highlights the critical gap between developing functional prototypes and deploying hardened, sustainable technology for mission-critical warfare.

## Highlights
- Main idea: Automated target recognition uses ensembles of deep learners on edge hardware to detect underwater mines
- Practical takeaway: Successful military AI deployment requires focusing on sustainability, cybersecurity, and policy, not just model accuracy
- Failure mode: Relying on unhardened prototypes that lack the physical architecture and communication robustness needed for the battlefield
- Main idea: The 'fog of war' can be mitigated by using AI agents to process sparse data and improve human decision-making
- Practical takeaway: Effective defense tech must prioritize interoperability and the ability to function in low-bandwidth, high-latency environments

## Topics

Naval Warfare, Autonomous Underwater Vehicles, Automated Target Recognition, Edge AI, Defense Technology, Robotics, Deep Learning, Military Logistics

## Chapters
- 1:00 — Automated Target Recognition: An overview of using deep learning ensembles on NVIDIA hardware for detecting mines via unmanned underwater vehicles.
- 5:35 — The Challenges of Underwater Autonomy: Discussing the extreme difficulty of maintaining communication and autonomy in sub-surface environments.
- 10:25 — Lessons from Near-Misses: Reflecting on the importance of proactive mine countermeasures and the high cost of naval assets.
- 15:15 — Maintaining the Technological Edge: The necessity of aggressive innovation to keep pace with global adversaries and the importance of the defense-tech relationship.
- 20:05 — Bridging the Tech-Military Culture Gap: How the different cultures of Silicon Valley and the Navy must communicate to effectively integrate new talent and tools.
- 24:35 — Complexity in Communication Architecture: The massive engineering effort required to change physical and software layers for reliable data transmission.
- 38:40 — The Future of Robotic Warfare: Predicting a battlefield defined by multi-agent interaction and the human-machine interface.
- 43:25 — LLMs in Administrative Operations: Using AI agents for low-threat processes like HR and paperwork to free up human focus.

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## Transcript

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