Date: April 10–11, 2026
Location: Oxford Culinary Tech Lab
Abstract:
An exploration of how artificial intelligence is reshaping molecular gastronomy—from predictive recipe generation to sensory simulation and robotic plating.

Learning Objectives:

• Understand AI models used in gastronomy.

• Explore digital flavor prediction and algorithmic creativity.

• Examine case studies of AI-driven restaurants and labs.

Target Audience:
Chefs, data scientists, tech developers, culinary educators.

Structure:

• Opening Keynote: “Coding Taste: How AI Learns Flavor”

• Live Demo: Recipe Creation with GPT-Food Models

• Debate: Human Intuition vs. Algorithmic Creativity

• Workshop: Building a Culinary Dataset

Speakers:

• AI researchers (OpenAI, IBM Food Trust)

• Culinary innovators (Heston Blumenthal’s R&D team, or similar)

Outcomes:
Creation of a collaborative digital recipe dataset called “AI-GastroLab 2026.”