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EP 44: How Shipping Intel is Redefining Maritime with AI

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Manage episode 431884652 series 3493211
collide.에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 collide. 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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.

Join the conversation shaping the future of energy.
Collide is the community where oil & gas professionals connect, share insights, and solve real-world problems together. No noise. No fluff. Just the discussions that move our industry forward.
Apply today at collide.io

Click here to watch a video of this episode.
00:00 - Intro
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

https://www.instagram.com/digitalwildcatters
https://www.tiktok.com/@digitalwildcatters
https://www.facebook.com/digitalwildcatters
https://twitter.com/DWildcatters

  continue reading

80 에피소드

Artwork
icon공유
 
Manage episode 431884652 series 3493211
collide.에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 collide. 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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.

Join the conversation shaping the future of energy.
Collide is the community where oil & gas professionals connect, share insights, and solve real-world problems together. No noise. No fluff. Just the discussions that move our industry forward.
Apply today at collide.io

Click here to watch a video of this episode.
00:00 - Intro
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

https://www.instagram.com/digitalwildcatters
https://www.tiktok.com/@digitalwildcatters
https://www.facebook.com/digitalwildcatters
https://twitter.com/DWildcatters

  continue reading

80 에피소드

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