Introducing Samsung NEXT Q Fund
We are excited to announce Samsung NEXT Q Fund, an early-stage venture fund focused on AI startups.
Why Q? In ML, researchers want to maximize “Q,” which is the quality of an action in noisy, partially observable environments. As venture investors, we’re trying to doing the same thing.
We are interested in startups tackling AI Grand Challenges. Problem spaces we are looking into include learning in simulation, scene understanding, intuitive physics, program learning programs, automl, robot control, human computer interaction, and meta learning, just to name a few.
We invest differently. We prefer novel techniques over solutions that “import ai.” We prioritize technical diligence over revenue models or go-to-market discussions. We are more likely to be convinced by the number of literature citations you have than pilot projects you’ve launched. If anything, you’re more likely to find us at CVPR than CES.
We take great pride in understanding your research and have surrounded ourselves with world-class researchers including Pieter Abbeel (UC Berkeley), Liangliang Cao (Columbia), Shih-Fu Chang (Columbia), David Duvenaud (Vector Institute), Joseph E. Gonzalez (UC Berkeley), Song Han (MIT), Tim Kraska (MIT), Zach Lipton (Carnegie Mellon), Olga Russakovsky (Princeton), Julian Togelius (NYU), and many others.
Our Q Fund portfolio is small but growing. We are proud investors in companies solving foundational problems in AI and robotics like Covariant AI and Vicarious. These investments are in addition to the eight AI investments made by Samsung NEXT in the past four years.
So whether you’re AI or IA centric, a tensorflow or pytorch enthusiast, a frequentist or bayesian, please reach out and say hello!
Vin & Ajay