Hear Helm.ai CEO Vlad Voroninski Discuss the Future of Mobility & Self-Driving Car Technology with Accelerated Podcast Host Vitaly Golomb
Ever stopped to wonder what the future of mobility looks like for humanity? Tune into the Accelerated podcast to hear Helm.ai CEO and co-founder Vlad Voroninski discuss that topic with host Vitaly Golomb. Here’s direct links to the episode:
- Spotify: https://loom.ly/wcEoGZk
- Apple Podcasts: https://loom.ly/QqZPHlk
- Podchaser: https://loom.ly/XpwbKJM
- Audible: https://loom.ly/ZCrpx70
- Accelerated Startup Academy: https://acceleratedstartupacademy.captivate.fm/listen
Over the course of their 45 minute conversation, Vlad dives deep into his motivations for starting Helm.ai with his co-founder and CTO Tudor Achim — discussing the origin story of the company, and making the leap from teaching at MIT to the world of deep tech entrepreneurship. They touch on the early days of self-driving cars during the DARPA Grand Challenges, the famed trolley problem for autonomous vehicles, and when we can expect to see true Level 4 and Level 5 autonomy.
Vlad and Vitaly (a Partner at Drake Star Partners) also discuss the biggest misconceptions many people in tech have about autonomy — such as the often flawed juxtaposition between LIDAR and computer vision, or the notion that heavily funded self-driving companies are ahead in the race to build a scalable and cost-effective self driving vehicle fleet. Finally, they explore Helm.ai’s novel approach to computer vision.
As you’ll hear in this episode, Vlad has a unique perspective on the advances in autonomous systems technologies that have been realized within the past decade. Previously co-founding Chief Scientist of Sift Security, which was acquired by Netskope, an Instructor and Postdoctoral fellow at MIT, as well as a PhD in mathematics at UC Berkeley, Vlad has earned numerous awards and accolades for his contributions to applied mathematics and machine learning, before delving into field of self driving cars and the development of Helm.ai’s unsupervised Deep Teaching technology.