
In this episode, Alex Wiltschko, founder and CEO of Osmo, joins the show to discuss his goal of giving computers a sense of smell and what it takes to build olfactory intelligence. We explore the science behind smell, from the hundreds of olfactory receptors in the human nose to the challenge of mapping the relationship between molecular structure and odor, ensuring safety regulations are met, and building foundation models for smell. Alex explains how graph neural networks and advanced embedding spaces allow AI to capture the multi-dimensional structure of scents, grouping them into perceptual neighborhoods, and creating a machine learning representation that predicts how molecules smell. We also cover how Osmo built the largest proprietary olfactory dataset from scratch to train a fleet of predictive models, and how olfactory intelligence could eventually power applications far beyond fragrance, including disease detection, emotion sensing, and consumer devices. 🗒️ Full show notes: https://twimlai.com/go/771.
Podzilla Summary coming soon
Sign up to get notified when the full AI-powered summary is ready.
Free forever for up to 3 podcasts. No credit card required.

Why Models Are AI’s Next Training Dataset with Damian Borth - #772

Why AI Agents Break the GenAI Security Model with Devvret Rishi - #770

Is RAG Dead? Lessons from Building AI for Tax Law with Alex Bowcut - #769

Relational Foundation Models for Enterprise Data with Jure Leskovec - #768
Free AI-powered recaps of The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) and your other favorite podcasts, delivered to your inbox.
Free forever for up to 3 podcasts. No credit card required.