EP 44: How Shipping Intel is Redefining Maritime with AI
Cameron Amigo, Maritime Data Guru at Orbit MI, and Jordan Taylor, Technical Advisor at Shipping Intel, join hosts Bobby and John in this episode of Energy Bytes to explore the revolutionary impact of AI in the maritime industry. From open-source AI models like Llama 3.1 to the use of React methodology for creating efficient, domain-specific tasks, Cameron and Jordan dive into how AI is transforming operations. They discuss how these technologies are improving safety, boosting operational efficiency, and reducing commercial risks in an industry that has long struggled with data silos and inefficiencies. With their extensive experience in maritime operations and AI innovation, Cameron and Jordan offer unique insights into how AI is solving complex problems and shaping the future of maritime technology.
00:41 - OpenAI's LLM Overview
02:02 - OpenAI's API Features
08:16 - Insights on Shipping Intel
17:34 - REACT and RAG Explained
19:56 - REACT Methodology Breakdown
22:45 - Importance of Context in Data
25:48 - Tagging and Annotating Data
26:37 - Document Structure Essentials
27:40 - Chunking Techniques
29:08 - Low-Code Tools for Data Science
29:53 - Future Trends in Data Science
32:36 - Pathways to Enter Data Science
33:44 - Data Maturity Significance
37:52 - Understanding Multimodal Models
38:52 - Querying Clean Datasets with OpenAI
42:50 - Reducing Bias in AI Models
45:23 - Trust Issues in Maritime Industry
48:35 - Gaining Stakeholder Buy-In
54:07 - Addressing Real World Problems
58:07 - Analyzing Sensor Data
1:00:24 - Future Improvements in AI Models
1:04:20 - Starlink and Connectivity
1:09:21 - Concerns about AI Language Development
1:11:14 - Rapid Fire Questions
1:15:00 - Camunda Overview
1:15:30 - Recommended Books
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00:00 - Intro00:41 - OpenAI's LLM Overview
02:02 - OpenAI's API Features
08:16 - Insights on Shipping Intel
17:34 - REACT and RAG Explained
19:56 - REACT Methodology Breakdown
22:45 - Importance of Context in Data
25:48 - Tagging and Annotating Data
26:37 - Document Structure Essentials
27:40 - Chunking Techniques
29:08 - Low-Code Tools for Data Science
29:53 - Future Trends in Data Science
32:36 - Pathways to Enter Data Science
33:44 - Data Maturity Significance
37:52 - Understanding Multimodal Models
38:52 - Querying Clean Datasets with OpenAI
42:50 - Reducing Bias in AI Models
45:23 - Trust Issues in Maritime Industry
48:35 - Gaining Stakeholder Buy-In
54:07 - Addressing Real World Problems
58:07 - Analyzing Sensor Data
1:00:24 - Future Improvements in AI Models
1:04:20 - Starlink and Connectivity
1:09:21 - Concerns about AI Language Development
1:11:14 - Rapid Fire Questions
1:15:00 - Camunda Overview
1:15:30 - Recommended Books
https://www.instagram.com/digitalwildcatters
https://www.tiktok.com/@digitalwildcatters
https://www.facebook.com/digitalwildcatters
https://twitter.com/DWildcatters
