How can business help solve society’s biggest challenges? Welcome to Series 3 of Take on Tomorrow, the award-winning podcast from PwC that examines the biggest problems facing society and the role business can—and should—play in solving them. This series, we’re welcoming broadcaster and journalist Femi Oke to the show. She joins podcaster and journalist Lizzie O’Leary, and together with industry innovators, tech trailblazers and visionary leaders from around the globe, they’ll explore timely ...
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AI Dialogues: exploring the significance of training AI models
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Manage episode 403988421 series 1528649
Sisällön tarjoaa RWS. RWS tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.
It's AI bingo at the moment! Everyone's talking about it - but did you know that the quality and quantity of training datasets are crucial to the accuracy and effectiveness of machine learning models? The more diverse and representative the data, the better the AI model can perform in terms of nuance. Did you ever wonder how to ensure that AI discerns what Americans would wear to a wedding? And what people would wear in Asia, Europe or Africa, taking into account the specificities of each country? In this enlightening AI dialogue episode of our Globally Speaking podcast, Melanie Peterson - Program Director for Train AI at RWS - joins Vasagi Kothandapani to discuss how she tackled one of her biggest AI challenges: a rating and labelling data project for western-style womenswear using resources in the APAC region only, where the raters were 80% male. Melanie unpacks the intricacies of her mission, shedding light on how she explains what she does to her family and friends, why a rocket scientist or a chef might have been involved in one of Train AI's latest data training projects, and what exactly we mean by data collection, data creation, data annotation and sentiment analysis. Get ready for a captivating exploration into the heart of AI.
…
continue reading
179 jaksoa
MP3•Jakson koti
Manage episode 403988421 series 1528649
Sisällön tarjoaa RWS. RWS tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.
It's AI bingo at the moment! Everyone's talking about it - but did you know that the quality and quantity of training datasets are crucial to the accuracy and effectiveness of machine learning models? The more diverse and representative the data, the better the AI model can perform in terms of nuance. Did you ever wonder how to ensure that AI discerns what Americans would wear to a wedding? And what people would wear in Asia, Europe or Africa, taking into account the specificities of each country? In this enlightening AI dialogue episode of our Globally Speaking podcast, Melanie Peterson - Program Director for Train AI at RWS - joins Vasagi Kothandapani to discuss how she tackled one of her biggest AI challenges: a rating and labelling data project for western-style womenswear using resources in the APAC region only, where the raters were 80% male. Melanie unpacks the intricacies of her mission, shedding light on how she explains what she does to her family and friends, why a rocket scientist or a chef might have been involved in one of Train AI's latest data training projects, and what exactly we mean by data collection, data creation, data annotation and sentiment analysis. Get ready for a captivating exploration into the heart of AI.
…
continue reading
179 jaksoa
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