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 ...
All content for AI in Automotive Podcast is the property of Jayesh Jagasia and is served directly from their servers
with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
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 ...
AI in Automotive - #404 - David Hallac - CEO, Viaduct
AI in Automotive Podcast
41 minutes
1 year ago
AI in Automotive - #404 - David Hallac - CEO, Viaduct
Vehicle quality issues that lead to recalls and lawsuits cost automotive OEMs tens of billions of dollars in cost and lost revenue each year. Given the explosion of connected vehicle data, one might expect that this data could be leveraged to reduce this cost. Things are rarely that straightforward. Why is that? I invited David Hallac, CEO of Viaduct to the AI in Automotive Podcast to find out more. David’s 5-year old startup finds patterns and relationships amongst billions of connected vehi...
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 ...
