Ambitious goals that solve important global problems through applied science, technology, and innovation. May include multisensory perception, intuitive physics, intuitive psychology, learning, language, planning and navigation, and emotion.
We invest in early stage AI startups taking on Grand Challenges.
We’re interested in
- Startups solving AI
- Startups solving computer science problems with AI
We Invest Differently
The more esoteric, exotic, and eccentric the approach, the better the fit.
- We prefer novel techniques over existing, off-the-shelf solutions.
- We prioritize technical diligence over revenue models or go-to-market discussions.
- We’re more likely to be convinced by the number of literature citations you have than pilot projects you’ve launched.
Our Advisors
We’re guided by a growing list of world-class researchers
Pieter Abbeel (UC Berkeley)
Shih-Fu Chang (Columbia)
David Duvenaud (Vector Institute)
Joseph E. Gonzalez (UC Berkeley)
Song Han (MIT)
Tim Kraska (MIT)
Zach Lipton (Carnegie Mellon)
Frank Rudzicz (University of Toronto)
Julian Togelius (NYU)
Why Q?
- If “AI is the new electricity,” then Q is the measure of electric charge
- Q is the quality of an action in reinforcement learning
- Q value = P value − false positives
Our Portfolio Companies Include
Team
We're more CVPR, less CES.
Ajay Singh
{work: [venture = 10, engineer = 5];
school: [engineer = @IITDelhi, law = @Northwestern, business = @Kellogg];
interests: [cognitive biases, first principles, moonwalk, jarvis]}
Vincent Tang
{work: [@samsungnext, @nygc];
school: @carnegiemellon;
mentor: [@ainexuslab, @techstars, @37angels, @creativedestructionlab];
contrib: [scikit, skimage, tpot, tsfresh, keras, textblob]
interests: [vintage computing, flying machines, turtlebots]}