Barry first found music when he borrowed his sister's record collection when he was about eight and was hooked. When Caroline started it was a new beginning, and he listened to all the stations, but Caroline was his favourite by far. Later he became a singer in a band, then started doing discos when he was 18. He joined Caroline in 1977, touring the country with the Caroline Roadshow for 10 years, having great fun. Barry helped with tender trips and worked on the Ross Revenge in '84 and '85. ...
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Trudy Painter – Algorithms behind AI - A case for technical literacy in AI
MP4•Episode-Home
Manage episode 437834440 series 1191096
Inhalt bereitgestellt von Video Archive – The Conference by Media Evolution. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Video Archive – The Conference by Media Evolution oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.
“It’s very fun to make AI tools magical. [...] But when you make AI feel airy, you remove the possibility for people to ask questions. So it’s better to make it approachable.”
Trudy is an active technology enthusiast who is convinced that AI tools can be as useful as electricity. By providing real-life examples and related metaphors of ceramic mugs and paper cups, the recent MIT graduate firmly believes that everyone can - and perhaps should - be able to understand AI tools and how the algorithm works “under the hood” in order to be better informed when making decisions around its usage and implementation in organisations.
Trudy conveys a clear and easy-to-follow explanation of how AI generation differs from the everyday search on our internet browsers. While search engines retrieve information from existing websites that the algorithm judges relevant, AI generation patches up an artifact which replicates human speech and predicts “the most likely next word” based on patterns observed in human interaction. AI literacy is hence of utmost relevance now that AI tools have reached their most capable and accessible stage yet.
500 Episoden
MP4•Episode-Home
Manage episode 437834440 series 1191096
Inhalt bereitgestellt von Video Archive – The Conference by Media Evolution. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Video Archive – The Conference by Media Evolution oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.
“It’s very fun to make AI tools magical. [...] But when you make AI feel airy, you remove the possibility for people to ask questions. So it’s better to make it approachable.”
Trudy is an active technology enthusiast who is convinced that AI tools can be as useful as electricity. By providing real-life examples and related metaphors of ceramic mugs and paper cups, the recent MIT graduate firmly believes that everyone can - and perhaps should - be able to understand AI tools and how the algorithm works “under the hood” in order to be better informed when making decisions around its usage and implementation in organisations.
Trudy conveys a clear and easy-to-follow explanation of how AI generation differs from the everyday search on our internet browsers. While search engines retrieve information from existing websites that the algorithm judges relevant, AI generation patches up an artifact which replicates human speech and predicts “the most likely next word” based on patterns observed in human interaction. AI literacy is hence of utmost relevance now that AI tools have reached their most capable and accessible stage yet.
500 Episoden
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