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AI in Automotive Podcast
Jayesh Jagasia
45 episodes
4 months ago
There is a lot of video in the world. Nearly 90% of global internet traffic is video. Getting value out of video data, however, is challenging, time-consuming and expensive. How do you identify the right subset of video data to train your models, and how do you reimagine the annotation process to accelerate vision AI application development are just some of the big questions that are looking for answers. On this episode of the AI in Automotive Podcast, I am delighted to be joined by Dr Jason ...
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There is a lot of video in the world. Nearly 90% of global internet traffic is video. Getting value out of video data, however, is challenging, time-consuming and expensive. How do you identify the right subset of video data to train your models, and how do you reimagine the annotation process to accelerate vision AI application development are just some of the big questions that are looking for answers. On this episode of the AI in Automotive Podcast, I am delighted to be joined by Dr Jason ...
Show more...
Marketing
Technology,
Business
https://is1-ssl.mzstatic.com/image/thumb/Podcasts221/v4/70/07/f9/7007f977-784c-4e76-0189-4b019232e920/mza_10279537135991083243.jpg/600x600bb.jpg
AI in Automotive - #403 - Daniel Langkilde - CEO, Kognic
AI in Automotive Podcast
47 minutes
2 years ago
AI in Automotive - #403 - Daniel Langkilde - CEO, Kognic
Autonomous Driving is a big enough paradigm shift. But after years of research and billions of dollars spent trying to get cars to drive themselves, perhaps it is time for a paradigm shift within a paradigm shift. What might this look like? Daniel Langkilde, CEO of Kognic joins me on the AI in Automotive Podcast to discuss exactly this. Daniel and I talk about the current approach to autonomy, which involves breaking down a very complex problem into its components - perception, pred...
AI in Automotive Podcast
There is a lot of video in the world. Nearly 90% of global internet traffic is video. Getting value out of video data, however, is challenging, time-consuming and expensive. How do you identify the right subset of video data to train your models, and how do you reimagine the annotation process to accelerate vision AI application development are just some of the big questions that are looking for answers. On this episode of the AI in Automotive Podcast, I am delighted to be joined by Dr Jason ...