Ben Taylor, CEO of VEOX Inc., Joe Reis, co-founder of Ternary Data, and Juan Sequeda, Principal Scientist at Data.World, discuss the evolution of AI from prompt engineering to goal engineering. They explore whether generative AI is more akin to an electrifying revolution or a blockchain phase. The panel highlights the importance of tackling the POC-to-production gap, understanding AI's failure modes, and balancing executive enthusiasm with employee workload. They also examine how AI's combinatorial abilities can redefine strategies, paralleling the success of AlphaZero in gaming.
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insights INSIGHT
Productivity Paradox
Generative AI's productivity impact is complex and not always positive.
Executives see potential, but employees report increased workloads, highlighting a disconnect.
insights INSIGHT
Web Moment
Generative AI's impact is similar to the web, transforming how we work.
It will create "before" and "after" moments in workflows, like the web did.
insights INSIGHT
Goal Engineering over Prompt Engineering
Generative AI can invent new algorithms, demonstrating runaway innovation in narrow scopes.
Shift from prompt engineering to goal engineering, letting AI optimize for defined metrics.
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Hugo Bowne-Anderson hosts a panel discussion from the MLOps World and Generative AI Summit in Austin, exploring the long-term growth of AI by distinguishing real problem-solving from trend-based solutions. If you're navigating the evolving landscape of generative AI, productionizing models, or questioning the hype, this episode dives into the tough questions shaping the field.
The panel features:
Ben Taylor (Jepson) – CEO and Founder at VEOX Inc., with experience in AI exploration, genetic programming, and deep learning.
Joe Reis – Co-founder of Ternary Data and author of Fundamentals of Data Engineering.
Juan Sequeda – Principal Scientist and Head of AI Lab at Data.World, known for his expertise in knowledge graphs and the semantic web.
The discussion unpacks essential topics such as:
The shift from prompt engineering to goal engineering—letting AI iterate toward well-defined objectives.
Whether generative AI is having an electricity moment or more of a blockchain trajectory.
The combinatorial power of AI to explore new solutions, drawing parallels to AlphaZero redefining strategy games.
The POC-to-production gap and why AI projects stall.
Failure modes, hallucinations, and governance risks—and how to mitigate them.
The disconnect between executive optimism and employee workload.
A huge thanks to Dave Scharbach and the Toronto Machine Learning Society for organizing the conference and to the audience for their thoughtful questions.
As we head into the new year, this conversation offers a reality check amidst the growing AI agent hype.
Vanishing Gradients 