I have a few core theses about the world, emerging science and technology at the “edges”, and new frontiers that shape my thinking as an early-stage investor. These are themes I’ve been seeing recently and encompass what I see to be important to build in order to make the world a better place and guide why I invest.

 

 

Cloud Computing Infrastructure

A large part of the rapid technological innovation we’ve seen since the turn of the century can be attributed to the transition to the cloud, as well as the tools that enable it. I believe we will see new use cases for cloud computing in the years to come, across all enterprise types, verticals, and geographies.

Tech-Enabled Marketplaces

Marketplaces, ever since their first iterations in ancient times and the nascent stages of human history, serve as a nexus for value creation and catalyst for economic growth. Technology is revolutionizing the concept of the marketplace, retaining its core purpose but expanding its scope - digital marketplaces now allow this economic value to be created irrespective of physical location. Tech-enabled marketplaces see immense opportunity given emerging trends in technology and consumer preferences. At their essence, marketplaces are about the collective good (every sale is also a purchase), which is a story that’s core to economics as a field.

Federated ML

New AI/ML necessitates a discussion of privacy, ethics, and privacy-preserving technology. Federated machine learning is one of the promising solutions to the issue of differential privacy with the implementation of new AI. Many industries have been unable to adopt ML because of privacy issues and data sensitivity, and federated ML can retain data ownership while enabling a model to train locally. Federated learning represents the intersection of distributed systems and privacy preservation, and has the potential to materialize the future of AI.

Edge AI

Local data processing is the path forward for an AI-integrated future, and edge AI technology is one of the ways to implement that. Edge AI gets to the closest point of interaction with the end user and maintains data security, and we all know that AI must be privacy-preserving in order for it to be realistically integrated into the facets of society we hope it to. Data network effects can also take hold and create a flywheel, as I discuss here.

Brain-Computer Interfaces

Research on BCIs began in the early 1970s but have recently garnered a lot of attention. BCIs have the potential to facilitate communication from the brain to an external device, which can aid human cognitive functions and leverage the immense processing power of the human brain. However, there is a cognitive bandwidth problem as the amount of data the human brain is able to synthesize, as well as the amount of data that the brain produces, far exceeds the processing capacity of any non-human interface. There is a discrepancy in the rate of data processing that has yet to be aligned, but once this interface compatibility problem is unlocked, there is enormous potential for BCIs to enhance human lives, especially those with diminished mobility or otherwise physical disability.

Healthcare AI

AI has the potential to impact every facet of the patient and provider experience, both in a clinical and non-clinical sense. While AI serving as the healthcare provider may seem more science fiction than not, with the patient-doctor experience continuing to be human-centric far into the future in my view, AI can be a disruptive catalyst for technological adoption within healthcare vis-à-vis a myriad of use cases. From diagnostics to treatment within the clinical setting, to patient engagement and data infrastructure/interoperability in the non-clinical - the healthcare space is poised for change and AI will be front and center of that transformation.

 

(Last edited 8/2020)