Open||Source||Data The Value of Reproducibility and Ease of AI Deployment with Daniel Lenton
This episode features an interview with Daniel Lenton, Founder and CEO of Ivy, where the team is on a mission to unify the fragmented AI stack. Prior to Ivy, Daniel was a Robotics Research Engineer at Dyson and a Deep Learning Research Scientist for Amazon Prime Air. During his PhD, Daniel explored the intersection between learning-based geometric representations, ego-centric perception, spatial memory, and visuomotor control for robotics.
In this episode, Sam and Daniel discuss the inspiration behind Ivy, open source reproducibility, and democratizing AI.
-------------------
"There's too much amazing stuff going on, from too many different parties. We just want to be the objective source of truth to show you the data and show you where your model will be doing best, and continue to do this as a service or something like this. This is high-level, some of the areas we see and going into, we really want to be a useful tool for anybody that wants to just kind of understand this fragmented complex space quickly and intuitively, and we are trying to be the tool that does that." – Daniel Lenton
-------------------
Episode Timestamps:
(01:00): What open source data means to Daniel
(05:37): The challenges of building Ivy
(15:37): The future of Ivy
(25:19): Who should know about Ivy
(28:46): Daniel’s advice for the audience
(32:00): Backstage takeaways with executive producer, Audra Montenegro
-------------------
Links: