Robotics

Datacast Episode 114: Building Data Products and Unlocking Data Insights with Carlos Aguilar

Datacast Episode 114: Building Data Products and Unlocking Data Insights with Carlos Aguilar

Carlos Aguilar is the Founder and CEO of Glean, a data visualization company based in New York City.

He grew up in Washington, DC, where he started tinkering with robots and websites early on and fell in love with the intersection of art and technology. At Cornell, he studied Mechanical Engineering and robotics and did research in machine learning applications in robotics and art. In 2009, he joined an early robotics startup called Kiva Systems, where he got deep into data and analytics.

After Kiva was acquired by Amazon, Carlos joined Flatiron Health and worked on data products to help cancer centers and cancer researchers. As the head of the Data Insights team, Carlos grew the team to 25 people who helped launch dozens of data products and supported Flatiron's core data infrastructure.

Datacast Episode 100: Data-Centric Computer Vision, Productizing AI, and Scaling a Global Startup with Hyun Kim

Datacast Episode 100: Data-Centric Computer Vision, Productizing AI, and Scaling a Global Startup with Hyun Kim

Hyun Kim is the co-founder and CEO of Superb AI, an ML DataOps platform that helps computer vision teams automate and manage the entire data pipeline: from ingestion and labeling to data quality assessment and delivery. He initially studied Biomedical Engineering and Electrical Engineering at Duke but shifted from genetic engineering to robotics and deep learning. He then pursued a Ph.D. in computer science at Duke with a focus on Robotics and Deep Learning but ended up taking leave to further immerse himself in the world of AI R&D at a corporate research lab. During this time, he started to experience the bottlenecks and obstacles that many companies still face to this day: data labeling and management were very manual, and the available solutions were nowhere near sufficient.

Datacast Episode 33: Domain Randomization in Robotics with Josh Tobin

Datacast Episode 33: Domain Randomization in Robotics with Josh Tobin

Josh Tobin is the founder and CEO of a stealth machine learning startup. Previously, Josh worked as a deep learning & robotics researcher at OpenAI and as a management consultant at McKinsey. He is also the creator of Full Stack Deep Learning, the first course focused on the emerging engineering discipline of production machine learning. Josh did his Ph.D. in Computer Science at UC Berkeley, advised by Pieter Abbeel.