{"podcast":{"title":"The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)","slug":"twiml-ai-podcast","podcast_index_feed_id":1045879,"rss_url":"https://feeds.megaphone.fm/MLN2155636147","website_url":"https://twimlai.com","image_url":"https://megaphone.imgix.net/podcasts/35230150-ee98-11eb-ad1a-b38cbabcd053/image/TWIML_AI_Podcast_Official_Cover_Art_1400px.png?ixlib=rails-4.3.1&max-w=3000&max-h=3000&fit=crop&auto=format,compress","author":"TWIML","episode_count":790,"summary":"Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Technologies covered include machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, computer science, data science and more.","last_synced_at":"2026-08-02T15:06:58.791455+00:00","page_url":"https://stenobird.com/podcast/twiml-ai-podcast"},"episode":{"title":"How AI Learns to Smell with Alex Wiltschko - #771","slug":"how-ai-learns-to-smell-with-alex-wiltschko-771","published_at":"2026-07-08T19:36:00+00:00","page_url":"https://stenobird.com/podcast/twiml-ai-podcast/how-ai-learns-to-smell-with-alex-wiltschko-771","show_page_url":"https://stenobird.com/podcast/twiml-ai-podcast","url":"https://twimlai.com/podcast/twimlai/how-ai-learns-smell","audio_url":"https://pscrb.fm/rss/p/traffic.megaphone.fm/MLN6387905777.mp3","summary":"Alex Wilchko, CEO of Osmo, explains how to bridge the gap between chemical structures and digital perception. The discussion focuses on building the 'map' required to digitize smell through graph neural networks and multi-dimensional embedding spaces.","meta_description":"Explore the frontier of olfactory intelligence: how AI uses graph neural networks to decode molecular structures and predict scents.","key_points":["Main idea: Digitizing smell requires a 'map' that translates molecular structures into a digital embedding space, similar to how RGB works for vision","Technical approach: Graph neural networks are used to process molecular macrostructures and propagate information into a 300-dimensional principle odor map","Practical takeaway: Building a self-perpetuating data loop involves using chemical sensors to feed proprietary datasets that train predictive models","Failure mode: The 'structure-odor relation problem' remained unsolved for a century because of the difficulty in mapping complex chemical inputs to human perception","Future potential: Olfactory intelligence could enable early disease detection, emotion sensing, and the creation of entirely new synthetic fragrances"],"chapters":[{"start_ms":60000,"title":"The Chemistry of Intelligence","summary":"The importance of training AI on the chemical language used by non-human species like bacteria and fungi."},{"start_ms":300000,"title":"The Biological Basis of Smell","summary":"Understanding olfactory sensory neurons and the genetic encoding of scent receptors."},{"start_ms":600000,"title":"Solving the Structure-Odor Problem","summary":"How neural networks can finally bridge the gap between molecular structure and perceived odor."},{"start_ms":840000,"title":"Graph Neural Networks in Olfaction","summary":"Using GNNs to process molecular graphs and capture multi-dimensional scent characteristics."},{"start_ms":1140000,"title":"Building Proprietary Datasets","summary":"The process of enumerating molecules and creating large-scale olfactory datasets."},{"start_ms":1380000,"title":"Aligning Sensors with Human Perception","summary":"Using chemical sensors to create data that can be mapped to human sensory labels."},{"start_ms":1680000,"title":"The Self-Perpetuating Data Loop","summary":"How fragrance design serves as both a business model and a source of continuous training data."}],"topics":["Olfactory Intelligence","Graph Neural Networks","Molecular Modeling","Chemical Sensors","Embedding Spaces","Chemoinformatics","Foundation Models","Digital Scent"],"duration_seconds":3595,"processing_state":"processed","actions":[{"name":"request_transcript","method":"POST","url":"https://stenobird.com/v1/public/podcasts/twiml-ai-podcast/episodes/how-ai-learns-to-smell-with-alex-wiltschko-771/transcription-requests","description":"Idempotently request low-priority transcript generation for this episode."},{"name":"read_markdown","method":"GET","url":"https://stenobird.com/podcast/twiml-ai-podcast/how-ai-learns-to-smell-with-alex-wiltschko-771.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}