Using Machine Learning and AI to serve people and communities
summary
Starts with facial analysis in 1999 and shows concrete outcomes: learned filters that improve cochlear implant speech-in-noise, a tablet system that reunites refugees in five minutes from millions of photos, Google Glass that accelerates emotion recognition for autistic kids, a diabetes ML that can predict blood glucose an hour ahead, a 70,000-person contact-tracing study that backpropagates productivity to individuals, a 122 million-profile hiring dataset, EEG+LLM creativity tools, and a postpartum prediction model before delivery.
AI-written summary · about
chapters (14)
- 0:00Intro
- 5:43Problems with facial recognition
- 8:12Building cyborgs
- 13:24My favorite talk
- 20:19Google Glass
- 24:24Hacking Medical Devices
- 37:05Making Tech Hiring Fair
- 41:58Predicting Career Success
- 43:37Bias
- 45:29Big Social Network
- 47:57Purpose
- 51:04Why
- 56:47Postpartum Depression
- 58:42Building a better person
related talks
38mHow Artificial Intelligence has changed your life
47mBuilding smarter apps with Machine Learning, from magic to reality
57mBuilding smarter solutions with Machine Learning, from magic to reality
41mSpotlight on AI use cases and innovators around the world
56mArtificial Intelligence? - more like Artificial Stupidity!
26mArtificial Intelligence: The Recent Past
40mMachines are Learning
50mBuilding Intelligent Mobile Apps using Machine Learning