Jason Bell is a contrarian voice in the AI industry, bringing mathematical rigor to an ecosystem drowning in marketing hype. With two decades of experience in machine learning and data science, he's become the go-to expert for exposing the statistical reality behind AI vendor claims.

His recent LinkedIn post calling "AI hallucination" marketing BS reached 345,000+ views, striking a nerve with developers and data scientists frustrated by industry snake oil. Jason's approach is simple: replace vendor fairy tales with mathematical truth.

Author of "Machine Learning: Hands-on for Developers and Technical Professionals" (Wiley, 2014, 2020), Jason bridges the gap between academic theory and practical implementation. He also contributed to "Machine Learning and the City," exploring ML applications in urban planning and population studies.

Currently developing the STAT Framework (Statistical Truth Assessment Toolkit), Jason helps organisations measure actual AI uncertainty instead of chasing imaginary "hallucination" solutions. The aim, his work saves companies millions by focusing on mathematical reality rather than marketing promises.

Jason actively reviews publication proposals for Wiley and writes for wilmott.com's quantitative finance section. He's known in the developer community for not holding back when calling out industry BS - backed by mathematics that vendors can't argue with.

When he's not demolishing AI marketing myths with probability theory, Jason advises organisations on practical machine learning implementations that actually work.