The Quantum Branch Engine: Redefining AI Through Symbolic Intelligence

Join former NFL player and entrepreneur Johnny L. Williams, founder and CEO of Player Epic, as he introduces the Quantum Branch Engine (QBE), a breakthrough in symbolic artificial intelligence (AI) that merges the precision of physics with the adaptability of human reasoning. Unlike conventional machine-learning systems, QBE operates on a quantum-inspired symbolic framework that produces transparent, deterministic outcomes while running efficiently on everyday hardware.

In this session, Johnny shares how this innovation is transforming industries — from aerospace and defense to health and gaming — revealing how physics-based reasoning can unlock a new era of trustworthy, human-aligned intelligence.

AI is evolving beyond prediction toward explanation. The QBE represents this next leap: a deterministic intelligence layer built to reason like a scientist and/or engineer rather than guess like a network.

In this talk, Johnny will break down what makes QBE different, why it challenges the boundaries of today’s black-box AI and how it enables organizations to see why a decision is made, not just the outcome.

Key takeaways include:

• Symbolic Reasoning in Action: How QBE models intelligence using structured relationships instead of statistical weights.
• CPU-Optimized AI: Achieving high performance and energy efficiency without GPU dependence.
• Applied Innovation: Real-world use cases spanning aerospace, healthcare, digital twins and simulation.
• Explainability by Design: How deterministic branching provides a complete audit trail for every output.
• From Athlete to Inventor: Lessons in translating real-world discipline and creativity into deep-tech entrepreneurship.

Students will leave inspired to explore how physics-inspired computation can drive the next generation of explainable, efficient and responsible AI.