The Quantum Branch Engine: Redefining AI Through Symbolic Intelligence

Join former NFL player and entrepreneur Johnny L. Williams, Founder & CEO of Player Epic, as he introduces the Quantum Branch Engine (QBE) a breakthrough in symbolic 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.

Artificial intelligence is evolving beyond prediction toward explanation. The Quantum Branch Engine (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 Williams breaks 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.