EP 20: Peter Harding from Kelvin Inc.
Peter Harding, founder of Kelvin discuss how his company is transforming the oil and gas industry with cutting-edge autonomous operations. Peter shares his journey from his beginnings in California to becoming a key innovator in energy tech startups. The conversation delves into the technical complexities of autonomous oilfields, the role of AI in enhancing efficiency, and the challenges of integrating advanced technology into the sector. Peter emphasizes the importance of human expertise working alongside AI, aiming to augment rather than replace human labor, and provides insights into the future of AI-powered solutions in oilfield operations.
0:50 - Peter Harding Background
5:40 - Kelvin Origin Story
9:32 - Kelvin's Current Role in AI
10:17 - AI Adoption Strategies
14:05 - AI as a Force Multiplier
15:31 - Knowledge Institutionalization
16:50 - AI Implementation Ease
19:39 - Industry Adoption Speed
21:55 - Empathy in AI Sales
24:50 - Identifying Customer Pain Points
26:45 - Transition to AI Software
30:37 - Data Quality Significance
38:50 - System Level AI Control
40:37 - Causal Inference in AI
44:12 - AI as a Complementary Tool
46:50 - Hybrid AI Models
48:54 - AI Edge Case Challenges
50:08 - Combining Human Expertise with AI
50:35 - AI in Reservoir Impact Examples
55:41 - Data Science Scalability
59:47 - Data Science Simplification
1:01:04 - Energy Sector Software Learning Curve
1:03:03 - Comprehensive vs Specialized Solutions
1:05:08 - Specialization in Energy Tech
1:06:20 - Quickfire Questions Segment
1:10:02 - Energy Tech Career Advice
1:14:04 - Texas Ice Storm Discussion
1:14:44 - Connecting with Peter Harding
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0:00 - Podcast Introduction0:50 - Peter Harding Background
5:40 - Kelvin Origin Story
9:32 - Kelvin's Current Role in AI
10:17 - AI Adoption Strategies
14:05 - AI as a Force Multiplier
15:31 - Knowledge Institutionalization
16:50 - AI Implementation Ease
19:39 - Industry Adoption Speed
21:55 - Empathy in AI Sales
24:50 - Identifying Customer Pain Points
26:45 - Transition to AI Software
30:37 - Data Quality Significance
38:50 - System Level AI Control
40:37 - Causal Inference in AI
44:12 - AI as a Complementary Tool
46:50 - Hybrid AI Models
48:54 - AI Edge Case Challenges
50:08 - Combining Human Expertise with AI
50:35 - AI in Reservoir Impact Examples
55:41 - Data Science Scalability
59:47 - Data Science Simplification
1:01:04 - Energy Sector Software Learning Curve
1:03:03 - Comprehensive vs Specialized Solutions
1:05:08 - Specialization in Energy Tech
1:06:20 - Quickfire Questions Segment
1:10:02 - Energy Tech Career Advice
1:14:04 - Texas Ice Storm Discussion
1:14:44 - Connecting with Peter Harding
https://www.instagram.com/digitalwildcatters
https://www.tiktok.com/@digitalwildcatters
https://www.facebook.com/digitalwildcatters
https://twitter.com/DWildcatters
