In this episode of Energy Newsbeat – Conversations in Energy, Stuart Turley speaks with Jon Brewton, CEO of Data Squared, about their groundbreaking work in AI and data management. Jon explains how their patented system eliminates AI hallucinations, making AI more trustworthy and transparent for industries like defense, energy, and engineering. They discuss the challenges of scaling AI, its applications in energy grid management, and the value of integrating various data types to optimize decision-making. This conversation sheds light on how AI can drive real-world solutions with reliability and explainability.
This is huge, with new patents in hand, Data2 Squared is helping add accountability to AI. I have been learning a great deal about AI through the podcast series on AI and Data Centers, which is significant.
The U.S. government and energy sectors will find Jon’s company and his resources critical. For the U.S. to achieve energy dominance, it must also be AI Dominant. I applaud the accountability that Jon’s team has successfully implemented.
John posted on his LinkedIn:
The biggest problem with AI isn’t what you think, it’s not speed or capability, it’s trust.
I just had an incredible conversation with Stuart Turley on Energy Newsbeat about solving AI’s accountability crisis, and it reinforced something I’ve been thinking about for months. Most AI operates as a black box, giving you answers but no idea how it arrived at them, which is dangerous when you’re making critical decisions in defense, energy, and engineering. We’ve patented a system that eliminates AI hallucinations through complete transparency, where every insight traces back to its source and every recommendation shows its reasoning.
Stuart understood immediately why this matters, putting it perfectly: “For the U.S. to achieve energy dominance, it must also be AI Dominant.” But here’s the thing, unreliable AI is worse than no AI at all.
Our platform is already transforming how organizations handle data chaos, from energy grid management to defense applications, turning disconnected information into actionable intelligence with full accountability. Instead of hoping your AI got it right, you can verify exactly how it reached its conclusions, which changes everything about how you can trust and deploy these systems.
The conversation revealed something crucial about where we are in this AI revolution, we’re not just building better AI, we’re building trustworthy AI. That’s the difference between technology that impresses and technology that transforms entire industries.
Stuart’s team gets it because they’ve been covering the intersection of AI and energy infrastructure, and they see what we see, the future belongs to organizations that can trust their AI to make mission critical decisions.
What’s your biggest concern about AI reliability in your industry?
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Also connect with Jon on his LinkedIn here: https://www.linkedin.com/in/jon-brewton-datasquared/
Thank you, Jon, for stopping by the podcast, and your leading the charge in AI security is critical for the United States – Stu
Highlights of the Podcast
00:00 – Intro
00:39 – What Is Explainable AI?
01:11 – The Problem with AI Hallucinations
03:15 – AI Systems and Trust Issues
06:21 – Data Squared’s Solution
08:32 – Real-World Applications in Energy
10:35 – Filtering Out Inaccurate AI Outputs
12:28 – Beyond Analytics: Building Trustworthy AI
16:12 – The Echo Chamber of AI Training Data
17:57 – Who Can Benefit from Data Squared’s Technology?
18:49 – Opportunities in the Utility Sector
20:08 – Achieving a Patent in AI Technology
21:06 – The Impact on Defense and Engineering
23:25 – The Role of Military Experience in Innovation
26:22 – The Unlikely Team Behind the Innovation
28:29 – Looking Ahead: Future Applications in Energy
29:01 – Closing Remarks
Check out the full transcript here:
