Hard Problems I want to back in 2024

It’s now a personal tradition to kick off the new year with a post that summarizes the areas I’m most interested for investment over the coming 12 months. As with each year, before I sit down to generate my list I reflect on my previous years and the methodology I used. With that in mind, I’m changing my approach for 2024.

In the past I’ve worn the self-appointed title of a “proudly anti-thesis investor” due to my still held belief that my job as a VC is not to predict the future but to identify and finance the talent that can. Given this, I have always worried that any predictive effort (i.e. thesis investing) would be lagging. But now with 2023 behind us I’m questioning this stance.

Though I still think it’s foolish to invest through a rigid / singular thesis at the pre-seed stage I have found the combinatorial power of a preparred mind undeniable. While I can make up a lot of ground through sheer curiosity and force of will I am so much better at my job when I have a shared language and world model with the founders I speak to. So for 2024 I am once again sharing a list of problems that I’m excited about backing but with the added public commitment that I will be developing mini thesis for each over the coming year.

  • AI Authentication - systems that ensure transparency and provenance / prevent the weaponization of AI

  • Compute Infrastructure - accelerating ML performance / significantly reducing inference cost through advanced, possibly application specific, hardware

  • Multipurpose Robotics - automation systems that can work in a variety of use environments via (near)zero-shot training

  • Material Science - identify and synthesize previously unknown materials to catalyze entirely new categories

  • Industrial Bio - transitioning away from extractive / petrochemical-heavy production

  • Reshoring / Deglobalization - rebuilding Western production capacity to account for the changing China positioning

  • In-orbit Manufacturing - leveraging the unique attributes of outer space to produce materials / compounds that are infeasible on Earth

  • Non-natural Carbon Capture - sequestration through engineered systems

  • Climate Reversal / Geo-Engineering - deliberate alteration of the climate via solar radiation reflection

  • Climate Adaptation - what systems are breaking today as a result of climate change? (e.g. weather modeling, border security, etc.)

  • Drug Repurposing - engineering better binding systems to revive Phase 1 drug failures

  • Full Stack Services - competing directly with service providers with an unattainable cost advantage

There are a few areas I’m interested in but don’t yet have strong enough of a sense that I will dedicate much time. A thesis backlog if you will.

  • Scientific Research Acceleration - ML could be really powerful in aggregating / distilling the highly distributed nature of research. But is there a venture scale outcome or is this a public good?

  • Nuclear Simulation - a frequent topic of my newsletter and (IMO) a critical component of an energy strategy, but likely non-viable for a purist pre-seed fund

  • Crypto Infrastructure - the current winter provides a nice opportunity for contrarian alpha, though the Europe follow on is particularly hard

  • Life Extension / Post-Biological - expanding the prime years of one’s life (vs. more elder years) or extending consciousness to silicon

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