State of the Future

I invest in computing hardware at pre-seed and seed stage. Traditional CMOS semiconductors are increasingly inadequate for AI workloads—both for energy-hungry training in data centers and low-power inference at the edge. To sustain computational growth, we need breakthroughs in architectures, designs, and materials that maximize performance per watt. I focus on emerging paradigms like photonic, analog, neuromorphic, temporal, quantum, and reversible computing, which rethink computation at the physical level.