The Q Fund will provide Seed and Series A financing to startups solving AI problems, as well as those using AI to solve computer science problems.
“For the past ten years, we’ve watched software eat the world. Now, it’s AI’s turn to eat software,” said Vincent Tang, Samsung NEXT Ventures. “We’re launching Q Fund to support the next generation of AI startups who look to scratch beyond the surface of what we know today.”
Samsung NEXT is focused on what the world will look like in five years and beyond—and helping make that a reality. With Q Fund, Samsung NEXT Ventures will have the flexibility to invest in non-obvious, forward-thinking approaches to AI instead of the applied AI technologies we see in the market today.
Problem spaces Q Fund will examine could include areas such as learning in simulation, scene understanding, intuitive physics, program learning programs, AutoML (Machine Learning for Automated Algorithm Design), robot control, human computer interaction and meta learning.
“There are multiple approaches to building fundamental AI technology,” said Ajay Singh, Samsung NEXT Ventures. “And we want to invest in the people and teams who will try new approaches to lay the groundwork for what AI will be. For this reason, Q Fund will prioritize technical diligence over revenue models.”
Samsung NEXT has made several investments in AI from its Samsung NEXT Fund. From Q Fund specifically, the company recently invested in Covariant.AI, which draws on advances in imitation learning and deep reinforcement learning to teach robots new, complex skills.
“We’re at a critical juncture in the development of robotics—learning approaches are about to open up a wide range of new applications,” said Pieter Abbeel, Professor at Berkeley Electrical Engineering and Computer Sciences and founder of Covariant.AI. “Q Fund understands how many ‘grand challenge’ problems, including drastically expanding robotic capabilities, will be solvable with an AI-first approach.”
The Samsung NEXT team behind Q Fund works closely with world-class researchers to identify cutting-edge approaches to machine learning and perform technical diligence on new opportunities.